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Sample records for adaptive loop filter

  1. Performance Enhancement for a GPS Vector-Tracking Loop Utilizing an Adaptive Iterated Extended Kalman Filter

    PubMed Central

    Chen, Xiyuan; Wang, Xiying; Xu, Yuan

    2014-01-01

    This paper deals with the problem of state estimation for the vector-tracking loop of a software-defined Global Positioning System (GPS) receiver. For a nonlinear system that has the model error and white Gaussian noise, a noise statistics estimator is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) named adaptive iterated Kalman filter (AIEKF) is proposed. A vector-tracking GPS receiver utilizing AIEKF is implemented to evaluate the performance of the proposed method. Through road tests, it is shown that the proposed method has an obvious accuracy advantage over the IEKF and Adaptive Extended Kalman filter (AEKF) in position determination. The results show that the proposed method is effective to reduce the root-mean-square error (RMSE) of position (including longitude, latitude and altitude). Comparing with EKF, the position RMSE values of AIEKF are reduced by about 45.1%, 40.9% and 54.6% in the east, north and up directions, respectively. Comparing with IEKF, the position RMSE values of AIEKF are reduced by about 25.7%, 19.3% and 35.7% in the east, north and up directions, respectively. Compared with AEKF, the position RMSE values of AIEKF are reduced by about 21.6%, 15.5% and 30.7% in the east, north and up directions, respectively. PMID:25502124

  2. Filter for third order phase locked loops

    NASA Technical Reports Server (NTRS)

    Crow, R. B.; Tausworthe, R. C. (Inventor)

    1973-01-01

    Filters for third-order phase-locked loops are used in receivers to acquire and track carrier signals, particularly signals subject to high doppler-rate changes in frequency. A loop filter with an open-loop transfer function and set of loop constants, setting the damping factor equal to unity are provided.

  3. Adaptive particle filtering

    NASA Astrophysics Data System (ADS)

    Stevens, Mark R.; Gutchess, Dan; Checka, Neal; Snorrason, Magnús

    2006-05-01

    Image exploitation algorithms for Intelligence, Surveillance and Reconnaissance (ISR) and weapon systems are extremely sensitive to differences between the operating conditions (OCs) under which they are trained and the extended operating conditions (EOCs) in which the fielded algorithms are tested. As an example, terrain type is an important OC for the problem of tracking hostile vehicles from an airborne camera. A system designed to track cars driving on highways and on major city streets would probably not do well in the EOC of parking lots because of the very different dynamics. In this paper, we present a system we call ALPS for Adaptive Learning in Particle Systems. ALPS takes as input a sequence of video images and produces labeled tracks. The system detects moving targets and tracks those targets across multiple frames using a multiple hypothesis tracker (MHT) tightly coupled with a particle filter. This tracker exploits the strengths of traditional MHT based tracking algorithms by directly incorporating tree-based hypothesis considerations into the particle filter update and resampling steps. We demonstrate results in a parking lot domain tracking objects through occlusions and object interactions.

  4. Frequency domain FIR and IIR adaptive filters

    NASA Technical Reports Server (NTRS)

    Lynn, D. W.

    1990-01-01

    A discussion of the LMS adaptive filter relating to its convergence characteristics and the problems associated with disparate eigenvalues is presented. This is used to introduce the concept of proportional convergence. An approach is used to analyze the convergence characteristics of block frequency-domain adaptive filters. This leads to a development showing how the frequency-domain FIR adaptive filter is easily modified to provide proportional convergence. These ideas are extended to a block frequency-domain IIR adaptive filter and the idea of proportional convergence is applied. Experimental results illustrating proportional convergence in both FIR and IIR frequency-domain block adaptive filters is presented.

  5. Adaptive WMMR filters for edge enhancement

    NASA Astrophysics Data System (ADS)

    Zhou, Jun; Longbotham, Harold G.

    1993-05-01

    In this paper, an adaptive WMMR filter is introduced, which adaptively changes its window size to accommodate edge width variations. We prove that for any given one dimensional input signal convergence is to fixed points, which are PICO (piecewise constant), by iterative application of the adaptive WMMR filter. An application of the filters to one-D data (non- PICO) and images of printed circuit boards are then provided. Application to images in general is discussed.

  6. An estimator-predictor approach to PLL loop filter design

    NASA Technical Reports Server (NTRS)

    Statman, Joseph I.; Hurd, William J.

    1990-01-01

    The design of digital phase locked loops (DPLL) using estimation theory concepts in the selection of a loop filter is presented. The key concept, that the DPLL closed-loop transfer function is decomposed into an estimator and a predictor, is discussed. The estimator provides recursive estimates of phase, frequency, and higher-order derivatives, and the predictor compensates for the transport lag inherent in the loop.

  7. A Nonlinear Adaptive Filter for Gyro Thermal Bias Error Cancellation

    NASA Technical Reports Server (NTRS)

    Galante, Joseph M.; Sanner, Robert M.

    2012-01-01

    Deterministic errors in angular rate gyros, such as thermal biases, can have a significant impact on spacecraft attitude knowledge. In particular, thermal biases are often the dominant error source in MEMS gyros after calibration. Filters, such as J\\,fEKFs, are commonly used to mitigate the impact of gyro errors and gyro noise on spacecraft closed loop pointing accuracy, but often have difficulty in rapidly changing thermal environments and can be computationally expensive. In this report an existing nonlinear adaptive filter is used as the basis for a new nonlinear adaptive filter designed to estimate and cancel thermal bias effects. A description of the filter is presented along with an implementation suitable for discrete-time applications. A simulation analysis demonstrates the performance of the filter in the presence of noisy measurements and provides a comparison with existing techniques.

  8. Adaptive autofocusing: a closed-loop perspective.

    PubMed

    Zhang, Ying; Wen, Changyun; Soh, Yeng Chai; Fong, Aik Meng

    2005-04-01

    We present an adaptive autofocusing scheme. In this scheme, the focus measure is updated with focus tuning. To achieve this, we construct the focus measure by using image moments and develop an adaptive focus-tuning strategy to estimate the measure in closed loop. It is shown that the adaptive updating of the focus measure enables us to overcome the dependence of autofocusing on the image contents. Such an adaptive closed-loop focusing operation also effectively suppresses both the effect of the noise in optical imaging and the effect of time delay due to image processing time. Therefore a high accuracy of autofocusing is guaranteed. The effectiveness of the proposed scheme is demonstrated by simulations and experiments. PMID:15839269

  9. Objects tracking with adaptive correlation filters and Kalman filtering

    NASA Astrophysics Data System (ADS)

    Ontiveros-Gallardo, Sergio E.; Kober, Vitaly

    2015-09-01

    Object tracking is commonly used for applications such as video surveillance, motion based recognition, and vehicle navigation. In this work, a tracking system using adaptive correlation filters and robust Kalman prediction of target locations is proposed. Tracking is performed by means of multiple object detections in reduced frame areas. A bank of filters is designed from multiple views of a target using synthetic discriminant functions. An adaptive approach is used to improve discrimination capability of the synthesized filters adapting them to multiple types of backgrounds. With the help of computer simulation, the performance of the proposed algorithm is evaluated in terms of detection efficiency and accuracy of object tracking.

  10. Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

  11. Adaptive Inner-Loop Rover Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

    2006-01-01

    Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

  12. Adaptive Mallow's optimization for weighted median filters

    NASA Astrophysics Data System (ADS)

    Rachuri, Raghu; Rao, Sathyanarayana S.

    2002-05-01

    This work extends the idea of spectral optimization for the design of Weighted Median filters and employ adaptive filtering that updates the coefficients of the FIR filter from which the weights of the median filters are derived. Mallows' theory of non-linear smoothers [1] has proven to be of great theoretical significance providing simple design guidelines for non-linear smoothers. It allows us to find a set of positive weights for a WM filter whose sample selection probabilities (SSP's) are as close as possible to a SSP set predetermined by Mallow's. Sample selection probabilities have been used as a basis for designing stack smoothers as they give a measure of the filter's detail preserving ability and give non-negative filter weights. We will extend this idea to design weighted median filters admitting negative weights. The new method first finds the linear FIR filter coefficients adaptively, which are then used to determine the weights of the median filter. WM filters can be designed to have band-pass, high-pass as well as low-pass frequency characteristics. Unlike the linear filters, however, the weighted median filters are robust in the presence of impulsive noise, as shown by the simulation results.

  13. Adaptive control of large space structures using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.

  14. An estimator-predictor approach to PLL loop filter design

    NASA Technical Reports Server (NTRS)

    Statman, J. I.; Hurd, W. J.

    1986-01-01

    An approach to the design of digital phase locked loops (DPLLs), using estimation theory concepts in the selection of a loop filter, is presented. The key concept is that the DPLL closed-loop transfer function is decomposed into an estimator and a predictor. The estimator provides recursive estimates of phase, frequency, and higher order derivatives, while the predictor compensates for the transport lag inherent in the loop. This decomposition results in a straightforward loop filter design procedure, enabling use of techniques from optimal and sub-optimal estimation theory. A design example for a particular choice of estimator is presented, followed by analysis of the associated bandwidth, gain margin, and steady state errors caused by unmodeled dynamics. This approach is under consideration for the design of the Deep Space Network (DSN) Advanced Receiver Carrier DPLL.

  15. Adaptive filtering in biological signal processing.

    PubMed

    Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

    1990-01-01

    The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed. PMID:2180633

  16. Adaptable Iterative and Recursive Kalman Filter Schemes

    NASA Technical Reports Server (NTRS)

    Zanetti, Renato

    2014-01-01

    Nonlinear filters are often very computationally expensive and usually not suitable for real-time applications. Real-time navigation algorithms are typically based on linear estimators, such as the extended Kalman filter (EKF) and, to a much lesser extent, the unscented Kalman filter. The Iterated Kalman filter (IKF) and the Recursive Update Filter (RUF) are two algorithms that reduce the consequences of the linearization assumption of the EKF by performing N updates for each new measurement, where N is the number of recursions, a tuning parameter. This paper introduces an adaptable RUF algorithm to calculate N on the go, a similar technique can be used for the IKF as well.

  17. A comparison of methods for DPLL loop filter design

    NASA Technical Reports Server (NTRS)

    Aguirre, S.; Hurd, W. J.; Kumar, R.; Statman, J.

    1986-01-01

    Four design methodologies for loop filters for a class of digital phase-locked loops (DPLLs) are presented. The first design maps an optimum analog filter into the digital domain; the second approach designs a filter that minimizes in discrete time weighted combination of the variance of the phase error due to noise and the sum square of the deterministic phase error component; the third method uses Kalman filter estimation theory to design a filter composed of a least squares fading memory estimator and a predictor. The last design relies on classical theory, including rules for the design of compensators. Linear analysis is used throughout the article to compare different designs, and includes stability, steady state performance and transient behavior of the loops. Design methodology is not critical when the loop update rate can be made high relative to loop bandwidth, as the performance approaches that of continuous time. For low update rates, however, the miminization method is significantly superior to the other methods.

  18. Enhancement of Electrolaryngeal Speech by Adaptive Filtering.

    ERIC Educational Resources Information Center

    Espy-Wilson, Carol Y.; Chari, Venkatesh R.; MacAuslan, Joel M.; Huang, Caroline B.; Walsh, Michael J.

    1998-01-01

    A study tested the quality and intelligibility, as judged by several listeners, of four users' electrolaryngeal speech, with and without filtering to compensate for perceptually objectionable acoustic characteristics. Results indicated that an adaptive filtering technique produced a noticeable improvement in the quality of the Transcutaneous…

  19. Recursive total-least-squares adaptive filtering

    NASA Astrophysics Data System (ADS)

    Dowling, Eric M.; DeGroat, Ronald D.

    1991-12-01

    In this paper a recursive total least squares (RTLS) adaptive filter is introduced and studied. The TLS approach is more appropriate and provides more accurate results than the LS approach when there is error on both sides of the adaptive filter equation; for example, linear prediction, AR modeling, and direction finding. The RTLS filter weights are updated in time O(mr) where m is the filter order and r is the dimension of the tracked subspace. In conventional adaptive filtering problems, r equals 1, so that updates can be performed with complexity O(m). The updates are performed by tracking an orthonormal basis for the smaller of the signal or noise subspaces using a computationally efficient subspace tracking algorithm. The filter is shown to outperform both LMS and RLS in terms of tracking and steady state tap weight error norms. It is also more versatile in that it can adapt its weight in the absence of persistent excitation, i.e., when the input data correlation matrix is near rank deficient. Through simulation, the convergence and tracking properties of the filter are presented and compared with LMS and RLS.

  20. Adaptive control of large space structures using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures was studied. Lattice filters are used widely in the areas of speech and signal processing. Herein, they are used to identify the structural dynamics model of the flexible structures. This identified model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures control is engaged. This type of validation scheme prevents instability when the overall loop is closed. The results obtained from simulation were compared to those obtained from experiments. In this regard, the flexible beam and grid apparatus at the Aerospace Control Research Lab (ACRL) of NASA Langley Research Center were used as the principal candidates for carrying out the above tasks. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods.

  1. VSP wave separation by adaptive masking filters

    NASA Astrophysics Data System (ADS)

    Rao, Ying; Wang, Yanghua

    2016-06-01

    In vertical seismic profiling (VSP) data processing, the first step might be to separate the down-going wavefield from the up-going wavefield. When using a masking filter for VSP wave separation, there are difficulties associated with two termination ends of the up-going waves. A critical challenge is how the masking filter can restore the energy tails, the edge effect associated with these terminations uniquely exist in VSP data. An effective strategy is to implement masking filters in both τ-p and f-k domain sequentially. Meanwhile it uses a median filter, producing a clean but smooth version of the down-going wavefield, used as a reference data set for designing the masking filter. The masking filter is implemented adaptively and iteratively, gradually restoring the energy tails cut-out by any surgical mute. While the τ-p and the f-k domain masking filters target different depth ranges of VSP, this combination strategy can accurately perform in wave separation from field VSP data.

  2. Adaptive Filtering Using Recurrent Neural Networks

    NASA Technical Reports Server (NTRS)

    Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.

    2005-01-01

    A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

  3. Filtering Algebraic Multigrid and Adaptive Strategies

    SciTech Connect

    Nagel, A; Falgout, R D; Wittum, G

    2006-01-31

    Solving linear systems arising from systems of partial differential equations, multigrid and multilevel methods have proven optimal complexity and efficiency properties. Due to shortcomings of geometric approaches, algebraic multigrid methods have been developed. One example is the filtering algebraic multigrid method introduced by C. Wagner. This paper proposes a variant of Wagner's method with substantially improved robustness properties. The method is used in an adaptive, self-correcting framework and tested numerically.

  4. Musical noise reduction using an adaptive filter

    NASA Astrophysics Data System (ADS)

    Hanada, Takeshi; Murakami, Takahiro; Ishida, Yoshihisa; Hoya, Tetsuya

    2003-10-01

    This paper presents a method for reducing a particular noise (musical noise). The musical noise is artificially produced by Spectral Subtraction (SS), which is one of the most conventional methods for speech enhancement. The musical noise is the tin-like sound and annoying in human auditory. We know that the duration of the musical noise is considerably short in comparison with that of speech, and that the frequency components of the musical noise are random and isolated. In the ordinary SS-based methods, the musical noise is removed by the post-processing. However, the output of the ordinary post-processing is delayed since the post-processing uses the succeeding frames. In order to improve this problem, we propose a novel method using an adaptive filter. In the proposed system, the observed noisy signal is used as the input signal to the adaptive filter and the output of SS is used as the reference signal. In this paper we exploit the normalized LMS (Least Mean Square) algorithm for the adaptive filter. Simulation results show that the proposed method has improved the intelligibility of the enhanced speech in comparison with the conventional method.

  5. Adaptive noise Wiener filter for scanning electron microscope imaging system.

    PubMed

    Sim, K S; Teh, V; Nia, M E

    2016-01-01

    Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments. PMID:26235517

  6. Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering.

    PubMed

    Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V

    2015-01-01

    Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares. PMID:25983690

  7. Controller-structure interaction compensation using adaptive residual mode filters

    NASA Technical Reports Server (NTRS)

    Davidson, Roger A.; Balas, Mark J.

    1990-01-01

    It is not feasible to construct controllers for large space structures or large scale systems (LSS's) which are of the same order as the structures. The complexity of the dynamics of these systems is such that full knowledge of its behavior cannot by processed by today's controller design methods. The controller for system performance of such a system is therefore based on a much smaller reduced-order model (ROM). Unfortunately, the interaction between the LSS and the ROM-based controller can produce instabilities in the closed-loop system due to the unmodeled dynamics of the LSS. Residual mode filters (RMF's) allow the systematic removal of these instabilities in a matter which does not require a redesign of the controller. In addition RMF's have a strong theoretical basis. As simple first- or second-order filters, the RMF CSI compensation technique is at once modular, simple and highly effective. RMF compensation requires knowledge of the dynamics of the system modes which resulted in the previous closed-loop instabilities (the residual modes), but this information is sometimes known imperfectly. An adaptive, self-tuning RMF design, which compensates for uncertainty in the frequency of the residual mode, has been simulated using continuous-time and discrete-time models of a flexible robot manipulator. Work has also been completed on the discrete-time experimental implementation on the Martin Marietta flexible robot manipulator experiment. This paper will present the results of that work on adaptive, self-tuning RMF's, and will clearly show the advantage of this adaptive compensation technique for controller-structure interaction (CSI) instabilities in actively-controlled LSS's.

  8. Attitude determination using an adaptive multiple model filtering Scheme

    NASA Technical Reports Server (NTRS)

    Lam, Quang; Ray, Surendra N.

    1995-01-01

    Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown

  9. Attitude determination using an adaptive multiple model filtering Scheme

    NASA Astrophysics Data System (ADS)

    Lam, Quang; Ray, Surendra N.

    1995-05-01

    Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown

  10. Adaptive filters for detection of gravitational waves from coalescing binaries

    SciTech Connect

    Eleuteri, Antonio; Milano, Leopoldo; De Rosa, Rosario; Garufi, Fabio; Acernese, Fausto; Barone, Fabrizio; Giordano, Lara; Pardi, Silvio

    2006-06-15

    In this work we propose use of infinite impulse response adaptive line enhancer (IIR ALE) filters for detection of gravitational waves from coalescing binaries. We extend our previous work and define an adaptive matched filter structure. Filter performance is analyzed in terms of the tracking capability and determination of filter parameters. Furthermore, following the Neyman-Pearson strategy, receiver operating characteristics are derived, with closedform expressions for detection threshold, false alarm, and detection probability. Extensive tests demonstrate the effectiveness of adaptive filters both in terms of small computational cost and robustness.

  11. Reduction of MPEG ringing artifacts using adaptive sigma filter

    NASA Astrophysics Data System (ADS)

    Pan, Hao

    2006-01-01

    In this paper, we propose a novel computationally efficient post-processing algorithm to reduce ringing artifacts in the decoded DCT-coded video without using coding information. While the proposed algorithm is based on edge information as most filtering-based de-ringing algorithms do, this algorithm solely uses one single computationally efficient nonlinear filter, namely sigma filter, for both edge detection and smoothing. Specifically, the sigma filter, which was originally designed for nonlinear filtering, is extended to generate edge proximity information. Different from other adaptive filtering-based methods, whose filters typically use a fixed small window but flexible weights, this sigma filter adaptively switches between small and large windows. The adaptation is designed for removing ringing artifacts only, so the algorithm cannot be used for de-blocking. Overall, the proposed algorithm achieves a good balance among removing ringing artifacts, preserving edges and details, and computational complexity.

  12. Adaptive filtering image preprocessing for smart FPA technology

    NASA Astrophysics Data System (ADS)

    Brooks, Geoffrey W.

    1995-05-01

    This paper discusses two applications of adaptive filters for image processing on parallel architectures. The first, based on the results of previously accomplished work, summarizes the analyses of various adaptive filters implemented for pixel-level image prediction. FIR filters, fixed and adaptive IIR filters, and various variable step size algorithms were compared with a focus on algorithm complexity against the ability to predict future pixel values. A gaussian smoothing operation with varying spatial and temporal constants were also applied for comparisons of random noise reductions. The second application is a suggestion to use memory-adaptive IIR filters for detecting and tracking motion within an image. Objects within an image are made of edges, or segments, with varying degrees of motion. An application has been previously published that describes FIR filters connecting pixels and using correlations to determine motion and direction. This implementation seems limited to detecting motion coinciding with FIR filter operation rate and the associated harmonics. Upgrading the FIR structures with adaptive IIR structures can eliminate these limitations. These and any other pixel-level adaptive filtering application require data memory for filter parameters and some basic computational capability. Tradeoffs have to be made between chip real estate and these desired features. System tradeoffs will also have to be made as to where it makes the most sense to do which level of processing. Although smart pixels may not be ready to implement adaptive filters, applications such as these should give the smart pixel designer some long range goals.

  13. Turbo LMS algorithm: supercharger meets adaptive filter

    NASA Astrophysics Data System (ADS)

    Meyer-Baese, Uwe

    2006-04-01

    Adaptive digital filters (ADFs) are, in general, the most sophisticated and resource intensive components of modern digital signal processing (DSP) and communication systems. Improvements in performance or the complexity of ADFs can have a significant impact on the overall size, speed, and power properties of a complete system. The least mean square (LMS) algorithm is a popular algorithm for coefficient adaptation in ADF because it is robust, easy to implement, and a close approximation to the optimal Wiener-Hopf least mean square solution. The main weakness of the LMS algorithm is the slow convergence, especially for non Markov-1 colored noise input signals with high eigenvalue ratios (EVRs). Since its introduction in 1993, the turbo (supercharge) principle has been successfully applied in error correction decoding and has become very popular because it reaches the theoretical limits of communication capacity predicted 5 decades ago by Shannon. The turbo principle applied to LMS ADF is analogous to the turbo principle used for error correction decoders: First, an "interleaver" is used to minimize crosscorrelation, secondly, an iterative improvement which uses the same data set several times is implemented using the standard LMS algorithm. Results for 6 different interleaver schemes for EVR in the range 1-100 are presented.

  14. Adaptive identification and control of structural dynamics systems using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Montgomery, R. C.; Williams, J. P.

    1985-01-01

    A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

  15. Open loop liquid crystal adaptive optics systems: progresses and results

    NASA Astrophysics Data System (ADS)

    Cao, Zhao-liang; Mu, Quan-quan; Xu, Huan-yu; Zhang, Pei-guang; Yao, Li-shuang; Xuan, Li

    2015-10-01

    Liquid crystal wavefront corrector (LCWFC) is one of the most attractive wavefront correction devices for adaptive optics system. The main disadvantages for conventional nematic LCWFC are polarization dependence and narrow working waveband. In this paper, a polarized beam splitter (PBS) based open loop optical design and an optimized energy splitting method was used to overcome these problems respectively. The results indicate that the open loop configuration was suitable for LCWFC and the novel energy splitting method can significantly improve the detection capability of the liquid crystal adaptive optics system.

  16. Tracking performance of unbalanced QPSK demodulators. I - Biphase Costas loop with passive arm filters

    NASA Technical Reports Server (NTRS)

    Simon, M. K.; Alem, W. K.

    1978-01-01

    Unbalanced quadriphase-shift-keying (QPSK) is an attractive means for transmitting two digital data streams which in general have different average powers, data rates, and data formats. Previous analyses of the tracking performance of Costas loop demodulators of unbalanced QPSK have accounted only for the filtering effect produced by the loop's two arm filters on the equivalent additive noise perturbing the loop. When the bandwidth of these filters is selected on the basis of the order of the data rate, as is typical of optimum Costas loop design, the filtering degradations of the data modulations themselves and the cross-modulation noise produced by their multiplication in the loop often cannot be neglected. The purpose of this paper is to incorporate these additional filtering effects into the analysis. Many of the results obtained herein are in the form of closed-form expressions which can easily be evaluated numerically for design and performance prediction purposes.

  17. Autonomous navigation system using a fuzzy adaptive nonlinear H∞ filter.

    PubMed

    Outamazirt, Fariz; Li, Fu; Yan, Lin; Nemra, Abdelkrim

    2014-01-01

    Although nonlinear H∞ (NH∞) filters offer good performance without requiring assumptions concerning the characteristics of process and/or measurement noises, they still require additional tuning parameters that remain fixed and that need to be determined through trial and error. To address issues associated with NH∞ filters, a new SINS/GPS sensor fusion scheme known as the Fuzzy Adaptive Nonlinear H∞ (FANH∞) filter is proposed for the Unmanned Aerial Vehicle (UAV) localization problem. Based on a real-time Fuzzy Inference System (FIS), the FANH∞ filter continually adjusts the higher order of the Taylor development thorough adaptive bounds  and adaptive disturbance attenuation , which significantly increases the UAV localization performance. The results obtained using the FANH∞ navigation filter are compared to the NH∞ navigation filter results and are validated using a 3D UAV flight scenario. The comparison proves the efficiency and robustness of the UAV localization process using the FANH∞ filter. PMID:25244587

  18. The adaptive-loop-gain adaptive-scale CLEAN deconvolution of radio interferometric images

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Zhang, M.; Liu, X.

    2016-05-01

    CLEAN algorithms are a class of deconvolution solvers which are widely used to remove the effect of the telescope Point Spread Function (PSF). Loop gain is one important parameter in CLEAN algorithms. Currently the parameter is fixed during deconvolution, which restricts the performance of CLEAN algorithms. In this paper, we propose a new deconvolution algorithm with an adaptive loop gain scheme, which is referred to as the adaptive-loop-gain adaptive-scale CLEAN (Algas-Clean) algorithm. The test results show that the new algorithm can give a more accurate model with faster convergence.

  19. Superresolution restoration of an image sequence: adaptive filtering approach.

    PubMed

    Elad, M; Feuer, A

    1999-01-01

    This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented. PMID:18262881

  20. Filter. Remix. Make.: Cultivating Adaptability through Multimodality

    ERIC Educational Resources Information Center

    Dusenberry, Lisa; Hutter, Liz; Robinson, Joy

    2015-01-01

    This article establishes traits of adaptable communicators in the 21st century, explains why adaptability should be a goal of technical communication educators, and shows how multimodal pedagogy supports adaptability. Three examples of scalable, multimodal assignments (infographics, research interviews, and software demonstrations) that evidence…

  1. Real time adaptive filtering for digital X-ray applications.

    PubMed

    Bockenbach, Olivier; Mangin, Michel; Schuberth, Sebastian

    2006-01-01

    Over the last decade, many methods for adaptively filtering a data stream have been proposed. Those methods have applications in two dimensional imaging as well as in three dimensional image reconstruction. Although the primary objective of this filtering technique is to reduce the noise while avoiding to blur the edges, diagnostic, automated segmentation and surgery show a growing interest in enhancing the features contained in the image flow. Most of the methods proposed so far emerged from thorough studies of the physics of the considered modality and therefore show only a marginal capability to be extended across modalities. Moreover, adaptive filtering belongs to the family of processing intensive algorithms. Existing technology has often driven to simplifications and modality specific optimization to sustain the expected performances. In the specific case of real time digital X-ray as used surgery, the system has to sustain a throughput of 30 frames per second. In this study, we take a generalized approach for adaptive filtering based on multiple oriented filters. Mapping the filtering part to the embedded real time image processing while a user/application defined adaptive recombination of the filter outputs allow to change the smoothing and edge enhancement properties of the filter without changing the oriented filter parameters. We have implemented the filtering on a Cell Broadband Engine processor and the adaptive recombination on an off-the-shelf PC, connected via Gigabit Ethernet. This implementation is capable of filtering images of 5122 pixels at a throughput in excess of 40 frames per second while allowing to change the parameters in real time. PMID:17354937

  2. Adaptive Control of Flexible Structures Using Residual Mode Filters

    NASA Technical Reports Server (NTRS)

    Balas, Mark J.; Frost, Susan

    2010-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

  3. Adaptive median filtering for preprocessing of time series measurements

    NASA Technical Reports Server (NTRS)

    Paunonen, Matti

    1993-01-01

    A median (L1-norm) filtering program using polynomials was developed. This program was used in automatic recycling data screening. Additionally, a special adaptive program to work with asymmetric distributions was developed. Examples of adaptive median filtering of satellite laser range observations and TV satellite time measurements are given. The program proved to be versatile and time saving in data screening of time series measurements.

  4. A Windowing Frequency Domain Adaptive Filter for Acoustic Echo Cancellation

    NASA Astrophysics Data System (ADS)

    Wu, Sheng; Qiu, Xiaojun

    This letter proposes a windowing frequency domain adaptive algorithm, which reuses the filtering error to apply window function in the filter updating symmetrically. By using a proper window function to reduce the negative influence of the spectral leakage, the proposed algorithm can significantly improve the performance of the acoustic echo cancellation for speech signals.

  5. Likelihood Methods for Adaptive Filtering and Smoothing. Technical Report #455.

    ERIC Educational Resources Information Center

    Butler, Ronald W.

    The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…

  6. A hybrid method for optimization of the adaptive Goldstein filter

    NASA Astrophysics Data System (ADS)

    Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue

    2014-12-01

    The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.

  7. Estimated spectrum adaptive postfilter and the iterative prepost filtering algirighms

    NASA Technical Reports Server (NTRS)

    Linares, Irving (Inventor)

    2004-01-01

    The invention presents The Estimated Spectrum Adaptive Postfilter (ESAP) and the Iterative Prepost Filter (IPF) algorithms. These algorithms model a number of image-adaptive post-filtering and pre-post filtering methods. They are designed to minimize Discrete Cosine Transform (DCT) blocking distortion caused when images are highly compressed with the Joint Photographic Expert Group (JPEG) standard. The ESAP and the IPF techniques of the present invention minimize the mean square error (MSE) to improve the objective and subjective quality of low-bit-rate JPEG gray-scale images while simultaneously enhancing perceptual visual quality with respect to baseline JPEG images.

  8. Lossless compression of weight vectors from an adaptive filter

    SciTech Connect

    Bredemann, M.V.; Elliott, G.R.; Stearns, S.D.

    1994-08-01

    Techniques for lossless waveform compression can be applied to the transmission of weight vectors from an orbiting satellite. The vectors, which are a part of a hybrid analog/digital adaptive filter, are a representation of the radio frequency background seen by the satellite. An approach is used which treats each adaptive weight as a time-varying waveform.

  9. Analysis on Influence Factors of Adaptive Filter Acting on ANC

    NASA Astrophysics Data System (ADS)

    Zhang, Xiuqun; Zou, Liang; Ni, Guangkui; Wang, Xiaojun; Han, Tao; Zhao, Quanfu

    The noise problem has become more and more serious in recent years. The adaptive filter theory which is applied in ANC [1] (active noise control) has also attracted more and more attention. In this article, the basic principle and algorithm of adaptive theory are both researched. And then the influence factor that affects its covergence rate and noise reduction is also simulated.

  10. Filter-free wavelength converter using Sagnac loop and delayed interferometer

    NASA Astrophysics Data System (ADS)

    Tsuji, K.; Yamaguchi, T.; Onodera, N.; Saruwatari, M.

    2006-01-01

    A filter-free fiber-XPM-based wavelength converter is proposed and experimentally demonstrated without conventional bandpass optical filters used to filter out the converted signal. The converter is constructed with a propagation-diversity Sagnac loop to separate a converted signal from a pump signal and a delayed interferometer to covert the XPM signal into intensity modulation. We show that 10-Gbit/s input signals are successfully converted to signals with allotted wavelengths by our proposed scheme.

  11. Improving nonlinear modeling capabilities of functional link adaptive filters.

    PubMed

    Comminiello, Danilo; Scarpiniti, Michele; Scardapane, Simone; Parisi, Raffaele; Uncini, Aurelio

    2015-09-01

    The functional link adaptive filter (FLAF) represents an effective solution for online nonlinear modeling problems. In this paper, we take into account a FLAF-based architecture, which separates the adaptation of linear and nonlinear elements, and we focus on the nonlinear branch to improve the modeling performance. In particular, we propose a new model that involves an adaptive combination of filters downstream of the nonlinear expansion. Such combination leads to a cooperative behavior of the whole architecture, thus yielding a performance improvement, particularly in the presence of strong nonlinearities. An advanced architecture is also proposed involving the adaptive combination of multiple filters on the nonlinear branch. The proposed models are assessed in different nonlinear modeling problems, in which their effectiveness and capabilities are shown. PMID:26057613

  12. Dynamic analysis of neural encoding by point process adaptive filtering.

    PubMed

    Eden, Uri T; Frank, Loren M; Barbieri, Riccardo; Solo, Victor; Brown, Emery N

    2004-05-01

    Neural receptive fields are dynamic in that with experience, neurons change their spiking responses to relevant stimuli. To understand how neural systems adapt their representations of biological information, analyses of receptive field plasticity from experimental measurements are crucial. Adaptive signal processing, the well-established engineering discipline for characterizing the temporal evolution of system parameters, suggests a framework for studying the plasticity of receptive fields. We use the Bayes' rule Chapman-Kolmogorov paradigm with a linear state equation and point process observation models to derive adaptive filters appropriate for estimation from neural spike trains. We derive point process filter analogues of the Kalman filter, recursive least squares, and steepest-descent algorithms and describe the properties of these new filters. We illustrate our algorithms in two simulated data examples. The first is a study of slow and rapid evolution of spatial receptive fields in hippocampal neurons. The second is an adaptive decoding study in which a signal is decoded from ensemble neural spiking activity as the receptive fields of the neurons in the ensemble evolve. Our results provide a paradigm for adaptive estimation for point process observations and suggest a practical approach for constructing filtering algorithms to track neural receptive field dynamics on a millisecond timescale. PMID:15070506

  13. Local adaptive filtering of images corrupted by nonstationary noise

    NASA Astrophysics Data System (ADS)

    Lukin, Vladimir V.; Fevralev, Dmitriy V.; Ponomarenko, Nikolay N.; Pogrebnyak, Oleksiy B.; Egiazarian, Karen O.; Astola, Jaakko T.

    2009-02-01

    In various practical situations of remote sensing image processing it is assumed that noise is nonstationary and no a priory information on noise dependence on local mean or about local properties of noise statistics is available. It is shown that in such situations it is difficult to find a proper filter for effective image processing, i.e., for noise removal with simultaneous edge/detail preservation. To deal with such images, a local adaptive filter based on discrete cosine transform in overlapping blocks is proposed. A threshold is set locally based on a noise standard deviation estimate obtained for each block. Several other operations to improve performance of the locally adaptive filter are proposed and studied. The designed filter effectiveness is demonstrated for simulated data as well as for real life radar remote sensing and marine polarimetric radar images.

  14. Acoustic Echo Cancellation Using Sub-Adaptive Filter

    NASA Astrophysics Data System (ADS)

    Ohta, Satoshi; Kajikawa, Yoshinobu; Nomura, Yasuo

    In the acoustic echo canceller (AEC), the step-size parameter of the adaptive filter must be varied according to the situation if double talk occurs and/or the echo path changes. We propose an AEC that uses a sub-adaptive filter. The proposed AEC can control the step-size parameter according to the situation. Moreover, it offers superior convergence compared to the conventional AEC even when the double talk and the echo path change occur simultaneously. Simulations demonstrate that the proposed AEC can achieve higher ERLE and faster convergence than the conventional AEC. The computational complexity of the proposed AEC can be reduced by reducing the number of taps of the sub-adaptive filter.

  15. Fault-tolerant adaptive FIR filters using variable detection threshold

    NASA Astrophysics Data System (ADS)

    Lin, L. K.; Redinbo, G. R.

    1994-10-01

    Adaptive filters are widely used in many digital signal processing applications, where tap weight of the filters are adjusted by stochastic gradient search methods. Block adaptive filtering techniques, such as block least mean square and block conjugate gradient algorithm, were developed to speed up the convergence as well as improve the tracking capability which are two important factors in designing real-time adaptive filter systems. Even though algorithm-based fault tolerance can be used as a low-cost high level fault-tolerant technique to protect the aforementioned systems from hardware failures with minimal hardware overhead, the issue of choosing a good detection threshold remains a challenging problem. First of all, the systems usually only have limited computational resources, i.e., concurrent error detection and correction is not feasible. Secondly, any prior knowledge of input data is very difficult to get in practical settings. We propose a checksum-based fault detection scheme using two-level variable detection thresholds that is dynamically dependent on the past syndromes. Simulations show that the proposed scheme reduces the possibility of false alarms and has a high degree of fault coverage in adaptive filter systems.

  16. Robust Wiener filtering for Adaptive Optics

    SciTech Connect

    Poyneer, L A

    2004-06-17

    In many applications of optical systems, the observed field in the pupil plane has a non-uniform phase component. This deviation of the phase of the field from uniform is called a phase aberration. In imaging systems this aberration will degrade the quality of the images. In the case of a large astronomical telescope, random fluctuations in the atmosphere lead to significant distortion. These time-varying distortions can be corrected using an Adaptive Optics (AO) system, which is a real-time control system composed of optical, mechanical and computational parts. Adaptive optics is also applicable to problems in vision science, laser propagation and communication. For a high-level overview, consult this web site. For an in-depth treatment of the astronomical case, consult these books.

  17. An information theoretic approach of designing sparse kernel adaptive filters.

    PubMed

    Liu, Weifeng; Park, Il; Principe, José C

    2009-12-01

    This paper discusses an information theoretic approach of designing sparse kernel adaptive filters. To determine useful data to be learned and remove redundant ones, a subjective information measure called surprise is introduced. Surprise captures the amount of information a datum contains which is transferable to a learning system. Based on this concept, we propose a systematic sparsification scheme, which can drastically reduce the time and space complexity without harming the performance of kernel adaptive filters. Nonlinear regression, short term chaotic time-series prediction, and long term time-series forecasting examples are presented. PMID:19923047

  18. Design of a nonlinear adaptive filter for suppression of shuttle pilot-induced oscillation tendencies

    NASA Technical Reports Server (NTRS)

    Smith, J. W.; Edwards, J. W.

    1980-01-01

    Analysis of a longitudinal pilot-induced oscillation (PIO) experienced just prior to touchdown on the final flight of the space shuttle's approach landing tests indicated that the source of the problem was a combination of poor basic handling qualities aggravated by time delays through the digital flight control computer and rate limiting of the elevator actuators due to high pilot gain. A nonlinear PIO suppression (PIOS) filter was designed and developed to alleviate the vehicle's PIO tendencies by reducing the gain in the command path. From analytical and simulator studies it was shown that the PIOS filter, in an adaptive fashion, can attenuate the command path gain without adding phase lag to the system. With the pitch attitude loop of a simulated shuttle model closed, the PIOS filter increased the gain margin by a factor of about two.

  19. A New Method to Cancel RFI---The Adaptive Filter

    NASA Astrophysics Data System (ADS)

    Bradley, R.; Barnbaum, C.

    1996-12-01

    An increasing amount of precious radio frequency spectrum in the VHF, UHF, and microwave bands is being utilized each year to support new commercial and military ventures, and all have the potential to interfere with radio astronomy observations. Some radio spectral lines of astronomical interest occur outside the protected radio astronomy bands and are unobservable due to heavy interference. Conventional approaches to deal with RFI include legislation, notch filters, RF shielding, and post-processing techniques. Although these techniques are somewhat successful, each suffers from insufficient interference cancellation. One concept of interference excision that has not been used before in radio astronomy is adaptive interference cancellation. The concept of adaptive interference canceling was first introduced in the mid-1970s as a way to reduce unwanted noise in low frequency (audio) systems. Examples of such systems include the canceling of maternal ECG in fetal electrocardiography and the reduction of engine noise in the passenger compartment of automobiles. Only recently have high-speed digital filter chips made adaptive filtering possible in a bandwidth as large a few megahertz, finally opening the door to astronomical uses. The system consists of two receivers: the main beam of the radio telescope receives the desired signal corrupted by RFI coming in the sidelobes, and the reference antenna receives only the RFI. The reference antenna is processed using a digital adaptive filter and then subtracted from the signal in the main beam, thus producing the system output. The weights of the digital filter are adjusted by way of an algorithm that minimizes, in a least-squares sense, the power output of the system. Through an adaptive-iterative process, the interference canceler will lock onto the RFI and the filter will adjust itself to minimize the effect of the RFI at the system output. We are building a prototype 100 MHz receiver and will measure the cancellation

  20. Microwave photonic notch filter based on a dual-Sagnac-loop structure.

    PubMed

    Wang, Xudong; Chan, Erwin H W; Minasian, Robert A

    2010-11-20

    A new single-wavelength, coherence-free microwave photonic notch filter is presented. The concept is based on a dual-Sagnac-loop structure that functions with a new principle in which the two loops operate with different free spectral ranges, and which generate noncommensurate taps. It has the ability to generate a narrow notch response and can operate to high frequencies. Experimental results demonstrate a notch filter with a narrow notch width, a flat passband, and high stop-band attenuation of over 40dB. PMID:21102681

  1. Enhancing Adaptive Filtering Approaches for Land Data Assimilation Systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent work has presented the initial application of adaptive filtering techniques to land surface data assimilation systems. Such techniques are motivated by our current lack of knowledge concerning the structure of large-scale error in either land surface modeling output or remotely-sensed estima...

  2. An improved adaptive deblocking filter for MPEG video decoder

    NASA Astrophysics Data System (ADS)

    Kwon, Do-Kyoung; Shen, Mei-Yin; Kuo, C.-C. Jay

    2005-03-01

    A highly adaptive deblocking algorithm is proposed for MPEG video in this research. In comparison with previous work in this area, the proposed deblocking filter improves in three aspects. First, the proposed algorithm is adaptive to the change of the quantization parameter (QP). Since blocking artifacts between two blocks encoded with different QPs tend to be more visible due to quality difference, filters should be able to adapt dynamically to the QP change between blocks. Second, the proposed algorithm classifies the block boundary into three different region modes based on local region characteristics. The three modes are active, smooth and dormant regions. The active region represents a complex region with details and high activities while the smooth and the dormant regions refer to moderately flat and extremely flat regions, respectively. By applying different filters of different strengths to each region mode, the proposed algorithm can minimize the undesirable blur so that both subjective and objective qualities improve for various types of sequences at a wide range of bitrates. Finally, the proposed algorithm also provides a way to determine the threshold values. The proposed adaptive deblocking algorithms require several thresholds in determining proper region modes and filters. Since the quality of image sequences after filtering depends largely on the threshold values, they have to be determined carefully. In the proposed algorithm, thresholds are determined adaptively to the strength of the blocking artifact and, as a result, to various encoding parameters such as QP, absolute difference between QPs, the coding type, and motion vectors. It is shown by experimental results that the proposed algorithm can achieve 0.2-0.4 dB gains for I- and P-frames, and 0.1-0.3 dB gains for the B-frame when bit streams are encoded using the TM5 rate control algorithm.

  3. Extended adaptive filtering for wide-angle SAR image formation

    NASA Astrophysics Data System (ADS)

    Wang, Yanwei; Roberts, William; Li, Jian

    2005-05-01

    For two-dimensional (2-D) spectral analysis, the adaptive filtering based technologies, such as CAPON and APES (Amplitude and Phase EStimation), are developed under the implicit assumption that the data sets are rectangular. However, in real SAR applications, especially for the wide-angle cases, the collected data sets are always non-rectangular. This raises the problem of how to extend the original adaptive filtering based algorithms for such kind of scenarios. In this paper, we propose an extended adaptive filtering (EAF) approach, which includes Extended APES (E-APES) and Extended CAPON (E-CAPON), for arbitrarily shaped 2-D data. The EAF algorithms adopt a missing-data approach where the unavailable data samples close to the collected data set are assumed missing. Using a group of filter-banks with varying sizes, these algorithms are non-iterative and do not require the estimation of the unavailable samples. The improved imaging results of the proposed algorithms are demonstrated by applying them to two different SAR data sets.

  4. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    PubMed

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-01-01

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches. PMID:27472336

  5. Dip-separated structural filtering using seislet transform and adaptive empirical mode decomposition based dip filter

    NASA Astrophysics Data System (ADS)

    Chen, Yangkang

    2016-07-01

    The seislet transform has been demonstrated to have a better compression performance for seismic data compared with other well-known sparsity promoting transforms, thus it can be used to remove random noise by simply applying a thresholding operator in the seislet domain. Since the seislet transform compresses the seismic data along the local structures, the seislet thresholding can be viewed as a simple structural filtering approach. Because of the dependence on a precise local slope estimation, the seislet transform usually suffers from low compression ratio and high reconstruction error for seismic profiles that have dip conflicts. In order to remove the limitation of seislet thresholding in dealing with conflicting-dip data, I propose a dip-separated filtering strategy. In this method, I first use an adaptive empirical mode decomposition based dip filter to separate the seismic data into several dip bands (5 or 6). Next, I apply seislet thresholding to each separated dip component to remove random noise. Then I combine all the denoised components to form the final denoised data. Compared with other dip filters, the empirical mode decomposition based dip filter is data-adaptive. One only needs to specify the number of dip components to be separated. Both complicated synthetic and field data examples show superior performance of my proposed approach than the traditional alternatives. The dip-separated structural filtering is not limited to seislet thresholding, and can also be extended to all those methods that require slope information.

  6. Dip-separated structural filtering using seislet transform and adaptive empirical mode decomposition based dip filter

    NASA Astrophysics Data System (ADS)

    Chen, Yangkang

    2016-04-01

    The seislet transform has been demonstrated to have a better compression performance for seismic data compared with other well-known sparsity promoting transforms, thus it can be used to remove random noise by simply applying a thresholding operator in the seislet domain. Since the seislet transform compresses the seismic data along the local structures, the seislet thresholding can be viewed as a simple structural filtering approach. Because of the dependence on a precise local slope estimation, the seislet transform usually suffers from low compression ratio and high reconstruction error for seismic profiles that have dip conflicts. In order to remove the limitation of seislet thresholding in dealing with conflicting-dip data, I propose a dip-separated filtering strategy. In this method, I first use an adaptive empirical mode decomposition based dip filter to separate the seismic data into several dip bands (5 or 6). Next, I apply seislet thresholding to each separated dip component to remove random noise. Then I combine all the denoised components to form the final denoised data. Compared with other dip filters, the empirical mode decomposition based dip filter is data-adaptive. One only need to specify the number of dip components to be separated. Both complicated synthetic and field data examples show superior performance of my proposed approach than the traditional alternatives. The dip-separated structural filtering is not limited to seislet thresholding, and can also be extended to all those methods that require slope information.

  7. Design of adaptive control systems by means of self-adjusting transversal filters

    NASA Technical Reports Server (NTRS)

    Merhav, S. J.

    1986-01-01

    The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

  8. Fuel-flow filter for internal combustion engine, adaptable for use with a by-pass filter

    SciTech Connect

    Schmidt, R.

    1987-06-16

    This patent describes a filter apparatus for an internal combustion engine to replace a spin-on, full-flow oil filter threadably connected to an oil filter bushing. The engine has an oil system with an oil pump, an oil pan, and an oil cap at a low pressure side of the oil system. The apparatus comprises: a full-flow filter to be connected to the oil filter bushing to permit oil within the oil system to flow into the full-flow filter. The full-flow filter is of such density and filtering capacity that the oil flows from the oil pump through the full-flow filter with a minimum pressure drop; adapter means to permit use of the full-flow filter either with or without a by-pass filter. The adapter means is a nut located at the forward end of the full-flow filter opposite the oil filter bushing and extending outwardly. The nut defines an area that can be either left intact, permitting all of the oil flow outward from the full-flow filter after filtering, or punctured, permitting most of the oil to flow outward from the full-flow filter after filtering. A small portion of the oil to flows outward therefrom prior to filtering. The nut is within a specific range of depth and circumference so as to provide a means for controlling the size of the hole. The nut is inwardly threaded.

  9. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

    PubMed Central

    Carmena, Jose M.

    2016-01-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to

  10. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    PubMed

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  11. Adaptive gain and filtering circuit for a sound reproduction system

    NASA Technical Reports Server (NTRS)

    Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)

    1998-01-01

    Adaptive compressive gain and level dependent spectral shaping circuitry for a hearing aid include a microphone to produce an input signal and a plurality of channels connected to a common circuit output. Each channel has a preset frequency response. Each channel includes a filter with a preset frequency response to receive the input signal and to produce a filtered signal, a channel amplifier to amplify the filtered signal to produce a channel output signal, a threshold register to establish a channel threshold level, and a gain circuit. The gain circuit increases the gain of the channel amplifier when the channel output signal falls below the channel threshold level and decreases the gain of the channel amplifier when the channel output signal rises above the channel threshold level. A transducer produces sound in response to the signal passed by the common circuit output.

  12. Kalman filtering to suppress spurious signals in Adaptive Optics control

    SciTech Connect

    Poyneer, L; Veran, J P

    2010-03-29

    In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.

  13. Infinite impulse response modal filtering in visible adaptive optics

    NASA Astrophysics Data System (ADS)

    Agapito, G.; Arcidiacono, C.; Quirós-Pacheco, F.; Puglisi, A.; Esposito, S.

    2012-07-01

    Diffraction limited resolution adaptive optics (AO) correction in visible wavelengths requires a high performance control. In this paper we investigate infinite impulse response filters that optimize the wavefront correction: we tested these algorithms through full numerical simulations of a single-conjugate AO system comprising an adaptive secondary mirror with 1127 actuators and a pyramid wavefront sensor (WFS). The actual practicability of the algorithms depends on both robustness and knowledge of the real system: errors in the system model may even worsen the performance. In particular we checked the robustness of the algorithms in different conditions, proving that the proposed method can reject both disturbance and calibration errors.

  14. Model Adaptation for Prognostics in a Particle Filtering Framework

    NASA Technical Reports Server (NTRS)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  15. Image super-resolution via adaptive filtering and regularization

    NASA Astrophysics Data System (ADS)

    Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

    2014-11-01

    Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

  16. Assessment of Snared-Loop Technique When Standard Retrieval of Inferior Vena Cava Filters Fails

    SciTech Connect

    Doody, Orla Noe, Geertje; Given, Mark F.; Foley, Peter T.; Lyon, Stuart M.

    2009-01-15

    Purpose To identify the success and complications related to a variant technique used to retrieve inferior vena cava filters when simple snare approach has failed. Methods A retrospective review of all Cook Guenther Tulip filters and Cook Celect filters retrieved between July 2006 and February 2008 was performed. During this period, 130 filter retrievals were attempted. In 33 cases, the standard retrieval technique failed. Retrieval was subsequently attempted with our modified retrieval technique. Results The retrieval was successful in 23 cases (mean dwell time, 171.84 days; range, 5-505 days) and unsuccessful in 10 cases (mean dwell time, 162.2 days; range, 94-360 days). Our filter retrievability rates increased from 74.6% with the standard retrieval method to 92.3% when the snared-loop technique was used. Unsuccessful retrieval was due to significant endothelialization (n = 9) and caval penetration by the filter (n = 1). A single complication occurred in the group, in a patient developing pulmonary emboli after attempted retrieval. Conclusion The technique we describe increased the retrievability of the two filters studied. Hook endothelialization is the main factor resulting in failed retrieval and continues to be a limitation with these filters.

  17. Frequency-shift low-pass filtering and least mean square adaptive filtering for ultrasound imaging

    NASA Astrophysics Data System (ADS)

    Wang, Shanshan; Li, Chunyu; Ding, Mingyue; Yuchi, Ming

    2016-04-01

    Ultrasound image quality enhancement is a problem of considerable interest in medical imaging modality and an ongoing challenge to date. This paper investigates a method based on frequency-shift low-pass filtering (FSLF) and least mean square adaptive filtering (LMSAF) for ultrasound image quality enhancement. FSLF is used for processing the ultrasound signal in the frequency domain, while LMSAPF in the time domain. Firstly, FSLF shifts the center frequency of the focused signal to zero. Then the real and imaginary part of the complex data are filtered respectively by finite impulse response (FIR) low-pass filter. Thus the information around the center frequency are retained while the undesired ones, especially background noises are filtered. Secondly, LMSAF multiplies the signals with an automatically adjusted weight vector to further eliminate the noises and artifacts. Through the combination of the two filters, the ultrasound image is expected to have less noises and artifacts and higher resolution, and contrast. The proposed method was verified with the RF data of the CIRS phantom 055A captured by SonixTouch DAQ system. Experimental results show that the background noises and artifacts can be efficiently restrained, the wire object has a higher resolution and the contrast ratio (CR) can be enhanced for about 12dB to 15dB at different image depth comparing to delay-and-sum (DAS).

  18. Adaptive distributed Kalman filtering with wind estimation for astronomical adaptive optics.

    PubMed

    Massioni, Paolo; Gilles, Luc; Ellerbroek, Brent

    2015-12-01

    In the framework of adaptive optics (AO) for astronomy, it is a common assumption to consider the atmospheric turbulent layers as "frozen flows" sliding according to the wind velocity profile. For this reason, having knowledge of such a velocity profile is beneficial in terms of AO control system performance. In this paper we show that it is possible to exploit the phase estimate from a Kalman filter running on an AO system in order to estimate wind velocity. This allows the update of the Kalman filter itself with such knowledge, making it adaptive. We have implemented such an adaptive controller based on the distributed version of the Kalman filter, for a realistic simulation of a multi-conjugate AO system with laser guide stars on a 30 m telescope. Simulation results show that this approach is effective and promising and the additional computational cost with respect to the distributed filter is negligible. Comparisons with a previously published slope detection and ranging wind profiler are made and the impact of turbulence profile quantization is assessed. One of the main findings of the paper is that all flavors of the adaptive distributed Kalman filter are impacted more significantly by turbulence profile quantization than the static minimum mean square estimator which does not incorporate wind profile information. PMID:26831389

  19. Study of Interpolated Timing Recovery Phase-Locked Loop with Linearly Constrained Adaptive Prefilter for Higher-Density Optical Disc

    NASA Astrophysics Data System (ADS)

    Kajiwara, Yoshiyuki; Shiraishi, Junya; Kobayashi, Shoei; Yamagami, Tamotsu

    2009-03-01

    A digital phase-locked loop (PLL) with a linearly constrained adaptive filter (LCAF) has been studied for higher-linear-density optical discs. LCAF has been implemented before an interpolated timing recovery (ITR) PLL unit in order to improve the quality of phase error calculation by using an adaptively equalized partial response (PR) signal. Coefficient update of an asynchronous sampled adaptive FIR filter with a least-mean-square (LMS) algorithm has been constrained by a projection matrix in order to suppress the phase shift of the tap coefficients of the adaptive filter. We have developed projection matrices that are suitable for Blu-ray disc (BD) drive systems by numerical simulation. Results have shown the properties of the projection matrices. Then, we have designed the read channel system of the ITR PLL with an LCAF model on the FPGA board for experiments. Results have shown that the LCAF improves the tilt margins of 30 gigabytes (GB) recordable BD (BD-R) and 33 GB BD read-only memory (BD-ROM) with a sufficient LMS adaptation stability.

  20. A New Adaptive Framework for Collaborative Filtering Prediction.

    PubMed

    Almosallam, Ibrahim A; Shang, Yi

    2008-06-01

    Collaborative filtering is one of the most successful techniques for recommendation systems and has been used in many commercial services provided by major companies including Amazon, TiVo and Netflix. In this paper we focus on memory-based collaborative filtering (CF). Existing CF techniques work well on dense data but poorly on sparse data. To address this weakness, we propose to use z-scores instead of explicit ratings and introduce a mechanism that adaptively combines global statistics with item-based values based on data density level. We present a new adaptive framework that encapsulates various CF algorithms and the relationships among them. An adaptive CF predictor is developed that can self adapt from user-based to item-based to hybrid methods based on the amount of available ratings. Our experimental results show that the new predictor consistently obtained more accurate predictions than existing CF methods, with the most significant improvement on sparse data sets. When applied to the Netflix Challenge data set, our method performed better than existing CF and singular value decomposition (SVD) methods and achieved 4.67% improvement over Netflix's system. PMID:21572924

  1. Switched Band-Pass Filters for Adaptive Transceivers

    NASA Technical Reports Server (NTRS)

    Wang, Ray

    2007-01-01

    Switched band-pass filters are key components of proposed adaptive, software- defined radio transceivers that would be parts of envisioned digital-data-communication networks that would enable real-time acquisition and monitoring of data from geographically distributed sensors. Examples of sensors to be connected to such networks include security cameras, radio-frequency identification units, and geolocation units based on the Global Positioning System. Through suitable software configuration and without changing hardware, these transceivers could be made to operate according to any of a number of complex wireless-communication standards that could be characterized by diverse modulation schemes, bandwidths, and data-handling protocols. The adaptive transceivers would include field-programmable gate arrays (FPGAs) and digital signal-processing hardware. In the receiving path of a transceiver, the incoming signal would be amplified by a low-noise amplifier (LNA). The output spectrum of the LNA would be processed by a band-pass filter operating in the frequency range between 900 MHz and 2.4 GHz. Then a down-converter would translate the signal to a lower frequency range to facilitate analog-to-digital conversion, which would be followed by baseband processing by one or more FPGAs. In the transmitting path, a digital stream would first be converted to an analog signal, which would then be up-converted to a selected frequency band before being applied to a transmitting power amplifier. The aforementioned band-pass filter in the receiving path would be a combination of resonant inductor-and-capacitor filters and switched band-pass filters. The overall combination would implement a switch function designed mathematically to exhibit desired frequency responses and to switch the signal in each frequency band to an analog-to-digital converter appropriate for that band to produce a digital intermediate-frequency signal for digital signal processing.

  2. Tracking performance of unbalanced QPSK demodulators. II - Biphase Costas loop with active arm filters

    NASA Technical Reports Server (NTRS)

    Simon, M. K.

    1978-01-01

    In a Costas loop study for biphase modulation conducted by Simon and Lindsey (1977), it was demonstrated that considerable improvement in tracking performance could be obtained by employing active arm filters of the integrate-and-dump type as opposed to passive arm filters. An investigation is conducted concerning the possibility to obtain a similar performance improvement for an unbalanced quadriphase-shift-keying (QPSK) modulation. It is found that the biphase Costas loop can be used as an efficient demodulator of QPSK in cases in which the ratio of data rates is of the same order of magnitude as the inverse of the power ratio. These cases involve approximately equal signal energies in the two channels.

  3. Covariance matching based adaptive unscented Kalman filter for direct filtering in INS/GNSS integration

    NASA Astrophysics Data System (ADS)

    Meng, Yang; Gao, Shesheng; Zhong, Yongmin; Hu, Gaoge; Subic, Aleksandar

    2016-03-01

    The use of the direct filtering approach for INS/GNSS integrated navigation introduces nonlinearity into the system state equation. As the unscented Kalman filter (UKF) is a promising method for nonlinear problems, an obvious solution is to incorporate the UKF concept in the direct filtering approach to address the nonlinearity involved in INS/GNSS integrated navigation. However, the performance of the standard UKF is dependent on the accurate statistical characterizations of system noise. If the noise distributions of inertial instruments and GNSS receivers are not appropriately described, the standard UKF will produce deteriorated or even divergent navigation solutions. This paper presents an adaptive UKF with noise statistic estimator to overcome the limitation of the standard UKF. According to the covariance matching technique, the innovation and residual sequences are used to determine the covariance matrices of the process and measurement noises. The proposed algorithm can estimate and adjust the system noise statistics online, and thus enhance the adaptive capability of the standard UKF. Simulation and experimental results demonstrate that the performance of the proposed algorithm is significantly superior to that of the standard UKF and adaptive-robust UKF under the condition without accurate knowledge on system noise, leading to improved navigation precision.

  4. Statistical-uncertainty-based adaptive filtering of lidar signals

    SciTech Connect

    Fuehrer, P. L.; Friehe, C. A.; Hristov, T. S.; Cooper, D. I.; Eichinger, W. E.

    2000-02-10

    An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H{sub 2}O and the N{sub 2} photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America.

  5. Fast Source Camera Identification Using Content Adaptive Guided Image Filter.

    PubMed

    Zeng, Hui; Kang, Xiangui

    2016-03-01

    Source camera identification (SCI) is an important topic in image forensics. One of the most effective fingerprints for linking an image to its source camera is the sensor pattern noise, which is estimated as the difference between the content and its denoised version. It is widely believed that the performance of the sensor-based SCI heavily relies on the denoising filter used. This study proposes a novel sensor-based SCI method using content adaptive guided image filter (CAGIF). Thanks to the low complexity nature of the CAGIF, the proposed method is much faster than the state-of-the-art methods, which is a big advantage considering the potential real-time application of SCI. Despite the advantage of speed, experimental results also show that the proposed method can achieve comparable or better performance than the state-of-the-art methods in terms of accuracy. PMID:27404627

  6. An adaptive filter method for spacecraft using gravity assist

    NASA Astrophysics Data System (ADS)

    Ning, Xiaolin; Huang, Panpan; Fang, Jiancheng; Liu, Gang; Ge, Shuzhi Sam

    2015-04-01

    Celestial navigation (CeleNav) has been successfully used during gravity assist (GA) flyby for orbit determination in many deep space missions. Due to spacecraft attitude errors, ephemeris errors, the camera center-finding bias, and the frequency of the images before and after the GA flyby, the statistics of measurement noise cannot be accurately determined, and yet have time-varying characteristics, which may introduce large estimation error and even cause filter divergence. In this paper, an unscented Kalman filter (UKF) with adaptive measurement noise covariance, called ARUKF, is proposed to deal with this problem. ARUKF scales the measurement noise covariance according to the changes in innovation and residual sequences. Simulations demonstrate that ARUKF is robust to the inaccurate initial measurement noise covariance matrix and time-varying measurement noise. The impact factors in the ARUKF are also investigated.

  7. Adaptive feed-forward loop connection based on error signal

    NASA Astrophysics Data System (ADS)

    Hidaka, Koichi

    2005-12-01

    In this paper, we investigate effect of changing the connection of feed-forward loop based on error signal. Our motivation of this work is solution to progress of human skill. For the skill model, we study a human simple action such as arm motion. Many models that describe the human arm dynamics have been proposed in recent year. While one type does not need an inverse model of human dynamics, the system based on the model does not include feed-forward loop. On the other hand, another type model has a feed-forward loop and feedback loop systems. This type assumes feed-forward element includes an internal model by repeating action or training and this loop progress our skill. Then we usually have to exercise to get a good performance. This says that we design the internal motion model by training and we move on prediction for motion. Under the assumption, Kawato model is well known. The model proposed that learning of feed-forward element is promoted in brain so that the error of feedback loop decreases. Furthermore, we assume the connections in feedback loop and feed-forward loop are changed. We show numerical simulations and consider that the position error given by our vision changes the skill element and we confirm that the position error is the one of the estimate function for the improvement in our skill.

  8. Study of adaptive correlation filter synthesis guided by the peak and shape of the correlation output

    NASA Astrophysics Data System (ADS)

    Campos Trujillo, Oliver G.; Díaz Blancas, Gerardo

    2014-09-01

    In recent years, many proposals that consider an adaptive perspective had been developed to solve some drawbacks, such as geometric distortions, background noise and target discrimination. The metrics are based only in the correlation peak output for the filter synthesis. In this paper, the correlation shape is studied to implement adaptive correlation filters guided by the peak and shape of the correlation output. Furthermore, the shape of correlation output is studied to improve the search in the filters bank. In addition, parallel algorithms are developed for accelerated the search in the filters bank. Some results are shown, such as time of synthesis, filter performance and comparisons with other adaptive correlation filter proposals.

  9. Residual mode filters and adaptive control in large space structures

    NASA Technical Reports Server (NTRS)

    Davidson, Roger A.; Balas, Mark J.

    1989-01-01

    One of the most difficult problems in controlling large systems and structures is compensating for the destructive interaction which can occur between the reduced-order model (ROM) of the plant, which is used by the controller, and the unmodeled dynamics of the plant, often called the residual modes. The problem is more significant in the case of large space structures because their naturally light damping and high performance requirements lead to more frequent, destructive residual mode interaction (RMI). Using the design/compensation technique of residual mode filters (RMF's), effective compensation of RMI can be accomplished in a straightforward manner when using linear controllers. The use of RMF's has been shown to be effective for a variety of large structures, including a space-based laser and infinite dimensional systems. However, the dynamics of space structures is often uncertain and may even change over time due to on-orbit erosion from space debris and corrosive chemicals in the upper atmosphere. In this case, adaptive control can be extremely beneficial in meeting the performance requirements of the structure. Adaptive control for large structures is also based on ROM's and so destructive RMI may occur. Unfortunately, adaptive control is inherently nonlinear, and therefore the known results of RMF's cannot be applied. The purpose is to present the results of new research showing the effects of RMI when using adaptive control and the work which will hopefully lead to RMF compensation of this problem.

  10. Multimodal Medical Image Fusion by Adaptive Manifold Filter.

    PubMed

    Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna

    2015-01-01

    Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images. PMID:26664494

  11. On application of adaptive decorrelation filtering to assistive listening

    NASA Astrophysics Data System (ADS)

    Zhao, Yunxin; Yen, Kuan-Chieh; Soli, Sig; Gao, Shawn; Vermiglio, Andy

    2002-02-01

    This paper describes an application of the multichannel signal processing technique of adaptive decorrelation filtering to the design of an assistive listening system. A simulated ``dinner table'' scenario was studied. The speech signal of a desired talker was corrupted by three simultaneous speech jammers and by a speech-shaped diffusive noise. The technique of adaptive decorrelation filtering processing was used to extract the desired speech from the interference speech and noise. The effectiveness of the assistive listening system was evaluated by observing improvements in A-weighted signal-to-noise ratio (SNR) and in sentence intelligibility, where the latter was evaluated in a listening test with eight normal hearing subjects and three subjects with hearing impairments. Significant improvements in SNR and sentence intelligibility were achieved with the use of the assistive listening system. For subjects with normal hearing, the speech reception threshold was improved by 3 to 5 dBA, and for subjects with hearing impairments, the threshold was improved by 4 to 8 dBA.

  12. A wavelet packet adaptive filtering algorithm for enhancing manatee vocalizations.

    PubMed

    Gur, M Berke; Niezrecki, Christopher

    2011-04-01

    Approximately a quarter of all West Indian manatee (Trichechus manatus latirostris) mortalities are attributed to collisions with watercraft. A boater warning system based on the passive acoustic detection of manatee vocalizations is one possible solution to reduce manatee-watercraft collisions. The success of such a warning system depends on effective enhancement of the vocalization signals in the presence of high levels of background noise, in particular, noise emitted from watercraft. Recent research has indicated that wavelet domain pre-processing of the noisy vocalizations is capable of significantly improving the detection ranges of passive acoustic vocalization detectors. In this paper, an adaptive denoising procedure, implemented on the wavelet packet transform coefficients obtained from the noisy vocalization signals, is investigated. The proposed denoising algorithm is shown to improve the manatee detection ranges by a factor ranging from two (minimum) to sixteen (maximum) compared to high-pass filtering alone, when evaluated using real manatee vocalization and background noise signals of varying signal-to-noise ratios (SNR). Furthermore, the proposed method is also shown to outperform a previously suggested feedback adaptive line enhancer (FALE) filter on average 3.4 dB in terms of noise suppression and 0.6 dB in terms of waveform preservation. PMID:21476661

  13. An adaptive filtered back-projection for photoacoustic image reconstruction

    PubMed Central

    Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong

    2015-01-01

    Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing

  14. An adaptive filtered back-projection for photoacoustic image reconstruction

    SciTech Connect

    Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong

    2015-05-15

    Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing

  15. Automatic balancing of AMB systems using plural notch filter and adaptive synchronous compensation

    NASA Astrophysics Data System (ADS)

    Xu, Xiangbo; Chen, Shao; Zhang, Yanan

    2016-07-01

    To achieve automatic balancing in active magnetic bearing (AMB) system, a control method with notch filters and synchronous compensators is widely employed. However, the control precision is significantly affected by the synchronous compensation error, which is caused by parameter errors and variations of the power amplifiers. Furthermore, the computation effort may become intolerable if a 4-degree-of-freedom (dof) AMB system is studied. To solve these problems, an adaptive automatic balancing control method in the AMB system is presented in this study. Firstly, a 4-dof radial AMB system is described and analyzed. To simplify the controller design, the 4-dof dynamic equations are transferred into two plural functions related to translation and rotation, respectively. Next, to achieve automatic balancing of the AMB system, two synchronous equations are formed. Solution of them leads to a control strategy based on notch filters and feedforward controllers with an inverse function of the power amplifier. The feedforward controllers can be simplified as synchronous phases and amplitudes. Then, a plural phase-shift notch filter which can identify the synchronous components in 2-dof motions is formulated, and an adaptive compensation method that can form two closed-loop systems to tune the synchronous amplitude of the feedforward controller and the phase of the plural notch filter is proposed. Finally, the proposed control strategy is verified by both simulations and experiments on a test rig of magnetically suspended control moment gyro. The results indicate that this method can fulfill the automatic balancing of the AMB system with a light computational load.

  16. Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2. Parts 1 and 2

    NASA Technical Reports Server (NTRS)

    Balas, Mark J.; Frost, Susan

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. This paper will be divided into two parts. Here in Part I we will review the basic adaptive control approach and introduce the primary ideas. In Part II, we will present the RMF methodology and complete the proofs of all our results. Also, we will apply the above theoretical results to a simple flexible structure example to illustrate the behavior with and without the residual mode filter.

  17. Autonomous robotic capture of non-cooperative target by adaptive extended Kalman filter based visual servo

    NASA Astrophysics Data System (ADS)

    Dong, Gangqi; Zhu, Zheng H.

    2016-05-01

    This paper presents a real-time, vision-based algorithm for the pose and motion estimation of non-cooperative targets and its application in visual servo robotic manipulator to perform autonomous capture. A hybrid approach of adaptive extended Kalman filter and photogrammetry is developed for the real-time pose and motion estimation of non-cooperative targets. Based on the pose and motion estimates, the desired pose and trajectory of end-effector is defined and the corresponding desired joint angles of the robotic manipulator are derived by inverse kinematics. A close-loop visual servo control scheme is then developed for the robotic manipulator to track, approach and capture the target. Validating experiments are designed and performed on a custom-built six degrees of freedom robotic manipulator with an eye-in-hand configuration. The experimental results demonstrate the feasibility, effectiveness and robustness of the proposed adaptive extended Kalman filter enabled pose and motion estimation and visual servo strategy.

  18. A general transfer-function approach to noise filtering in open-loop quantum control

    NASA Astrophysics Data System (ADS)

    Viola, Lorenza

    2015-03-01

    Hamiltonian engineering via unitary open-loop quantum control provides a versatile and experimentally validated framework for manipulating a broad class of non-Markovian open quantum systems of interest, with applications ranging from dynamical decoupling and dynamically corrected quantum gates, to noise spectroscopy and quantum simulation. In this context, transfer-function techniques directly motivated by control engineering have proved invaluable for obtaining a transparent picture of the controlled dynamics in the frequency domain and for quantitatively analyzing performance. In this talk, I will show how to identify a computationally tractable set of ``fundamental filter functions,'' out of which arbitrary filter functions may be assembled up to arbitrary high order in principle. Besides avoiding the infinite recursive hierarchy of filter functions that arises in general control scenarios, this fundamental set suffices to characterize the error suppression capabilities of the control protocol in both the time and frequency domain. I will show, in particular, how the resulting notion of ``filtering order'' reveals conceptually distinct, albeit complementary, features of the controlled dynamics as compared to the ``cancellation order,'' traditionally defined in the Magnus sense. Implications for current quantum control experiments will be discussed. Work supported by the U.S. Army Research Office under Contract No. W911NF-14-1-0682.

  19. Reduced-Rank Adaptive Filtering Using Krylov Subspace

    NASA Astrophysics Data System (ADS)

    Burykh, Sergueï; Abed-Meraim, Karim

    2003-12-01

    A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.

  20. Adaptive Data Filtering of Inertial Sensors with Variable Bandwidth

    PubMed Central

    Alam, Mushfiqul; Rohac, Jan

    2015-01-01

    MEMS (micro-electro-mechanical system)-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU), which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor's behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer's data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing. PMID:25648711

  1. Adaptive data filtering of inertial sensors with variable bandwidth.

    PubMed

    Alam, Mushfiqul; Rohac, Jan

    2015-01-01

    MEMS (micro-electro-mechanical system)-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU), which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor's behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer's data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing. PMID:25648711

  2. Adaptive noise cancellation based on beehive pattern evolutionary digital filter

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaojun; Shao, Yimin

    2014-01-01

    Evolutionary digital filtering (EDF) exhibits the advantage of avoiding the local optimum problem by using cloning and mating searching rules in an adaptive noise cancellation system. However, convergence performance is restricted by the large population of individuals and the low level of information communication among them. The special beehive structure enables the individuals on neighbour beehive nodes to communicate with each other and thus enhance the information spread and random search ability of the algorithm. By introducing the beehive pattern evolutionary rules into the original EDF, this paper proposes an improved beehive pattern evolutionary digital filter (BP-EDF) to overcome the defects of the original EDF. In the proposed algorithm, a new evolutionary rule which combines competing cloning, complete cloning and assistance mating methods is constructed to enable the individuals distributed on the beehive to communicate with their neighbours. Simulation results are used to demonstrate the improved performance of the proposed algorithm in terms of convergence speed to the global optimum compared with the original methods. Experimental results also verify the effectiveness of the proposed algorithm in extracting feature signals that are contaminated by significant amounts of noise during the fault diagnosis task.

  3. Closed-loop adaptive optics using a spatial light modulator for sensing and compensating of optical aberrations in ophthalmic applications

    NASA Astrophysics Data System (ADS)

    Akondi, Vyas; Jewel, Md. Atikur Rahman; Vohnsen, Brian

    2014-09-01

    Sensing and compensating of optical aberrations in closed-loop mode using a single spatial light modulator (SLM) for ophthalmic applications is demonstrated. Notwithstanding the disadvantages of the SLM, in certain cases, this multitasking capability of the device makes it advantageous over existing deformable mirrors (DMs), which are expensive and in general used for aberration compensation alone. A closed-loop adaptive optics (AO) system based on a single SLM was built. Beam resizing optics were used to utilize the large active area of the device and hence make it feasible to generate 137 active subapertures for wavefront sensing. While correcting Zernike aberrations up to fourth order introduced with the help of a DM (for testing purposes), diffraction-limited resolution was achieved. It is shown that matched filter and intensity-weighted centroiding techniques stand out among others. Closed-loop wavefront correction of aberrations in backscattered light from the eyes of three healthy human subjects was demonstrated after satisfactory results were obtained using an artificial eye, which was simulated with a short focal length lens and a sheet of white paper as diffuser. It is shown that the closed-loop AO system based on a single SLM is capable of diffraction-limited correction for ophthalmic applications.

  4. Exploring Adaptability through Learning Layers and Learning Loops

    ERIC Educational Resources Information Center

    Lof, Annette

    2010-01-01

    Adaptability in social-ecological systems results from individual and collective action, and multi-level interactions. It can be understood in a dual sense as a system's ability to adapt to disturbance and change, and to navigate system transformation. Inherent in this conception, as found in resilience thinking, are the concepts of learning and…

  5. Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter.

    PubMed

    Zhang, Zhen; Ma, Yaopeng

    2016-01-01

    A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively. PMID:26861349

  6. Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter

    PubMed Central

    Zhang, Zhen; Ma, Yaopeng

    2016-01-01

    A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively. PMID:26861349

  7. Subsurface characterization with localized ensemble Kalman filter employing adaptive thresholding

    NASA Astrophysics Data System (ADS)

    Delijani, Ebrahim Biniaz; Pishvaie, Mahmoud Reza; Boozarjomehry, Ramin Bozorgmehry

    2014-07-01

    Ensemble Kalman filter, EnKF, as a Monte Carlo sequential data assimilation method has emerged promisingly for subsurface media characterization during past decade. Due to high computational cost of large ensemble size, EnKF is limited to small ensemble set in practice. This results in appearance of spurious correlation in covariance structure leading to incorrect or probable divergence of updated realizations. In this paper, a universal/adaptive thresholding method is presented to remove and/or mitigate spurious correlation problem in the forecast covariance matrix. This method is, then, extended to regularize Kalman gain directly. Four different thresholding functions have been considered to threshold forecast covariance and gain matrices. These include hard, soft, lasso and Smoothly Clipped Absolute Deviation (SCAD) functions. Three benchmarks are used to evaluate the performances of these methods. These benchmarks include a small 1D linear model and two 2D water flooding (in petroleum reservoirs) cases whose levels of heterogeneity/nonlinearity are different. It should be noted that beside the adaptive thresholding, the standard distance dependant localization and bootstrap Kalman gain are also implemented for comparison purposes. We assessed each setup with different ensemble sets to investigate the sensitivity of each method on ensemble size. The results indicate that thresholding of forecast covariance yields more reliable performance than Kalman gain. Among thresholding function, SCAD is more robust for both covariance and gain estimation. Our analyses emphasize that not all assimilation cycles do require thresholding and it should be performed wisely during the early assimilation cycles. The proposed scheme of adaptive thresholding outperforms other methods for subsurface characterization of underlying benchmarks.

  8. Adaptive Wiener filter super-resolution of color filter array images.

    PubMed

    Karch, Barry K; Hardie, Russell C

    2013-08-12

    Digital color cameras using a single detector array with a Bayer color filter array (CFA) require interpolation or demosaicing to estimate missing color information and provide full-color images. However, demosaicing does not specifically address fundamental undersampling and aliasing inherent in typical camera designs. Fast non-uniform interpolation based super-resolution (SR) is an attractive approach to reduce or eliminate aliasing and its relatively low computational load is amenable to real-time applications. The adaptive Wiener filter (AWF) SR algorithm was initially developed for grayscale imaging and has not previously been applied to color SR demosaicing. Here, we develop a novel fast SR method for CFA cameras that is based on the AWF SR algorithm and uses global channel-to-channel statistical models. We apply this new method as a stand-alone algorithm and also as an initialization image for a variational SR algorithm. This paper presents the theoretical development of the color AWF SR approach and applies it in performance comparisons to other SR techniques for both simulated and real data. PMID:23938797

  9. First laboratory demonstration of closed-loop Kalman based optimal control for vibration filtering and simplified MCAO

    NASA Astrophysics Data System (ADS)

    Petit, C.; Conan, J.-M.; Kulcsár, C.; Raynaud, H.-F.; Fusco, T.; Montri, J.; Rabaud, D.

    2006-06-01

    Classic Adaptive Optics (AO) is now successfully implemented on a growing number of ground-based imaging systems. Nevertheless some limitations are still to cope with. First, the AO standard control laws are unable to easily handle vibrations. In the particular case of eXtreme AO (XAO), which requires a highly efficient AO, these vibrations can thus be much penalizing. We have previously shown that a Kalman based control law can provide both an efficient correction of the turbulence and a strong vibration filtering. Second, anisoplanatism effects lead to a small corrected field of view. Multi-Conjugate AO (MCAO) is a promising concept that should increase significantly this field of view. We have shown numerically that MCAO correction can be highly improved by optimal control based on a Kalman filter. This article presents the first laboratory demonstration of these two concepts. We use a classic AO bench available at Onera with a deformable mirror (DM) in the pupil and a Shack-Hartmann Wave Front Sensor (WFS) pointing at an on-axis guide-star. The turbulence is produced by a rotating phase screen in altitude. First, this AO configuration is used to validate the ability of our control approach to filter out system vibrations and improve the overall performance of the AO closed-loop, compared to classic controllers. The consequences on the RTC design of an XAO system is discussed. Then, we optimize the correction for an off-axis star although the WFS still points at the on-axis star. This Off-Axis AO (OAAO) can be seen as a first step towards MCAO or Multi-Object AO in a simplified configuration. It proves the ability of our control law to estimate the turbulence in altitude and correct in the direction of interest. We describe the off-axis correction tests performed in a dynamic mode (closed-loop) using our Kalman based control. We present the evolution of the off-axis correction according to the angular separation between the stars. A highly significant

  10. An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction

    NASA Astrophysics Data System (ADS)

    Zhang, Yan; Tang, Baoping; Liu, Ziran; Chen, Rengxiang

    2016-02-01

    Fault diagnosis of rolling element bearings is important for improving mechanical system reliability and performance. Vibration signals contain a wealth of complex information useful for state monitoring and fault diagnosis. However, any fault-related impulses in the original signal are often severely tainted by various noises and the interfering vibrations caused by other machine elements. Narrow-band amplitude demodulation has been an effective technique to detect bearing faults by identifying bearing fault characteristic frequencies. To achieve this, the key step is to remove the corrupting noise and interference, and to enhance the weak signatures of the bearing fault. In this paper, a new method based on adaptive wavelet filtering and spectral subtraction is proposed for fault diagnosis in bearings. First, to eliminate the frequency associated with interfering vibrations, the vibration signal is bandpass filtered with a Morlet wavelet filter whose parameters (i.e. center frequency and bandwidth) are selected in separate steps. An alternative and efficient method of determining the center frequency is proposed that utilizes the statistical information contained in the production functions (PFs). The bandwidth parameter is optimized using a local ‘greedy’ scheme along with Shannon wavelet entropy criterion. Then, to further reduce the residual in-band noise in the filtered signal, a spectral subtraction procedure is elaborated after wavelet filtering. Instead of resorting to a reference signal as in the majority of papers in the literature, the new method estimates the power spectral density of the in-band noise from the associated PF. The effectiveness of the proposed method is validated using simulated data, test rig data, and vibration data recorded from the transmission system of a helicopter. The experimental results and comparisons with other methods indicate that the proposed method is an effective approach to detecting the fault-related impulses

  11. Unscented fuzzy-controlled current statistic model and adaptive filtering for tracking maneuvering targets

    NASA Astrophysics Data System (ADS)

    Hu, Hongtao; Jing, Zhongliang; Hu, Shiqiang

    2006-12-01

    A novel adaptive algorithm for tracking maneuvering targets is proposed. The algorithm is implemented with fuzzy-controlled current statistic model adaptive filtering and unscented transformation. A fuzzy system allows the filter to tune the magnitude of maximum accelerations to adapt to different target maneuvers, and unscented transformation can effectively handle nonlinear system. A bearing-only tracking scenario simulation results show the proposed algorithm has a robust advantage over a wide range of maneuvers and overcomes the shortcoming of the traditional current statistic model and adaptive filtering algorithm.

  12. The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.

    PubMed

    Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

    2016-01-01

    This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'β' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively. PMID:27438835

  13. The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation

    PubMed Central

    Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

    2016-01-01

    This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix ‘R’ and the system noise V-C matrix ‘Q’. Then, the global filter uses R to calculate the information allocation factor ‘β’ for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively. PMID:27438835

  14. An Adaptive Fourier Filter for Relaxing Time Stepping Constraints for Explicit Solvers

    SciTech Connect

    Gelb, Anne; Archibald, Richard K

    2015-01-01

    Filtering is necessary to stabilize piecewise smooth solutions. The resulting diffusion stabilizes the method, but may fail to resolve the solution near discontinuities. Moreover, high order filtering still requires cost prohibitive time stepping. This paper introduces an adaptive filter that controls spurious modes of the solution, but is not unnecessarily diffusive. Consequently we are able to stabilize the solution with larger time steps, but also take advantage of the accuracy of a high order filter.

  15. An online novel adaptive filter for denoising time series measurements.

    PubMed

    Willis, Andrew J

    2006-04-01

    A nonstationary form of the Wiener filter based on a principal components analysis is described for filtering time series data possibly derived from noisy instrumentation. The theory of the filter is developed, implementation details are presented and two examples are given. The filter operates online, approximating the maximum a posteriori optimal Bayes reconstruction of a signal with arbitrarily distributed and non stationary statistics. PMID:16649562

  16. Application of multirate digital filter banks to wideband all-digital phase-locked loops design

    NASA Technical Reports Server (NTRS)

    Sadr, R.; Shah, B.; Hinedi, S.

    1992-01-01

    A new class of architecture for all-digital phase-locked loops (DPLL's) is presented in this article. These architectures, referred to as parallel DPLL (PDPLL), employ multirate digital filter banks (DFB's) to track signals with a lower processing rate than the Nyquist rate, without reducing the input (Nyquist) bandwidth. The PDPLL basically trades complexity for hardware-processing speed by introducing parallel processing in the receiver. It is demonstrated here that the DPLL performance is identical to that of a PDPLL for both steady-state and transient behavior. A test signal with a time-varying Doppler characteristic is used to compare the performance of both the DPLL and the PDPLL.

  17. Burst noise reduction of image by decimation and adaptive weighted median filter

    NASA Astrophysics Data System (ADS)

    Nakayama, Fumitaka; Meguro, Mitsuhiko; Hamada, Nozomu

    2000-12-01

    The removal of noise in image is one of the important issues, and useful as a preprocessing for edge detection, motion estimation and so on. Recently, many studies on the nonlinear digital filter for impulsive noise reduction have been reported. The median filter, the representative of the nonlinear filters, is very effective for removing impulsive noise and preserving sharp edge. In some cases, burst (i.e., successive) impulsive noise is added to image, and this type of noise is difficult to remove by using the median filter. In this paper, we propose an Adaptive Weighted Median (AWM) filter with Decimation (AWM-D filter) for burst noise reduction. This method can also be applied to recover large destructive regions, such as blotch and scratch. The proposed filter is an extension of the Decimated Median (DM) filter, which is useful for reducing successive impulsive noise. The DM filter can split long impulsive noise sequences into short ones, and remove burst noise in spite of the short filter window. Nevertheless, the DM filter also has two disadvantages. One is that the signals without added noise is unnecessary filtered. The other is that the position information in the window is not considered in the weight determinative process, as common in the median type filter. To improve detail-preserving property of the DM filter, we use the noise detection procedure and the AWM-D filter, which can be tuned by Least Mean Absolute (LMA) algorithm. The AWM-D filter preserves details more precisely than the median-type filter, because the AWM-D filter has the weights that can control the filter output. Through some simulations, the higher performance of the proposed filter is shown compared with the simple median, the WM filter, and the DM filter.

  18. Closed-loop adaptive optics using a CMOS image quality metric sensor

    NASA Astrophysics Data System (ADS)

    Ting, Chueh; Rayankula, Aditya; Giles, Michael K.; Furth, Paul M.

    2006-08-01

    When compared to a Shack-Hartmann sensor, a CMOS image sharpness sensor has the advantage of reduced complexity in a closed-loop adaptive optics system. It also has the potential to be implemented as a smart sensor using VLSI technology. In this paper, we present a novel adaptive optics testbed that uses a CMOS sharpness imager built in the New Mexico State University (NMSU) Electro-Optics Research Laboratory (EORL). The adaptive optics testbed, which includes a CMOS image quality metric sensor and a 37-channel deformable mirror, has the capability to rapidly compensate higher-order phase aberrations. An experimental performance comparison of the pinhole image sharpness feedback method and the CMOS imager is presented. The experimental data shows that the CMOS sharpness imager works well in a closed-loop adaptive optics system. Its overall performance is better than that of the pinhole method, and it has a fast response time.

  19. Adaptive RSOV filter using the FELMS algorithm for nonlinear active noise control systems

    NASA Astrophysics Data System (ADS)

    Zhao, Haiquan; Zeng, Xiangping; He, Zhengyou; Li, Tianrui

    2013-01-01

    This paper presents a recursive second-order Volterra (RSOV) filter to solve the problems of signal saturation and other nonlinear distortions that occur in nonlinear active noise control systems (NANC) used for actual applications. Since this nonlinear filter based on an infinite impulse response (IIR) filter structure can model higher than second-order and third-order nonlinearities for systems where the nonlinearities are harmonically related, the RSOV filter is more effective in NANC systems with either a linear secondary path (LSP) or a nonlinear secondary path (NSP). Simulation results clearly show that the RSOV adaptive filter using the multichannel structure filtered-error least mean square (FELMS) algorithm can further greatly reduce the computational burdens and is more suitable to eliminate nonlinear distortions in NANC systems than a SOV filter, a bilinear filter and a third-order Volterra (TOV) filter.

  20. Discrete cosine transform-based local adaptive filtering of images corrupted by nonstationary noise

    NASA Astrophysics Data System (ADS)

    Lukin, Vladimir V.; Fevralev, Dmitriy V.; Ponomarenko, Nikolay N.; Abramov, Sergey K.; Pogrebnyak, Oleksiy; Egiazarian, Karen O.; Astola, Jaakko T.

    2010-04-01

    In many image-processing applications, observed images are contaminated by a nonstationary noise and no a priori information on noise dependence on local mean or about local properties of noise statistics is available. In order to remove such a noise, a locally adaptive filter has to be applied. We study a locally adaptive filter based on evaluation of image local activity in a ``blind'' manner and on discrete cosine transform computed in overlapping blocks. Two mechanisms of local adaptation are proposed and applied. The first mechanism takes into account local estimates of noise standard deviation while the second one exploits discrimination of homogeneous and heterogeneous image regions by adaptive threshold setting. The designed filter performance is tested for simulated data as well as for real-life remote-sensing and maritime radar images. Recommendations concerning filter parameter setting are provided. An area of applicability of the proposed filter is defined.

  1. Geometric-Algebra LMS Adaptive Filter and Its Application to Rotation Estimation

    NASA Astrophysics Data System (ADS)

    Lopes, Wilder B.; Al-Nuaimi, Anas; Lopes, Cassio G.

    2016-06-01

    This paper exploits Geometric (Clifford) Algebra (GA) theory in order to devise and introduce a new adaptive filtering strategy. From a least-squares cost function, the gradient is calculated following results from Geometric Calculus (GC), the extension of GA to handle differential and integral calculus. The novel GA least-mean-squares (GA-LMS) adaptive filter, which inherits properties from standard adaptive filters and from GA, is developed to recursively estimate a rotor (multivector), a hypercomplex quantity able to describe rotations in any dimension. The adaptive filter (AF) performance is assessed via a 3D point-clouds registration problem, which contains a rotation estimation step. Calculating the AF computational complexity suggests that it can contribute to reduce the cost of a full-blown 3D registration algorithm, especially when the number of points to be processed grows. Moreover, the employed GA/GC framework allows for easily applying the resulting filter to estimating rotors in higher dimensions.

  2. Adaptation of a Filter Assembly to Assess Microbial Bioburden of Pressurant Within a Propulsion System

    NASA Technical Reports Server (NTRS)

    Benardini, James N.; Koukol, Robert C.; Schubert, Wayne W.; Morales, Fabian; Klatte, Marlin F.

    2012-01-01

    A report describes an adaptation of a filter assembly to enable it to be used to filter out microorganisms from a propulsion system. The filter assembly has previously been used for particulates greater than 2 micrometers. Projects that utilize large volumes of nonmetallic materials of planetary protection concern pose a challenge to their bioburden budget, as a conservative specification value of 30 spores per cubic centimeter is typically used. Helium was collected utilizing an adapted filtration approach employing an existing Millipore filter assembly apparatus used by the propulsion team for particulate analysis. The filter holder on the assembly has a 47-mm diameter, and typically a 1.2-5 micrometer pore-size filter is used for particulate analysis making it compatible with commercially available sterilization filters (0.22 micrometers) that are necessary for biological sampling. This adaptation to an existing technology provides a proof-of-concept and a demonstration of successful use in a ground equipment system. This adaptation has demonstrated that the Millipore filter assembly can be utilized to filter out microorganisms from a propulsion system, whereas in previous uses the filter assembly was utilized for particulates greater than 2 micrometers.

  3. Adaptive mean filtering for noise reduction in CT polymer gel dosimetry

    SciTech Connect

    Hilts, Michelle; Jirasek, Andrew

    2008-01-15

    X-ray computed tomography (CT) as a method of extracting 3D dose information from irradiated polymer gel dosimeters is showing potential as a practical means to implement gel dosimetry in a radiation therapy clinic. However, the response of CT contrast to dose is weak and noise reduction is critical in order to achieve adequate dose resolutions with this method. Phantom design and CT imaging technique have both been shown to decrease image noise. In addition, image postprocessing using noise reduction filtering techniques have been proposed. This work evaluates in detail the use of the adaptive mean filter for reducing noise in CT gel dosimetry. Filter performance is systematically tested using both synthetic patterns mimicking a range of clinical dose distribution features as well as actual clinical dose distributions. Both low and high signal-to-noise ratio (SNR) situations are examined. For all cases, the effects of filter kernel size and the number of iterations are investigated. Results indicate that adaptive mean filtering is a highly effective tool for noise reduction CT gel dosimetry. The optimum filtering strategy depends on characteristics of the dose distributions and image noise level. For low noise images (SNR {approx}20), the filtered results are excellent and use of adaptive mean filtering is recommended as a standard processing tool. For high noise images (SNR {approx}5) adaptive mean filtering can also produce excellent results, but filtering must be approached with more caution as spatial and dose distortions of the original dose distribution can occur.

  4. Closed-loop adaptive control for torsional micromirrors

    NASA Astrophysics Data System (ADS)

    Liao, Ke-Min; Wang, Yi-Chih; Yeh, Chih-Hsien; Chen, Rongshun

    2004-01-01

    An adaptive control scheme to achieve accurate positioning and trajectory tracking of torsional micromirror is presented in this study. The torsional micromirror is fabricated by using surface micromachining processes, in which phosphorusdoped polysilicon is employed as the structure layer as well as the bottom electrode. Generally, every fabrication step contributes to imperfections in micromirror. The proposed adaptive self-tuning controller has advantages of on-line compensating parameter variations or model uncertainty of the torsional micromirror, resulting from fabrication imperfections that produce asymmetric structures, misalignment of actuation mechanism, and deviations of the center of mass from the geometric center. In our design, the amount of detection of differential capacitance between the left and right electrodes at the femtofarad (fF) level is utilized as feedback signals. Simulation results show that the designed controller has better transient response compared to the PID control scheme. The micromirror can follow the reference trajectory (5 kHz) with acceptable error in several microseconds, thus the convergence of the controller is confirmed. Furthermore, the unknown model parameters can be identified correctly while the so-called persistent excitation condition is satisfied.

  5. Analysis of dynamic deformation processes with adaptive KALMAN-filtering

    NASA Astrophysics Data System (ADS)

    Eichhorn, Andreas

    2007-05-01

    In this paper the approach of a full system analysis is shown quantifying a dynamic structural ("white-box"-) model for the calculation of thermal deformations of bar-shaped machine elements. The task was motivated from mechanical engineering searching new methods for the precise prediction and computational compensation of thermal influences in the heating and cooling phases of machine tools (i.e. robot arms, etc.). The quantification of thermal deformations under variable dynamic loads requires the modelling of the non-stationary spatial temperature distribution inside the object. Based upon FOURIERS law of heat flow the high-grade non-linear temperature gradient is represented by a system of partial differential equations within the framework of a dynamic Finite Element topology. It is shown that adaptive KALMAN-filtering is suitable to quantify relevant disturbance influences and to identify thermal parameters (i.e. thermal diffusivity) with a deviation of only 0,2%. As result an identified (and verified) parametric model for the realistic prediction respectively simulation of dynamic temperature processes is presented. Classifying the thermal bend as the main deformation quantity of bar-shaped machine tools, the temperature model is extended to a temperature deformation model. In lab tests thermal load steps are applied to an aluminum column. Independent control measurements show that the identified model can be used to predict the columns bend with a mean deviation (r.m.s.) smaller than 10 mgon. These results show that the deformation model is a precise predictor and suitable for realistic simulations of thermal deformations. Experiments with modified heat sources will be necessary to verify the model in further frequency spectra of dynamic thermal loads.

  6. Open-loop frequency acquisition for suppressed-carrier biphase signals using one-pole arm filters

    NASA Technical Reports Server (NTRS)

    Shah, B.; Holmes, J. K.

    1991-01-01

    Open loop frequency acquisition performance is discussed for suppressed carrier binary phase shift keyed signals in terms of the probability of detecting the carrier frequency offset when the arms of the Costas loop detector have one pole filters. The approach, which does not require symbol timing, uses fast Fourier transforms (FFTs) to detect the carrier frequency offset. The detection probability, which depends on both the 3 dB arm filter bandwidth and the received symbol signal to noise ratio, is derived and is shown to be independent of symbol timing. It is shown that the performance of this technique is slightly better that other open loop acquisition techniques which use integrators in the arms and whose detection performance varies with symbol timing.

  7. An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors

    PubMed Central

    2014-01-01

    Background Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. Methods We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Results Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min −1 (0.3 min −1) and -0.7 bpm (1.7 bpm) (compared to -0.2 min −1 (0.4 min −1) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average

  8. An adaptive human response mechanism controlling the V/STOL aircraft. Appendix 3: The adaptive control model of a pilot in V/STOL aircraft control loops. M.S. Thesis. Final Report

    NASA Technical Reports Server (NTRS)

    Kucuk, Senol

    1988-01-01

    Importance of the role of human operator in control systems has led to the particular area of manual control theory. Human describing functions were developed to model human behavior for manual control studies to take advantage of the successful and safe human operations. A single variable approach is presented that can be extended for multi-variable tasks where a low order human response model is used together with its rules, to adapt the model on-line, being capable of responding to the changes in the controlled element dynamics. Basic control theory concepts are used to combine the model, constrained with the physical observations, particularly, for the case of aircraft control. Pilot experience is represented as the initial model parameters. An adaptive root-locus method is presented as the adaptation law of the model where the closed loop bandwidth of the system is to be preserved in a stable manner with the adjustments of the pilot handling qualities which relate the latter to the closed loop bandwidth and damping of the closed loop pilot aircraft combination. A Kalman filter parameter estimator is presented as the controlled element identifier of the adaptive model where any discrepancies of the open loop dynamics from the presented one, are sensed to be compensated.

  9. A self-adaptive genetic algorithm to estimate JA model parameters considering minor loops

    NASA Astrophysics Data System (ADS)

    Lu, Hai-liang; Wen, Xi-shan; Lan, Lei; An, Yun-zhu; Li, Xiao-ping

    2015-01-01

    A self-adaptive genetic algorithm for estimating Jiles-Atherton (JA) magnetic hysteresis model parameters is presented. The fitness function is established based on the distances between equidistant key points of normalized hysteresis loops. Linearity function and logarithm function are both adopted to code the five parameters of JA model. Roulette wheel selection is used and the selection pressure is adjusted adaptively by deducting a proportional which depends on current generation common value. The Crossover operator is established by combining arithmetic crossover and multipoint crossover. Nonuniform mutation is improved by adjusting the mutation ratio adaptively. The algorithm is used to estimate the parameters of one kind of silicon-steel sheet's hysteresis loops, and the results are in good agreement with published data.

  10. An Efficient Adaptive Weighted Switching Median Filter for Removing High Density Impulse Noise

    NASA Astrophysics Data System (ADS)

    Nair, Madhu S.; Ameera Mol, P. M.

    2014-09-01

    Restoration of images corrupted by impulse noise is a very active research area in image processing. In this paper, an Efficient Adaptive Weighted Switching Median filter for restoration of images that are corrupted by high density impulse noise is proposed. The filtering is performed as a two phase process—a detection phase followed by a filtering phase. In the proposed method, noise detection is done by HEIND algorithm proposed by Duan et al. The filtering algorithm is then applied to the pixels which are detected as noisy by the detection algorithm. All uncorrupted pixels in the image are left unchanged. The filtering window size is chosen adaptively depending on the local noise distribution around each corrupted pixels. Noisy pixels are replaced by a weighted median value of uncorrupted pixels in the filtering window. The weight value assigned to each uncorrupted pixels depends on its closeness to the central pixel.

  11. Adaptive multidirectional frequency domain filter for noise removal in wrapped phase patterns.

    PubMed

    Liu, Guixiong; Chen, Dongxue; Peng, Yanhua; Zeng, Qilin

    2016-08-01

    In order to avoid the detrimental effects of excessive noise in the phase fringe patterns of a laser digital interferometer over the accuracy of phase unwrapping and the successful detection of mechanical fatigue defects, an effective method of adaptive multidirectional frequency domain filtering is introduced based on the characteristics of the energy spectrum of localized wrapped phase patterns. Not only can this method automatically set the cutoff frequency, but it can also effectively filter out noise while preserving the image edge information. Compared with the sine and cosine transform filtering and the multidirectional frequency domain filtering, the experimental results demonstrate that the image filtered by our method has the fewest number of residues and is the closest to the noise-free image, compared to the two aforementioned methods, demonstrating the effectiveness of this adaptive multidirectional frequency domain filter. PMID:27505376

  12. Adaptive Filtering for Large Space Structures: A Closed-Form Solution

    NASA Technical Reports Server (NTRS)

    Rauch, H. E.; Schaechter, D. B.

    1985-01-01

    In a previous paper Schaechter proposes using an extended Kalman filter to estimate adaptively the (slowly varying) frequencies and damping ratios of a large space structure. The time varying gains for estimating the frequencies and damping ratios can be determined in closed form so it is not necessary to integrate the matrix Riccati equations. After certain approximations, the time varying adaptive gain can be written as the product of a constant matrix times a matrix derived from the components of the estimated state vector. This is an important savings of computer resources and allows the adaptive filter to be implemented with approximately the same effort as the nonadaptive filter. The success of this new approach for adaptive filtering was demonstrated using synthetic data from a two mode system.

  13. Impulse radar imaging for dispersive concrete using inverse adaptive filtering techniques

    SciTech Connect

    Arellano, J.; Hernandez, J.M.; Brase, J.

    1993-05-01

    This publication addresses applications of a delayed inverse model adaptive filter for modeled data obtained from short-pulse radar reflectometry. To determine the integrity of concrete, a digital adaptive filter was used, which allows compensation of dispersion and clutter generated by the concrete. A standard set of weights produced by an adaptive filter are used on modeled data to obtain the inverse-impulse response of the concrete. The data for this report include: Multiple target, nondispersive data; single-target, variable-size dispersive data; single-target, variable-depth dispersive data; and single-target, variable transmitted-pulse-width dispersive data. Results of this simulation indicate that data generated by the weights of the adaptive filter, coupled with a two-dimensional, synthetic-aperture focusing technique, successfully generate two-dimensional images of targets within the concrete from modeled data.

  14. Applying well flow adapted filtering to transient pumping tests

    NASA Astrophysics Data System (ADS)

    Zech, Alraune; Attinger, Sabine

    2014-05-01

    Transient pumping tests are often used to estimate porous medium characteristics like hydraulic conductivity and storativity. The interpretation of pumping test drawdowns is based on methods which are normally developed under the assumption of homogeneous porous media. However aquifer heterogeneity strongly impacts on well flow pattern, in particular in the vicinity of the pumping well. The purpose of this work is to present a method to interpret drawdowns of transient pumping tests in heterogeneous porous media. With this method we are able to describe the effects that statistical quantities like variance and correlation length have on pumping test drawdowns. Furthermore it allows inferring on the statistical parameters of aquifer heterogeneity from drawdown data by invers estimation, which is not possible using methods for homogeneous media like Theis' solution. The method is based on a representative description of hydraulic conductivity for radial flow regimes. It is derived from a well flow adapted filtering procedure (Coarse Graining), where the heterogeneity of hydraulic conductivity is assumed to be log-normal distributed with a Gaussian correlation structure. applying the up scaled hydraulic conductivity to the groundwater flow equation results in a hydraulic head which depends on the statistical parameters of the porous medium. It describes the drawdown of a transient pumping test in heterogeneous media. We used an ensemble of transient pumping test simulations to verify the up scaled drawdown solution. We generated transient pumping tests in heterogeneous media for various values of the statistical parameters variance and correlation length and evaluated their impact on the drawdown behavior as well as on the temporal evolution. We further examined the impact of several aspects like the location of an observation well or the local conductivity at the pumping well on the drawdown behavior. This work can be understood as an expansion of the work of Zech et

  15. Microwave Photonic Filters for Interference Cancellation and Adaptive Beamforming

    NASA Astrophysics Data System (ADS)

    Chang, John

    Wireless communication has experienced an explosion of growth, especially in the past half- decade, due to the ubiquity of wireless devices, such as tablets, WiFi-enabled devices, and especially smartphones. Proliferation of smartphones with powerful processors and graphic chips have given an increasing amount of people the ability to access anything from anywhere. Unfortunately, this ease of access has greatly increased mobile wireless bandwidth and have begun to stress carrier networks and spectra. Wireless interference cancellation will play a big role alongside the popularity of wire- less communication. In this thesis, we will investigate optical signal processing methods for wireless interference cancellation methods. Optics provide the perfect backdrop for interference cancellation. Mobile wireless data is already aggregated and transported through fiber backhaul networks in practice. By sandwiching the signal processing stage between the receiver and the fiber backhaul, processing can easily be done locally in one location. Further, optics offers the advantages of being instantaneously broadband and size, weight, and power (SWAP). We are primarily concerned with two methods for interference cancellation, based on microwave photonic filters, in this thesis. The first application is for a co-channel situation, in which a transmitter and receiver are co-located and transmitting at the same frequency. A novel analog optical technique extended for multipath interference cancellation of broadband signals is proposed and experimentally demonstrated in this thesis. The proposed architecture was able to achieve a maximum of 40 dB of cancellation over 200 MHz and 50 dB of cancellation over 10 MHz. The broadband nature of the cancellation, along with its depth, demonstrates both the precision of the optical components and the validity of the architecture. Next, we are interested in a scenario with dynamically changing interference, which requires an adaptive photonic

  16. Adaptive box filters for removal of random noise from digital images

    USGS Publications Warehouse

    Eliason, E.M.; McEwen, A.S.

    1990-01-01

    We have developed adaptive box-filtering algorithms to (1) remove random bit errors (pixel values with no relation to the image scene) and (2) smooth noisy data (pixels related to the image scene but with an additive or multiplicative component of noise). For both procedures, we use the standard deviation (??) of those pixels within a local box surrounding each pixel, hence they are adaptive filters. This technique effectively reduces speckle in radar images without eliminating fine details. -from Authors

  17. Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter

    NASA Astrophysics Data System (ADS)

    Rosa, Stefano; Paleari, Marco; Ariano, Paolo; Bona, Basilio

    2012-01-01

    Scenarios for a manned mission to the Moon or Mars call for astronaut teams to be accompanied by semiautonomous robots. A prerequisite for human-robot interaction is the capability of successfully tracking humans and objects in the environment. In this paper we present a system for real-time visual object tracking in 2D images for mobile robotic systems. The proposed algorithm is able to specialize to individual objects and to adapt to substantial changes in illumination and object appearance during tracking. The algorithm is composed by two main blocks: a detector based on Histogram of Oriented Gradient (HOG) descriptors and linear Support Vector Machines (SVM), and a tracker which is implemented by an adaptive Rao-Blackwellised particle filter (RBPF). The SVM is re-trained online on new samples taken from previous predicted positions. We use the effective sample size to decide when the classifier needs to be re-trained. Position hypotheses for the tracked object are the result of a clustering procedure applied on the set of particles. The algorithm has been tested on challenging video sequences presenting strong changes in object appearance, illumination, and occlusion. Experimental tests show that the presented method is able to achieve near real-time performances with a precision of about 7 pixels on standard video sequences of dimensions 320 × 240.

  18. Improving the response of accelerometers for automotive applications by using LMS adaptive filters: Part II.

    PubMed

    Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg Y; Fernández, Eduardo

    2010-01-01

    In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate. PMID:22315579

  19. Adaptive Spatial Filtering with Principal Component Analysis for Biomedical Photoacoustic Imaging

    NASA Astrophysics Data System (ADS)

    Nagaoka, Ryo; Yamazaki, Rena; Saijo, Yoshifumi

    Photoacoustic (PA) signal is very sensitive to noise generated by peripheral equipment such as power supply, stepping motor or semiconductor laser. Band-pass filter is not effective because the frequency bandwidth of the PA signal also covers the noise frequency. The objective of the present study is to reduce the noise by using an adaptive spatial filter with principal component analysis (PCA).

  20. Adaptive high temperature superconducting filters for interference rejection

    SciTech Connect

    Raihn, K.F.; Fenzi, N.O.; Hey-Shipton, G.L.; Saito, E.R.; Loung, P.V.; Aidnik, D.L.

    1996-07-01

    An optically switched high temperature superconducting (HTS) band-reject filter bank is presented. Fast low loss switching of high quality (Q) factor HTS filter elements enables digital selection of arbitrary pass-bands and stop-bands. Patterned pieces of GaAs and silicon are used in the manufacture of the photosensitive switches. Fiber optic cabling is used to transfer the optical energy from an LED to the switch. The fiber optic cable minimizes the thermal loading of the filter package and de-couples the switch`s power source from the RF circuit. This paper will discuss the development of a computer-controlled HTS bank of optically switchable, narrow band, high Q bandstop filters which incorporates a cryocooler to maintain the 77 K operating temperature of the HTS microwave circuit.

  1. Adaptive iterated function systems filter for images highly corrupted with fixed - Value impulse noise

    NASA Astrophysics Data System (ADS)

    Shanmugavadivu, P.; Eliahim Jeevaraj, P. S.

    2014-06-01

    The Adaptive Iterated Functions Systems (AIFS) Filter presented in this paper has an outstanding potential to attenuate the fixed-value impulse noise in images. This filter has two distinct phases namely noise detection and noise correction which uses Measure of Statistics and Iterated Function Systems (IFS) respectively. The performance of AIFS filter is assessed by three metrics namely, Peak Signal-to-Noise Ratio (PSNR), Mean Structural Similarity Index Matrix (MSSIM) and Human Visual Perception (HVP). The quantitative measures PSNR and MSSIM endorse the merit of this filter in terms of degree of noise suppression and details/edge preservation respectively, in comparison with the high performing filters reported in the recent literature. The qualitative measure HVP confirms the noise suppression ability of the devised filter. This computationally simple noise filter broadly finds application wherein the images are highly degraded by fixed-value impulse noise.

  2. High-resolution retinal imaging through open-loop adaptive optics

    NASA Astrophysics Data System (ADS)

    Li, Chao; Xia, Mingliang; Li, Dayu; Mu, Quanquan; Xuan, Li

    2010-07-01

    Using the liquid crystal spatial light modulator (LC-SLM) as the wavefront corrector, an open-loop adaptive optics (AO) system for fundus imaging in vivo is constructed. Compared with the LC-SLM closed-loop AO system, the light energy efficiency is increased by a factor of 2, which is helpful for the safety of fundus illumination in vivo. In our experiment, the subjective accommodation method is used to precorrect the defocus aberration, and three subjects with different myopia 0, -3, and -5 D are tested. Although the residual wavefront error after correction cannot to detected, the fundus images adequately demonstrate that the imaging system reaches the resolution of a single photoreceptor cell through the open-loop correction. Without dilating and cyclopleging the eye, the continuous imaging for 8 s is recorded for one of the subjects.

  3. Adaptive filtering of radar images for autofocus applications

    NASA Technical Reports Server (NTRS)

    Stiles, J. A.; Frost, V. S.; Gardner, J. S.; Eland, D. R.; Shanmugam, K. S.; Holtzman, J. C.

    1981-01-01

    Autofocus techniques are being designed at the Jet Propulsion Laboratory to automatically choose the filter parameters (i.e., the focus) for the digital synthetic aperture radar correlator; currently, processing relies upon interaction with a human operator who uses his subjective assessment of the quality of the processed SAR data. Algorithms were devised applying image cross-correlation to aid in the choice of filter parameters, but this method also has its drawbacks in that the cross-correlation result may not be readily interpretable. Enhanced performance of the cross-correlation techniques of JPL was hypothesized given that the images to be cross-correlated were first filtered to improve the signal-to-noise ratio for the pair of scenes. The results of experiments are described and images are shown.

  4. Learning Motivation and Adaptive Video Caption Filtering for EFL Learners Using Handheld Devices

    ERIC Educational Resources Information Center

    Hsu, Ching-Kun

    2015-01-01

    The aim of this study was to provide adaptive assistance to improve the listening comprehension of eleventh grade students. This study developed a video-based language learning system for handheld devices, using three levels of caption filtering adapted to student needs. Elementary level captioning excluded 220 English sight words (see Section 1…

  5. Low-Complexity Lossless Compression of Hyperspectral Imagery Via Adaptive Filtering

    NASA Technical Reports Server (NTRS)

    Klimesh, Matthew A.

    2005-01-01

    A low-complexity, adaptive predictive technique for lossless compression of hyperspectral data is presented. The technique relies on the sign algorithm from the repertoire of adaptive filtering. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity.

  6. Low-Complexity Lossless Compression of Hyperspectral Imagery via Adaptive Filtering

    NASA Technical Reports Server (NTRS)

    Klimesh, M.

    2005-01-01

    A low-complexity, adaptive predictive technique for lossless compression of hyperspectral data is presented. The technique relies on the sign algorithm from the repertoire of adaptive filtering. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity.

  7. Block-adaptive filtering and its application to seismic-event detection

    SciTech Connect

    Clark, G.A.

    1981-04-01

    Block digital filtering involves the calculation of a block or finite set of filter output samples from a block of input samples. The motivation for block processing arises from computational advantages of the technique. Block filters take good advantage of parallel processing architectures, which are becoming more and more attractive with the advent of very large scale integrated (VLSI) circuits. This thesis extends the block technique to Wiener and adaptive filters, both of which are statistical filters. The key ingredient to this extension turns out to be the definition of a new performance index, block mean square error (BMSE), which combines the well known sum square error (SSE) and mean square error (MSE). A block adaptive filtering procedure is derived in which the filter coefficients are adjusted once per each output block in accordance with a generalized block least mean-square (BLMS) algorithm. Convergence properties of the BLMS algorithm are studied, including conditions for guaranteed convergence, convergence speed, and convergence accuracy. Simulation examples are given for clarity. Convergence properties of the BLMS and LMS algorithms are analyzed and compared. They are shown to be analogous, and under the proper circumstances, equivalent. The block adaptive filter was applied to the problem of detecting small seismic events in microseismic background noise. The predictor outperformed the world-wide standardized seismograph network (WWSSN) seismometers in improving signal-to-noise ratio (SNR).

  8. Theory and experimental study on low-light-level images by adaptive mode filter

    NASA Astrophysics Data System (ADS)

    Bai, Lianfa; Zhang, Baomin; Liu, Yunfen; Chen, Qian

    1996-09-01

    Real-time low light level (LLL) image processing technology is the important developmental subject in the area of LLL night vision. But there is an essential distinction between the LLL TV image and ordinary TV image, so the conventional digital image processing technique aren't suitable for LLL image. In this paper, the noise theoretical model of LLL imaging system is described and the LLL image processing system is set up. With regard to the characteristics of LLL image and its noise, a novel noise suppression method, adaptive mode filter, is presented. The experimental results show that the adaptive mode filter can suppress the sharp noise of LLL image effectively, and as for the protection of the image edge, the property of adaptive mode filter is better that of median filter. Finally, the processing results and the conclusions are given.

  9. Real-time 3D adaptive filtering for portable imaging systems

    NASA Astrophysics Data System (ADS)

    Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

    2015-03-01

    Portable imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often not able to run with sufficient performance on a portable platform. In recent years, advanced multicore DSPs have been introduced that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms like 3D adaptive filtering, improving the image quality of portable medical imaging devices. In this study, the performance of a 3D adaptive filtering algorithm on a digital signal processor (DSP) is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec.

  10. Adaptive box filters for removal of random noise from digital images

    NASA Technical Reports Server (NTRS)

    Eliason, Eric M.; Mcewen, Alfred S.

    1990-01-01

    Adaptive box-filtering algorithms to remove random bit errors and to smooth noisy data have been developed. For both procedures, the standard deviation of those pixels within a local box surrounding each pixel is used. A series of two or three filters with decreasing box sizes can be run to clean up extremely noisy images and to remove bit errors near sharp edges. The second filter, for noise smoothing, is similar to the 'sigma filter' of Lee (1983). The technique effectively reduces speckle in radar images without eliminating fine details.

  11. An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition.

    PubMed

    Wittenbach, Jason D; Bouchard, Kristofer E; Brainard, Michael S; Jin, Dezhe Z

    2015-10-01

    Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions; and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences. PMID:26448054

  12. An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition

    PubMed Central

    Brainard, Michael S.; Jin, Dezhe Z.

    2015-01-01

    Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions; and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences. PMID:26448054

  13. Optimization of the open-loop liquid crystal adaptive optics retinal imaging system

    NASA Astrophysics Data System (ADS)

    Kong, Ningning; Li, Chao; Xia, Mingliang; Li, Dayu; Qi, Yue; Xuan, Li

    2012-02-01

    An open-loop adaptive optics (AO) system for retinal imaging was constructed using a liquid crystal spatial light modulator (LC-SLM) as the wavefront compensator. Due to the dispersion of the LC-SLM, there was only one illumination source for both aberration detection and retinal imaging in this system. To increase the field of view (FOV) for retinal imaging, a modified mechanical shutter was integrated into the illumination channel to control the size of the illumination spot on the fundus. The AO loop was operated in a pulsing mode, and the fundus was illuminated twice by two laser impulses in a single AO correction loop. As a result, the FOV for retinal imaging was increased to 1.7-deg without compromising the aberration detection accuracy. The correction precision of the open-loop AO system was evaluated in a closed-loop configuration; the residual error is approximately 0.0909λ (root-mean-square, RMS), and the Strehl ratio ranges to 0.7217. Two subjects with differing rates of myopia (-3D and -5D) were tested. High-resolution images of capillaries and photoreceptors were obtained.

  14. An Adaptive Kalman Filter using a Simple Residual Tuning Method

    NASA Technical Reports Server (NTRS)

    Harman, Richard R.

    1999-01-01

    One difficulty in using Kalman filters in real world situations is the selection of the correct process noise, measurement noise, and initial state estimate and covariance. These parameters are commonly referred to as tuning parameters. Multiple methods have been developed to estimate these parameters. Most of those methods such as maximum likelihood, subspace, and observer Kalman Identification require extensive offline processing and are not suitable for real time processing. One technique, which is suitable for real time processing, is the residual tuning method. Any mismodeling of the filter tuning parameters will result in a non-white sequence for the filter measurement residuals. The residual tuning technique uses this information to estimate corrections to those tuning parameters. The actual implementation results in a set of sequential equations that run in parallel with the Kalman filter. Equations for the estimation of the measurement noise have also been developed. These algorithms are used to estimate the process noise and measurement noise for the Wide Field Infrared Explorer star tracker and gyro.

  15. An Adaptive Kalman Filter Using a Simple Residual Tuning Method

    NASA Technical Reports Server (NTRS)

    Harman, Richard R.

    1999-01-01

    One difficulty in using Kalman filters in real world situations is the selection of the correct process noise, measurement noise, and initial state estimate and covariance. These parameters are commonly referred to as tuning parameters. Multiple methods have been developed to estimate these parameters. Most of those methods such as maximum likelihood, subspace, and observer Kalman Identification require extensive offline processing and are not suitable for real time processing. One technique, which is suitable for real time processing, is the residual tuning method. Any mismodeling of the filter tuning parameters will result in a non-white sequence for the filter measurement residuals. The residual tuning technique uses this information to estimate corrections to those tuning parameters. The actual implementation results in a set of sequential equations that run in parallel with the Kalman filter. A. H. Jazwinski developed a specialized version of this technique for estimation of process noise. Equations for the estimation of the measurement noise have also been developed. These algorithms are used to estimate the process noise and measurement noise for the Wide Field Infrared Explorer star tracker and gyro.

  16. Selectivity filters and cysteine-rich extracellular loops in voltage-gated sodium, calcium, and NALCN channels

    PubMed Central

    Stephens, Robert F.; Guan, W.; Zhorov, Boris S.; Spafford, J. David

    2015-01-01

    How nature discriminates sodium from calcium ions in eukaryotic channels has been difficult to resolve because they contain four homologous, but markedly different repeat domains. We glean clues from analyzing the changing pore region in sodium, calcium and NALCN channels, from single-cell eukaryotes to mammals. Alternative splicing in invertebrate homologs provides insights into different structural features underlying calcium and sodium selectivity. NALCN generates alternative ion selectivity with splicing that changes the high field strength (HFS) site at the narrowest level of the hourglass shaped pore where the selectivity filter is located. Alternative splicing creates NALCN isoforms, in which the HFS site has a ring of glutamates contributed by all four repeat domains (EEEE), or three glutamates and a lysine residue in the third (EEKE) or second (EKEE) position. Alternative splicing provides sodium and/or calcium selectivity in T-type channels with extracellular loops between S5 and P-helices (S5P) of different lengths that contain three or five cysteines. All eukaryotic channels have a set of eight core cysteines in extracellular regions, but the T-type channels have an infusion of 4–12 extra cysteines in extracellular regions. The pattern of conservation suggests a possible pairing of long loops in Domains I and III, which are bridged with core cysteines in NALCN, Cav, and Nav channels, and pairing of shorter loops in Domains II and IV in T-type channel through disulfide bonds involving T-type specific cysteines. Extracellular turrets of increasing lengths in potassium channels (Kir2.2, hERG, and K2P1) contribute to a changing landscape above the pore selectivity filter that can limit drug access and serve as an ion pre-filter before ions reach the pore selectivity filter below. Pairing of extended loops likely contributes to the large extracellular appendage as seen in single particle electron cryo-microscopy images of the eel Nav1 channel. PMID

  17. New Approach for IIR Adaptive Lattice Filter Structure Using Simultaneous Perturbation Algorithm

    NASA Astrophysics Data System (ADS)

    Martinez, Jorge Ivan Medina; Nakano, Kazushi; Higuchi, Kohji

    Adaptive infinite impulse response (IIR), or recursive, filters are less attractive mainly because of the stability and the difficulties associated with their adaptive algorithms. Therefore, in this paper the adaptive IIR lattice filters are studied in order to devise algorithms that preserve the stability of the corresponding direct-form schemes. We analyze the local properties of stationary points, a transformation achieving this goal is suggested, which gives algorithms that can be efficiently implemented. Application to the Steiglitz-McBride (SM) and Simple Hyperstable Adaptive Recursive Filter (SHARF) algorithms is presented. Also a modified version of Simultaneous Perturbation Stochastic Approximation (SPSA) is presented in order to get the coefficients in a lattice form more efficiently and with a lower computational cost and complexity. The results are compared with previous lattice versions of these algorithms. These previous lattice versions may fail to preserve the stability of stationary points.

  18. Predictive wavefront control for Adaptive Optics with arbitrary control loop delays

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-10-30

    We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.

  19. Prototype adaptive bow-tie filter based on spatial exposure time modulation

    NASA Astrophysics Data System (ADS)

    Badal, Andreu

    2016-03-01

    In recent years, there has been an increased interest in the development of dynamic bow-tie filters that are able to provide patient-specific x-ray beam shaping. We introduce the first physical prototype of a new adaptive bow-tie filter design based on the concept of "spatial exposure time modulation." While most existing bow-tie filters operate by attenuating the radiation beam differently in different locations using partially attenuating objects, the presented filter shapes the radiation field using two movable completely radio-opaque collimators. The aperture and speed of the collimators is modulated in synchrony with the x-ray exposure to selectively block the radiation emitted to different parts of the object. This mode of operation does not allow the reproduction of every possible attenuation profile, but it can reproduce the profile of any object with an attenuation profile monotonically decreasing from the center to the periphery, such as an object with an elliptical cross section. Therefore, the new adaptive filter provides the same advantages as the currently existing static bow-tie filters, which are typically designed to work for a pre-determined cylindrical object at a fixed distance from the source, and provides the additional capability to adapt its performance at image acquisition time to better compensate for the actual diameter and location of the imaged object. A detailed description of the prototype filter, the implemented control methods, and a preliminary experimental validation of its performance are presented.

  20. An adaptive filter bank for motor imagery based Brain Computer Interface.

    PubMed

    Thomas, Kavitha P; Guan, Cuntai; Tong, Lau Chiew; Prasad, Vinod A

    2008-01-01

    Brain Computer Interface (BCI) provides an alternative communication and control method for people with severe motor disabilities. Motor imagery patterns are widely used in Electroencephalogram (EEG) based BCIs. These motor imagery activities are associated with variation in alpha and beta band power of EEG signals called Event Related Desynchronization/synchronization (ERD/ERS). The dominant frequency bands are subject-specific and therefore performance of motor imagery based BCIs are sensitive to both temporal filtering and spatial filtering. As the optimum filter is strongly subject-dependent, we propose a method that selects the subject-specific discriminative frequency components using time-frequency plots of Fisher ratio of two-class motor imagery patterns. We also propose a low complexity adaptive Finite Impulse Response (FIR) filter bank system based on coefficient decimation technique which can realize the subject-specific bandpass filters adaptively depending on the information of Fisher ratio map. Features are extracted only from the selected frequency components. The proposed adaptive filter bank based system offers average classification accuracy of about 90%, which is slightly better than the existing fixed filter bank system. PMID:19162856

  1. Stent enhancement in digital x-ray fluoroscopy using an adaptive feature enhancement filter

    NASA Astrophysics Data System (ADS)

    Jiang, Yuhao; Zachary, Josey

    2016-03-01

    Fluoroscopic images belong to the classes of low contrast and high noise. Simply lowering radiation dose will render the images unreadable. Feature enhancement filters can reduce patient dose by acquiring images at low dose settings and then digitally restoring them to the original quality. In this study, a stent contrast enhancement filter is developed to selectively improve the contrast of stent contour without dramatically boosting the image noise including quantum noise and clinical background noise. Gabor directional filter banks are implemented to detect the edges and orientations of the stent. A high orientation resolution of 9° is used. To optimize the use of the information obtained from Gabor filters, a computerized Monte Carlo simulation followed by ROC study is used to find the best nonlinear operator. The next stage of filtering process is to extract symmetrical parts in the stent. The global and local symmetry measures are used. The information gathered from previous two filter stages are used to generate a stent contour map. The contour map is then scaled and added back to the original image to get a contrast enhanced stent image. We also apply a spatio-temporal channelized Hotelling observer model and other numerical measures to characterize the response of the filters and contour map to optimize the selections of parameters for image quality. The results are compared to those filtered by an adaptive unsharp masking filter previously developed. It is shown that stent enhancement filter can effectively improve the stent detection and differentiation in the interventional fluoroscopy.

  2. Independent motion detection with a rival penalized adaptive particle filter

    NASA Astrophysics Data System (ADS)

    Becker, Stefan; Hübner, Wolfgang; Arens, Michael

    2014-10-01

    Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic

  3. Wide field adaptive optics laboratory demonstration with closed-loop tomographic control.

    PubMed

    Costille, Anne; Petit, Cyril; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

    2010-03-01

    HOMER, the new bench developed at ONERA devoted to wide field adaptive optics (WFAO) laboratory research, has allowed the first experimental validations of multi-conjugate adaptive optics (MCAO) and laser tomography adaptive optics (LTAO) concepts with a linear quadratic Gaussian (LQG) control approach. Results obtained in LTAO in closed loop show the significant gain in performance brought by LQG control, which allows tomographic reconstruction. We present a calibration and model identification strategy. Experimental results are shown to be consistent with end-to-end simulations. These results are very encouraging and demonstrate robustness of performance with respect to inevitable experimental uncertainties. They represent a first step for the study of very large telescope (VLT) and extremely large telescopes (ELT) instruments. PMID:20208937

  4. Lag Synchronization Between Two Coupled Networks via Open-Plus-Closed-Loop and Adaptive Controls

    NASA Astrophysics Data System (ADS)

    Hu, Tong-Chun; Wu, Yong-Qing; Li, Shi-Xing

    2016-01-01

    In this paper, we study lag synchronization between two coupled networks and apply two types of control schemes, including the open-plus-closed-loop (OPCL) and adaptive controls. We then design the corresponding control algorithms according to the OPCL and adaptive feedback schemes. With the designed controllers, we obtain two theorems on the lag synchronization based on Lyapunov stability theory and Barbalat's lemma. Finally we provide numerical examples to show the effectiveness of the obtained controllers and see that the adaptive control is stronger than the OPCL control when realizing the lag synchronization between two coupled networks with different coupling structures. Supported by the National Natural Science Foundation of China under Grant No. 61304173, Foundation of Liaoning Educational Committee (No. 13-1069) and Hangzhou Polytechnic (No. KZYZ-2009-2)

  5. Adaptive multispectral stimulator providing registered IR and RF data in a closed-loop environment

    NASA Astrophysics Data System (ADS)

    Jones, Stephen C.; Hall, Robert L.

    2004-08-01

    The Multi-Spectral Stimulator described in this paper has been designed to answer the future testing and evaluation needs for emerging multi-spectral technology. This system is portable, low cost, and scalable, and can produce synchronous IR and RF images and signals, respectively, for both injection and projection to multi-mode sensors. The scenes generated are temporally and spatially registered and generated from a three-dimensional database. Its present development provides closed-loop capabilities to a missile simulation. Two adaptive technologies are merged into a flexible system that can stimulate multiple sensors simultaneously in real time. It merges Scientific Research Corporation's Adaptable Radar Environment Simulator (ARES) and Quantum3D/CG2 Inc.'s real-time, multi-spectral Scene Generation system. The stimulator can run in either real-time or stepped mode, providing signals on demand. The resulting stimulator test bed is integrated to a non-real-time high fidelity missile simulation that consists of an IR seeker, IR imaging tracker, and a 6-DOF/Autopilot model. The stimulator design can be modified to stimulate multiple passive sensors, active laser systems, multi-mode systems, multiple radar systems, or almost any combination of sensors. The next planned development stage integrates the system to real-time closed-loop system and associated interface electronics. This will provide a bridge to full hardware-in-the-loop (HWIL) integration for the simulation of a dual mode missile system.

  6. Attitude determination and calibration using a recursive maximum likelihood-based adaptive Kalman filter

    NASA Technical Reports Server (NTRS)

    Kelly, D. A.; Fermelia, A.; Lee, G. K. F.

    1990-01-01

    An adaptive Kalman filter design that utilizes recursive maximum likelihood parameter identification is discussed. At the center of this design is the Kalman filter itself, which has the responsibility for attitude determination. At the same time, the identification algorithm is continually identifying the system parameters. The approach is applicable to nonlinear, as well as linear systems. This adaptive Kalman filter design has much potential for real time implementation, especially considering the fast clock speeds, cache memory and internal RAM available today. The recursive maximum likelihood algorithm is discussed in detail, with special attention directed towards its unique matrix formulation. The procedure for using the algorithm is described along with comments on how this algorithm interacts with the Kalman filter.

  7. Adaptive filtering and prediction of the Southern Oscillation index

    NASA Astrophysics Data System (ADS)

    Keppenne, Christian L.; Ghil, Michael

    1992-12-01

    Singular spectrum analysis (SSA), a variant of principal component analysis, is applied to a time series of the Southern Oscillation index (SOI). The analysis filters out variability unrelated to the Southern Oscillation and separates the high-frequency, 2- to 3-year variability, including the quasi-biennial oscillation, from the lower-frequency 4- to 6-year El Niño cycle. The maximum entropy method (MEM) is applied to forecasting the prefiltered SOI. Prediction based on MEM-associated autoregressive models has useful skill for 30-36 months. A 1993-1994 La Niña event is predicted based on data through February 1992.

  8. Adaptive filtering and prediction of the Southern Oscillation index

    NASA Technical Reports Server (NTRS)

    Keppenne, Christian L.; Ghil, Michael

    1992-01-01

    Singular spectrum analysis (SSA), a variant of principal component analysis, is applied to a time series of the Southern Oscillation index (SOI). The analysis filters out variability unrelated to the Southern Oscillation and separates the high-frequency, 2- to 3-year variability, including the quasi-biennial oscillation, from the lower-frequency 4- to 6-year El Nino cycle. The maximum entropy method (MEM) is applied to forecasting the prefiltered SOI. Prediction based on MEM-associated autoregresive models has useful skill for 30-36 months. A 1993-1994 La Nina event is predicted based on data through February 1992.

  9. Adaptive filtering and prediction of the Southern Oscillation index

    SciTech Connect

    Keppenne, C.L. California Inst. of Technology, Pasadena ); Ghil, M. )

    1992-12-20

    Singular spectrum analysis (SSA), a variant of principal component analysis, is applied to a time series of the Southern Oscillation index (SOI). The analysis filters out variability unrelated to the Southern Oscillation and separates the high-frequency, 2- to 3-year variability, including the quasi-biennial oscillation, from the lower-frequency 4- to 6-year El Nino cycle. The maximum entropy method (MEM) is applied to forecasting the prefiltered SOI. Prediction based on MEM-associated autoregressive models has useful skill for 30-36 months. A 1993-1994 La Nina event is predicted based on data through February 1992. 52 refs., 4 figs.

  10. Predicting Hyper-Chaotic Time Series Using Adaptive Higher-Order Nonlinear Filter

    NASA Astrophysics Data System (ADS)

    Zhang, Jia-Shu; Xiao, Xian-Ci

    2001-03-01

    A newly proposed method, i.e. the adaptive higher-order nonlinear finite impulse response (HONFIR) filter based on higher-order sparse Volterra series expansions, is introduced to predict hyper-chaotic time series. The effectiveness of using the adaptive HONFIR filter for making one-step and multi-step predictions is tested based on very few data points by computer-generated hyper-chaotic time series including the Mackey-Glass equation and four-dimensional nonlinear dynamical system. A comparison is made with some neural networks for predicting the Mackey-Glass hyper-chaotic time series. Numerical simulation results show that the adaptive HONFIR filter proposed here is a very powerful tool for making prediction of hyper-chaotic time series.

  11. Adaptive filters for suppressing irregular hostile jamming in direct sequence spread-spectrum system

    NASA Astrophysics Data System (ADS)

    Lee, Jung Hoon; Lee, Choong Woong

    A stable and high-performance adaptive filter for suppressing irregular hostile jamming in direct-sequence (DS) spread-spectrum systems is designed. A gradient-search fast converging algorithm (GFC) is suggested. For the case of a sudden parameter jump or incoming of an interference, the transient behaviors of the receiver using a GFC adaptive filter are investigated and compared with those of the receiver using a least-mean-square (LMS) or a lattice adaptive filter. The results are shown in the response graphs of the simulated receiver during the short period when the characteristic of a jammer is suddenly changed. Steady-state performances of those receivers are also evaluated in the sense of the excess mean-square error over that of an optimum receiver for suppressing stationary interferences.

  12. A study of infrared spectroscopy de-noising based on LMS adaptive filter

    NASA Astrophysics Data System (ADS)

    Mo, Jia-qing; Lv, Xiao-yi; Yu, Xiao

    2015-12-01

    Infrared spectroscopy has been widely used, but which often contains a lot of noise, so the spectral characteristic of the sample is seriously affected. Therefore the de-noising is very important in the spectrum analysis and processing. In the study of infrared spectroscopy, the least mean square (LMS) adaptive filter was applied in the field firstly. LMS adaptive filter algorithm can reserve the detail and envelope of the effective signal when the method was applied to infrared spectroscopy of breast cancer which signal-to-noise ratio (SNR) is lower than 10 dB, contrast and analysis the result with result of wavelet transform and ensemble empirical mode decomposition (EEMD). The three evaluation standards (SNR, root mean square error (RMSE) and the correlation coefficient (ρ)) fully proved de-noising advantages of LMS adaptive filter in infrared spectroscopy of breast cancer.

  13. ROI extraction of chest CT images using adaptive opening filter

    NASA Astrophysics Data System (ADS)

    Yamada, Nobuhiro; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Eguchi, Kenji; Omatsu, Hironobu; Kakinuma, Ryutaro; Kaneko, Masahiro; Kusumoto, Masahiko; Nishiyama, Hiroyuki; Moriyama, Noriyuki

    2003-05-01

    We have already developed a prototype of computer-aided diagnosis (CAD) system that can automatically detect suspicious shadows from Chest CT images. But the CAD system cannot detect Ground-Grass-Attenuation perfectly. In many cases, this reason depends on the inaccurate extraction of the region of interests (ROI) that CAD system analyzes, so we need to improve it. In this paper, we propose a method of an accurate extraction of the ROI, and compare proposed method to ordinary method that have used in CAD system. Proposed Method is performed by application of the three steps. Firstly we extract lung area using threshold. Secondly we remove the slowly varying bias field using flexible Opening Filter. This Opening Filter is calculated by the combination of the ordinary opening value and the distribution which CT value and contrast follow. Finally we extract Region of Interest using fuzzy clustering. When we applied proposal method to Chest CT images, we got a good result in which ordinary method cannot achieve. In this study we used the Helical CT images that are obtained under the following measurement: 10mm beam width; 20mm/sec table speed; 120kV tube voltage; 50mA tube current; 10mm reconstruction interval.

  14. An Adaptive Filter for the Removal of Drifting Sinusoidal Noise Without a Reference.

    PubMed

    Kelly, John W; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

    2016-01-01

    This paper presents a method for filtering sinusoidal noise with a variable bandwidth filter that is capable of tracking a sinusoid's drifting frequency. The method, which is based on the adaptive noise canceling (ANC) technique, will be referred to here as the adaptive sinusoid canceler (ASC). The ASC eliminates sinusoidal contamination by tracking its frequency and achieving a narrower bandwidth than typical notch filters. The detected frequency is used to digitally generate an internal reference instead of relying on an external one as ANC filters typically do. The filter's bandwidth adjusts to achieve faster and more accurate convergence. In this paper, the focus of the discussion and the data is physiological signals, specifically electrocorticographic (ECoG) neural data contaminated with power line noise, but the presented technique could be applicable to other recordings as well. On simulated data, the ASC was able to reliably track the noise's frequency, properly adjust its bandwidth, and outperform comparative methods including standard notch filters and an adaptive line enhancer. These results were reinforced by visual results obtained from real ECoG data. The ASC showed that it could be an effective method for increasing signal to noise ratio in the presence of drifting sinusoidal noise, which is of significant interest for biomedical applications. PMID:25474814

  15. Seasonal signal capturing in time series of up coordinates by means of adaptive filters

    NASA Astrophysics Data System (ADS)

    Yalvac, S.; Ustun, A.

    2013-12-01

    Digital filters, is a system that performs mathematical operations on a sampled or discrete time signals. Adaptive filters designed for noise canceling are capable tools of decomposing correlated parts of data sets. This kind of filters which optimize itself using Least Mean Square (LMS) algorithm is a powerful tool for understand the truth hidden into the complex data sets like time series in Geosciences. The complex data sets such as CGPS (Continuously operating reference station) station's time series can be understood better with adaptive noise canceling by means of decompose coherent (seasonal effect, tectonic plate motion) and incoherent (noise; site-specific effects) parts of data. In this study, it is aimed to model the subsidence caused by groundwater withdrawal based on the seasonal correlation between consecutive years of CGPS time series. For this purpose, two stations where located into subsidence area of 3 year time series have analyzed with adaptive noise canceling filter. According to the results, the annual movement of these two stations have strong relationship. Also, subsidence behavior are correlated with annual rainfall data. BELD station one year filtered movement KAMN station one year filtered movements

  16. Using adaptive genetic algorithms in the design of morphological filters in textural image processing

    NASA Astrophysics Data System (ADS)

    Li, Wei; Haese-Coat, Veronique; Ronsin, Joseph

    1996-03-01

    An adaptive GA scheme is adopted for the optimal morphological filter design problem. The adaptive crossover and mutation rate which make the GA avoid premature and at the same time assure convergence of the program are successfully used in optimal morphological filter design procedure. In the string coding step, each string (chromosome) is composed of a structuring element coding chain concatenated with a filter sequence coding chain. In decoding step, each string is divided into 3 chains which then are decoded respectively into one structuring element with a size inferior to 5 by 5 and two concatenating morphological filter operators. The fitness function in GA is based on the mean-square-error (MSE) criterion. In string selection step, a stochastic tournament procedure is used to replace the simple roulette wheel program in order to accelerate the convergence. The final convergence of our algorithm is reached by a two step converging strategy. In presented applications of noise removal from texture images, it is found that with the optimized morphological filter sequences, the obtained MSE values are smaller than those using corresponding non-adaptive morphological filters, and the optimized shapes and orientations of structuring elements take approximately the same shapes and orientations as those of the image textons.

  17. New cardiac MRI gating method using event-synchronous adaptive digital filter.

    PubMed

    Park, Hodong; Park, Youngcheol; Cho, Sungpil; Jang, Bongryoel; Lee, Kyoungjoung

    2009-11-01

    When imaging the heart using MRI, an artefact-free electrocardiograph (ECG) signal is not only important for monitoring the patient's heart activity but also essential for cardiac gating to reduce noise in MR images induced by moving organs. The fundamental problem in conventional ECG is the distortion induced by electromagnetic interference. Here, we propose an adaptive algorithm for the suppression of MR gradient artefacts (MRGAs) in ECG leads of a cardiac MRI gating system. We have modeled MRGAs by assuming a source of strong pulses used for dephasing the MR signal. The modeled MRGAs are rectangular pulse-like signals. We used an event-synchronous adaptive digital filter whose reference signal is synchronous to the gradient peaks of MRI. The event detection processor for the event-synchronous adaptive digital filter was implemented using the phase space method-a sort of topology mapping method-and least-squares acceleration filter. For evaluating the efficiency of the proposed method, the filter was tested using simulation and actual data. The proposed method requires a simple experimental setup that does not require extra hardware connections to obtain the reference signals of adaptive digital filter. The proposed algorithm was more effective than the multichannel approach. PMID:19644754

  18. Method and system for training dynamic nonlinear adaptive filters which have embedded memory

    NASA Technical Reports Server (NTRS)

    Rabinowitz, Matthew (Inventor)

    2002-01-01

    Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

  19. An Application Specific Instruction Set Processor (ASIP) for Adaptive Filters in Neural Prosthetics.

    PubMed

    Xin, Yao; Li, Will X Y; Zhang, Zhaorui; Cheung, Ray C C; Song, Dong; Berger, Theodore W

    2015-01-01

    Neural coding is an essential process for neuroprosthetic design, in which adaptive filters have been widely utilized. In a practical application, it is needed to switch between different filters, which could be based on continuous observations or point process, when the neuron models, conditions, or system requirements have changed. As candidates of coding chip for neural prostheses, low-power general purpose processors are not computationally efficient especially for large scale neural population coding. Application specific integrated circuits (ASICs) do not have flexibility to switch between different adaptive filters while the cost for design and fabrication is formidable. In this research work, we explore an application specific instruction set processor (ASIP) for adaptive filters in neural decoding activity. The proposed architecture focuses on efficient computation for the most time-consuming matrix/vector operations among commonly used adaptive filters, being able to provide both flexibility and throughput. Evaluation and implementation results are provided to demonstrate that the proposed ASIP design is area-efficient while being competitive to commercial CPUs in computational performance. PMID:26451817

  20. Image restoration of the open-loop adaptive optics retinal imaging system based on optical transfer function analysis

    NASA Astrophysics Data System (ADS)

    Yu, Lei; Qi, Yue; Li, Dayu; Xia, Mingliang; Xuan, Li

    2013-07-01

    The residual aberrations of the adaptive optics retinal imaging system will decrease the quality of the retinal images. To overcome this obstacle, we found that the optical transfer function (OTF) of the adaptive optics retinal imaging system can be described as the Levy stable distribution. Then a new method is introduced to estimate the OTF of the open-loop adaptive optics system, based on analyzing the residual aberrations of the open-loop adaptive optics system in the residual aberrations measuring mode. At last, the estimated OTF is applied to restore the retinal images of the open-loop adaptive optics retinal imaging system. The contrast and resolution of the restored image is significantly improved with the Laplacian sum (LS) from 0.0785 to 0.1480 and gray mean grads (GMG) from 0.0165 to 0.0306.

  1. Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering.

    PubMed

    Sudeep, P V; Issac Niwas, S; Palanisamy, P; Rajan, Jeny; Xiaojun, Yu; Wang, Xianghong; Luo, Yuemei; Liu, Linbo

    2016-04-01

    Optical coherence tomography (OCT) has continually evolved and expanded as one of the most valuable routine tests in ophthalmology. However, noise (speckle) in the acquired images causes quality degradation of OCT images and makes it difficult to analyze the acquired images. In this paper, an iterative approach based on bilateral filtering is proposed for speckle reduction in multiframe OCT data. Gamma noise model is assumed for the observed OCT image. First, the adaptive version of the conventional bilateral filter is applied to enhance the multiframe OCT data and then the bias due to noise is reduced from each of the filtered frames. These unbiased filtered frames are then refined using an iterative approach. Finally, these refined frames are averaged to produce the denoised OCT image. Experimental results on phantom images and real OCT retinal images demonstrate the effectiveness of the proposed filter. PMID:26907572

  2. Stent enhancement using a locally adaptive unsharp masking filter in digital x-ray fluoroscopy

    NASA Astrophysics Data System (ADS)

    Jiang, Yuhao; Ekanayake, Eranda

    2014-03-01

    Low exposure X-ray fluoroscopy is used to guide some complicate interventional procedures. Due to the inherent high levels of noise, improving the visibility of some interventional devices such as stent will greatly benefit those interventional procedures. Stent, which is made up of tiny steel wires, is also suffered from contrast dilutions of large flat panel detector pixels. A novel adaptive unsharp masking filter has been developed to improve stent contrast in real-time applications. In unsharp masking processing, the background is estimated and subtracted from the original input image to create a foreground image containing objects of interest. A background estimator is therefore critical in the unsharp masking processing. In this specific study, orientation filter kernels are used as the background estimator. To make the process simple and fast, the kernels average along a line of pixels. A high orientation resolution of 18° is used. A nonlinear operator is then used to combine the information from the images generated from convolving the original background and noise only images with orientation filters. A computerized Monte Carlo simulation followed by ROC study is used to identify the best nonlinear operator. We then apply the unsharp masking filter to the images with stents present. It is shown that the locally adaptive unsharp making filter is an effective filter for improving stent visibility in the interventional fluoroscopy. We also apply a spatio-temporal channelized human observer model to quantitatively optimize and evaluate the filter.

  3. Correction of vortex laser beam in a closed-loop adaptive system with bimorph mirror.

    PubMed

    Starikov, F A; Kochemasov, G G; Koltygin, M O; Kulikov, S M; Manachinsky, A N; Maslov, N V; Sukharev, S A; Aksenov, V P; Izmailov, I V; Kanev, F Yu; Atuchin, V V; Soldatenkov, I S

    2009-08-01

    The phase correction of a vortex laser beam is undertaken in the closed-loop adaptive system including a Hartmann-Shack wavefront sensor with singular reconstruction technique and a bimorph piezoceramic mirror. After correction the vortex doughnutlike beam is focused into a beam with bright axial spot that considerably increases the Strehl ratio and optical system resolution. Since the phase break cannot be exactly reproduced on the flexible mirror surface, off-axis vortices appear in the far field at the beam periphery. PMID:19649065

  4. Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces.

    PubMed

    Dangi, Siddharth; Orsborn, Amy L; Moorman, Helene G; Carmena, Jose M

    2013-07-01

    Closed-loop decoder adaptation (CLDA) is an emerging paradigm for achieving rapid performance improvements in online brain-machine interface (BMI) operation. Designing an effective CLDA algorithm requires making multiple important decisions, including choosing the timescale of adaptation, selecting which decoder parameters to adapt, crafting the corresponding update rules, and designing CLDA parameters. These design choices, combined with the specific settings of CLDA parameters, will directly affect the algorithm's ability to make decoder parameters converge to values that optimize performance. In this article, we present a general framework for the design and analysis of CLDA algorithms and support our results with experimental data of two monkeys performing a BMI task. First, we analyze and compare existing CLDA algorithms to highlight the importance of four critical design elements: the adaptation timescale, selective parameter adaptation, smooth decoder updates, and intuitive CLDA parameters. Second, we introduce mathematical convergence analysis using measures such as mean-squared error and KL divergence as a useful paradigm for evaluating the convergence properties of a prototype CLDA algorithm before experimental testing. By applying these measures to an existing CLDA algorithm, we demonstrate that our convergence analysis is an effective analytical tool that can ultimately inform and improve the design of CLDA algorithms. PMID:23607558

  5. Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

    PubMed Central

    Cannistraci, Carlo Vittorio; Abbas, Ahmed; Gao, Xin

    2015-01-01

    Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet's performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis. PMID:25619991

  6. Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra.

    PubMed

    Cannistraci, Carlo Vittorio; Abbas, Ahmed; Gao, Xin

    2015-01-01

    Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet's performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis. PMID:25619991

  7. Adaptive error covariances estimation methods for ensemble Kalman filters

    SciTech Connect

    Zhen, Yicun; Harlim, John

    2015-08-01

    This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.

  8. Adaptive Control of Linear Modal Systems Using Residual Mode Filters and a Simple Disturbance Estimator

    NASA Technical Reports Server (NTRS)

    Balas, Mark; Frost, Susan

    2012-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.

  9. Detecting discontinuities in time series of upper air data: Demonstration of an adaptive filter technique

    SciTech Connect

    Zurbenko, I.; Chen, J.; Rao, S.T.

    1997-11-01

    The issue of global climate change due to increased anthropogenic emissions of greenhouse gases in the atmosphere has gained considerable attention and importance. Climate change studies require the interpretation of weather data collected in numerous locations and/or over the span of several decades. Unfortunately, these data contain biases caused by changes in instruments and data acquisition procedures. It is essential that biases are identified and/or removed before these data can be used confidently in the context of climate change research. The purpose of this paper is to illustrate the use of an adaptive moving average filter and compare it with traditional parametric methods. The advantage of the adaptive filter over traditional parametric methods is that it is less effected by seasonal patterns and trends. The filter has been applied to upper air relative humidity and temperature data. Applied to generated data, the filter has a root mean squared error accuracy of about 600 days when locating changes of 0.1 standard deviations and about 20 days for changes of 0.5 standard deviations. In some circumstances, the accuracy of location estimation can be improved through parametric techniques used in conjunction with the adaptive filter.

  10. IIR filtering based adaptive active vibration control methodology with online secondary path modeling using PZT actuators

    NASA Astrophysics Data System (ADS)

    Boz, Utku; Basdogan, Ipek

    2015-12-01

    Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.

  11. Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

    PubMed Central

    Maier, Andreas; Wigström, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu, Lei; Strobel, Norbert; Fahrig, Rebecca

    2011-01-01

    Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia’s CUDA Interface provided an 8

  12. Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

    SciTech Connect

    Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca

    2011-11-15

    Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold

  13. Improved electromagnetic induction processing with novel adaptive matched filter and matched subspace detection

    NASA Astrophysics Data System (ADS)

    Hayes, Charles E.; McClellan, James H.; Scott, Waymond R.; Kerr, Andrew J.

    2016-05-01

    This work introduces two advances in wide-band electromagnetic induction (EMI) processing: a novel adaptive matched filter (AMF) and matched subspace detection methods. Both advances make use of recent work with a subspace SVD approach to separating the signal, soil, and noise subspaces of the frequency measurements The proposed AMF provides a direct approach to removing the EMI self-response while improving the signal to noise ratio of the data. Unlike previous EMI adaptive downtrack filters, this new filter will not erroneously optimize the EMI soil response instead of the EMI target response because these two responses are projected into separate frequency subspaces. The EMI detection methods in this work elaborate on how the signal and noise subspaces in the frequency measurements are ideal for creating the matched subspace detection (MSD) and constant false alarm rate matched subspace detection (CFAR) metrics developed by Scharf The CFAR detection metric has been shown to be the uniformly most powerful invariant detector.

  14. A multi-stage noise adaptive switching filter for extremely corrupted images

    NASA Astrophysics Data System (ADS)

    Dinh, Hai; Adhami, Reza; Wang, Yi

    2015-07-01

    A multi-stage noise adaptive switching filter (MSNASF) is proposed for the restoration of images extremely corrupted by impulse and impulse-like noise. The filter consists of two steps: noise detection and noise removal. The proposed extrema-based noise detection scheme utilizes the false contouring effect to get better over detection rate at low noise density. It is adaptive and will detect not only impulse but also impulse-like noise. In the noise removal step, a novel multi-stage filtering scheme is proposed. It replaces corrupted pixel with the nearest uncorrupted median to preserve details. When compared with other methods, MSNASF provides better peak signal to noise ratio (PSNR) and structure similarity index (SSIM). A subjective evaluation carried out online also demonstrates that MSNASF yields higher fidelity.

  15. Moving target detection by nonlinear adaptive filtering on temporal profiles in infrared image sequences

    NASA Astrophysics Data System (ADS)

    Liu, Delian; Li, Zhaohui; Wang, Xiaorui; Zhang, Jianqi

    2015-11-01

    Target detection is of great importance both in civil and military fields. Here a new moving target detection approach is proposed, which employs a nonlinear adaptive filter to remove large fluctuations on temporal profiles that are produced by evolving clutters. Initially, this paper discusses the temporal behaviors of different pixels in infrared sequences. Then, the new nonlinear adaptive filter that is a variation of the median-modified Wiener filter is given to extract pulse signals on temporal profiles that relate to moving targets. Next, the variance of each temporal profile is estimated by segmenting each temporal profile into several segments to normalize the amplitude of the pulse signals. Finally, the proposed approach is tested via two infrared image sequences and compared with several conventional target detection algorithms. The results show our approach has a high effectiveness in extracting target temporal profiles amidst heavy and slowly evolving clutters.

  16. Low-power adaptive spike detector based on a sigma-delta control loop.

    PubMed

    Gagnon-Turcotte, G; Sawan, M; Gosselin, B

    2015-08-01

    This paper presents a resources-optimized digital action potential (AP) detector featuring an adaptive threshold based on a new Sigma-delta control loop. The proposed AP detector is optimized for utilizing low hardware resources, which makes it suitable for implementation on most popular low-power microcontrollers units (MCU). The adaptive threshold is calculated using a digital control loop based on a Sigma-delta modulator that precisely estimates the standard deviation of the amplitude of the neuronal signal. The detector was implemented on a popular low-power MCU and fully characterized experimentally using previously recorded neural signals with different signal-to-noise ratios. A comparison of the obtained results with other thresholding approaches shows that the proposed method can compete with high performance and highly resources demanding spike detection approaches while achieving up to 100% of true positive detection rate at high SNR, and up to 63% for an SNR as low as 0 dB, while necessitating an execution time as low as 11 μs with the MCU operating at 8 MHz. PMID:26736719

  17. A dual-pass Mach-Zehnder interferometer filter using a TCF loop mirror for double-wavelength fiber lasers

    NASA Astrophysics Data System (ADS)

    Zou, Hui; Lou, Shuqin; Su, Wei; Wang, Xin

    2013-09-01

    A dual-pass Mach-Zehnder interferometer filter using a section of twin-core fiber (TCF) loop mirror is proposed. The filter is theoretically and experimentally studied for various interferometer arm difference when TCF length is constant. Theoretical results are validated by the experimental demonstration and in good agreement with the experimental results. And then, by using the filter in a ring fiber laser, a stable and switchable dual-wavelength lasing is obtained experimentally. The 3-dB bandwidth and the SMSR of the output laser are 0.015 nm and higher than 62.4 dB, respectively. The peak power fluctuation and wavelength shift are also monitored to be less than 0.04 dB and 0.02 nm over an hour at room temperature. Furthermore, the output laser can be switched between single and dual wavelength by carefully adjusting the PCs. The experimental results show that the filter can suppress mode competition effectively, improve the SMSR availably, and enhance the stability of the output lasing.

  18. Revisiting the relationship between adaptive smoothing and anisotropic diffusion with modified filters.

    PubMed

    Ham, Bumsub; Min, Dongbo; Sohn, Kwanghoon

    2013-03-01

    Anisotropic diffusion has been known to be closely related to adaptive smoothing and discretized in a similar manner. This paper revisits a fundamental relationship between two approaches. It is shown that adaptive smoothing and anisotropic diffusion have different theoretical backgrounds by exploring their characteristics with the perspective of normalization, evolution step size, and energy flow. Based on this principle, adaptive smoothing is derived from a second order partial differential equation (PDE), not a conventional anisotropic diffusion, via the coupling of Fick's law with a generalized continuity equation where a "source" or "sink" exists, which has not been extensively exploited. We show that the source or sink is closely related to the asymmetry of energy flow as well as the normalization term of adaptive smoothing. It enables us to analyze behaviors of adaptive smoothing, such as the maximum principle and stability with a perspective of a PDE. Ultimately, this relationship provides new insights into application-specific filtering algorithm design. By modeling the source or sink in the PDE, we introduce two specific diffusion filters, the robust anisotropic diffusion and the robust coherence enhancing diffusion, as novel instantiations which are more robust against the outliers than the conventional filters. PMID:23193236

  19. Parametric adaptive estimation and backstepping control of electro-hydraulic actuator with decayed memory filter.

    PubMed

    Guo, Qing; Sun, Ping; Yin, Jing-Min; Yu, Tian; Jiang, Dan

    2016-05-01

    Some unknown parameter estimation of electro-hydraulic system (EHS) should be considered in hydraulic controller design due to many parameter uncertainties in practice. In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load). The unknown parameters of EHS model are estimated by the parametric adaptive estimation law. Then the recursive backstepping controller is designed by Lyapunov technique to realize the displacement control of EHS. To avoid explosion of virtual control in traditional backstepping, a decayed memory filter is presented to re-estimate the virtual control and the dynamic external load. The effectiveness of the proposed controller has been demonstrated by comparison with the controller without adaptive and filter estimation. The comparative experimental results in critical working conditions indicate the proposed approach can achieve better dynamic performance on the motion control of Two-DOF robotic arm. PMID:26920086

  20. Neural Network Aided Adaptive Extended Kalman Filtering Approach for DGPS Positioning

    NASA Astrophysics Data System (ADS)

    Jwo, Dah-Jing; Huang, Hung-Chih

    2004-09-01

    The extended Kalman filter, when employed in the GPS receiver as the navigation state estimator, provides optimal solutions if the noise statistics for the measurement and system are completely known. In practice, the noise varies with time, which results in performance degradation. The covariance matching method is a conventional adaptive approach for estimation of noise covariance matrices. The technique attempts to make the actual filter residuals consistent with their theoretical covariance. However, this innovation-based adaptive estimation shows very noisy results if the window size is small. To resolve the problem, a multilayered neural network is trained to identify the measurement noise covariance matrix, in which the back-propagation algorithm is employed to iteratively adjust the link weights using the steepest descent technique. Numerical simulations show that based on the proposed approach the adaptation performance is substantially enhanced and the positioning accuracy is substantially improved.

  1. A unified set-based test with adaptive filtering for gene-environment interaction analyses.

    PubMed

    Liu, Qianying; Chen, Lin S; Nicolae, Dan L; Pierce, Brandon L

    2016-06-01

    In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate P-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data. PMID:26496228

  2. A unified set-based test with adaptive filtering for gene-environment interaction analyses

    PubMed Central

    Liu, Qianying; Chen, Lin S.; Nicolae, Dan L.; Pierce, Brandon L.

    2015-01-01

    Summary In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate p-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data. PMID:26496228

  3. Tunable multi-wavelength thulium-doped fiber laser incorporating two-stage cascaded Sagnac loop comb filter

    NASA Astrophysics Data System (ADS)

    Zhu, Lianqing; He, Wei; Dong, Mingli; Lou, Xiaoping; Luo, Fei

    2016-08-01

    A tunable multi-wavelength narrow-linewidth thulium-doped fiber laser employing two-stage cascaded Sagnac loop mirrors is proposed and experimentally demonstrated. The designed fiber laser is composed of a pump source, wavelength division multiplex, circulator, thulium-doped fiber, polarization controllers (PCs), couplers and polarization-maintaining fibers (PMFs). Two cascaded Sagnac loops are used as the cavity reflector and filter, and the proposed filter is fabricated using two sections of PMFs with 2-m and 1-m lengths, respectively. In the experiment, the laser threshold is 110 mW, and laser can emit single, double, triple, quadruple and quintuple wavelengths in the spectral range of 1873-1901 nm through the simultaneous adjustment of the two PCs. The power fluctuations and 3-dB linewidth are less than 2.1 dB and 0.2 nm, respectively, over 10 min at room temperature, and the side-mode suppression ratio is greater than 20 dB. The proposed laser will be useful in various fields, such as spectral analysis, fiber sensing and optical communication.

  4. Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators

    NASA Astrophysics Data System (ADS)

    Law, K. J. H.; Sanz-Alonso, D.; Shukla, A.; Stuart, A. M.

    2016-06-01

    In the context of filtering chaotic dynamical systems it is well-known that partial observations, if sufficiently informative, can be used to control the inherent uncertainty due to chaos. The purpose of this paper is to investigate, both theoretically and numerically, conditions on the observations of chaotic systems under which they can be accurately filtered. In particular, we highlight the advantage of adaptive observation operators over fixed ones. The Lorenz '96 model is used to exemplify our findings. We consider discrete-time and continuous-time observations in our theoretical developments. We prove that, for fixed observation operator, the 3DVAR filter can recover the system state within a neighbourhood determined by the size of the observational noise. It is required that a sufficiently large proportion of the state vector is observed, and an explicit form for such sufficient fixed observation operator is given. Numerical experiments, where the data is incorporated by use of the 3DVAR and extended Kalman filters, suggest that less informative fixed operators than given by our theory can still lead to accurate signal reconstruction. Adaptive observation operators are then studied numerically; we show that, for carefully chosen adaptive observation operators, the proportion of the state vector that needs to be observed is drastically smaller than with a fixed observation operator. Indeed, we show that the number of state coordinates that need to be observed may even be significantly smaller than the total number of positive Lyapunov exponents of the underlying system.

  5. Adaptive clutter rejection filters for airborne Doppler weather radar applied to the detection of low altitude windshear

    NASA Technical Reports Server (NTRS)

    Keel, Byron M.

    1989-01-01

    An optimum adaptive clutter rejection filter for use with airborne Doppler weather radar is presented. The radar system is being designed to operate at low-altitudes for the detection of windshear in an airport terminal area where ground clutter returns may mask the weather return. The coefficients of the adaptive clutter rejection filter are obtained using a complex form of a square root normalized recursive least squares lattice estimation algorithm which models the clutter return data as an autoregressive process. The normalized lattice structure implementation of the adaptive modeling process for determining the filter coefficients assures that the resulting coefficients will yield a stable filter and offers possible fixed point implementation. A 10th order FIR clutter rejection filter indexed by geographical location is designed through autoregressive modeling of simulated clutter data. Filtered data, containing simulated dry microburst and clutter return, are analyzed using pulse-pair estimation techniques. To measure the ability of the clutter rejection filters to remove the clutter, results are compared to pulse-pair estimates of windspeed within a simulated dry microburst without clutter. In the filter evaluation process, post-filtered pulse-pair width estimates and power levels are also used to measure the effectiveness of the filters. The results support the use of an adaptive clutter rejection filter for reducing the clutter induced bias in pulse-pair estimates of windspeed.

  6. Clock recovering characteristics of adaptive finite-impulse-response filters in digital coherent optical receivers.

    PubMed

    Kikuchi, Kazuro

    2011-03-14

    We analyze the clock-recovery process based on adaptive finite-impulse-response (FIR) filtering in digital coherent optical receivers. When the clock frequency is synchronized between the transmitter and the receiver, only five taps in half-symbol-spaced FIR filters can adjust the sampling phase of analog-to-digital conversion optimally, enabling bit-error rate performance independent of the initial sampling phase. Even if the clock frequency is not synchronized between them, the clock-frequency misalignment can be adjusted within an appropriate block interval; thus, we can achieve an asynchronous clock mode of operation of digital coherent receivers with block processing of the symbol sequence. PMID:21445201

  7. Parameter estimation with an iterative version of the adaptive Gaussian mixture filter

    NASA Astrophysics Data System (ADS)

    Stordal, A.; Lorentzen, R.

    2012-04-01

    The adaptive Gaussian mixture filter (AGM) was introduced in Stordal et. al. (ECMOR 2010) as a robust filter technique for large scale applications and an alternative to the well known ensemble Kalman filter (EnKF). It consists of two analysis steps, one linear update and one weighting/resampling step. The bias of AGM is determined by two parameters, one adaptive weight parameter (forcing the weights to be more uniform to avoid filter collapse) and one pre-determined bandwidth parameter which decides the size of the linear update. It has been shown that if the adaptive parameter approaches one and the bandwidth parameter decrease with increasing sample size, the filter can achieve asymptotic optimality. For large scale applications with a limited sample size the filter solution may be far from optimal as the adaptive parameter gets close to zero depending on how well the samples from the prior distribution match the data. The bandwidth parameter must often be selected significantly different from zero in order to make large enough linear updates to match the data, at the expense of bias in the estimates. In the iterative AGM we take advantage of the fact that the history matching problem is usually estimation of parameters and initial conditions. If the prior distribution of initial conditions and parameters is close to the posterior distribution, it is possible to match the historical data with a small bandwidth parameter and an adaptive weight parameter that gets close to one. Hence the bias of the filter solution is small. In order to obtain this scenario we iteratively run the AGM throughout the data history with a very small bandwidth to create a new prior distribution from the updated samples after each iteration. After a few iterations, nearly all samples from the previous iteration match the data and the above scenario is achieved. A simple toy problem shows that it is possible to reconstruct the true posterior distribution using the iterative version of

  8. Adaptive switching filter for noise removal in highly corrupted depth maps from Time-of-Flight image sensors

    NASA Astrophysics Data System (ADS)

    Lee, Seunghee; Bae, Kwanghyuk; Kyung, Kyu-min; Kim, Tae-Chan

    2012-03-01

    In this work, we present an adaptive switching filter for noise reduction and sharpness preservation in depth maps provided by Time-of-Flight (ToF) image sensors. Median filter and bilateral filter are commonly used in cost-sensitive applications where low computational complexity is needed. However, median filter blurs fine details and edges in depth map while bilateral filter works poorly with impulse noise present in the image. Since the variance of depth is inversely proportional to amplitude, we suggest an adaptive filter that switches between median filter and bilateral filter based on the level of amplitude. If a region of interest has low amplitude indicating low confidence level of measured depth data, then median filter is applied on the depth at the position while regions with high level of amplitude is processed with bilateral filter using Gaussian kernel with adaptive weights. Results show that the suggested algorithm performs surface smoothing and detail preservation as well as median filter and bilateral filter, respectively. By using the suggested algorithm, significant gain in visual quality is obtained in depth maps while low computational cost is maintained.

  9. Optimal reconstruction for closed-loop ground-layer adaptive optics with elongated spots.

    PubMed

    Béchet, Clémentine; Tallon, Michel; Tallon-Bosc, Isabelle; Thiébaut, Éric; Le Louarn, Miska; Clare, Richard M

    2010-11-01

    The design of the laser-guide-star-based adaptive optics (AO) systems for the Extremely Large Telescopes requires careful study of the issue of elongated spots produced on Shack-Hartmann wavefront sensors. The importance of a correct modeling of the nonuniformity and correlations of the noise induced by this elongation has already been demonstrated for wavefront reconstruction. We report here on the first (to our knowledge) end-to-end simulations of closed-loop ground-layer AO with laser guide stars with such an improved noise model. The results are compared with the level of performance predicted by a classical noise model for the reconstruction. The performance is studied in terms of ensquared energy and confirms that, thanks to the improved noise model, central or side launching of the lasers does not affect the performance with respect to the laser guide stars' flux. These two launching schemes also perform similarly whatever the atmospheric turbulence strength. PMID:21045872

  10. Adaptive nonlocal means filtering based on local noise level for CT denoising

    SciTech Connect

    Li, Zhoubo; Trzasko, Joshua D.; Lake, David S.; Blezek, Daniel J.; Manduca, Armando; Yu, Lifeng; Fletcher, Joel G.; McCollough, Cynthia H.

    2014-01-15

    Purpose: To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. Methods: A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analytical noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. Results: The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the

  11. Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces

    NASA Astrophysics Data System (ADS)

    Lu, Jun; McFarland, Dennis J.; Wolpaw, Jonathan R.

    2013-02-01

    Objective. Sensorimotor rhythms (SMRs) are 8-30 Hz oscillations in the electroencephalogram (EEG) recorded from the scalp over sensorimotor cortex that change with movement and/or movement imagery. Many brain-computer interface (BCI) studies have shown that people can learn to control SMR amplitudes and can use that control to move cursors and other objects in one, two or three dimensions. At the same time, if SMR-based BCIs are to be useful for people with neuromuscular disabilities, their accuracy and reliability must be improved substantially. These BCIs often use spatial filtering methods such as common average reference (CAR), Laplacian (LAP) filter or common spatial pattern (CSP) filter to enhance the signal-to-noise ratio of EEG. Here, we test the hypothesis that a new filter design, called an ‘adaptive Laplacian (ALAP) filter’, can provide better performance for SMR-based BCIs. Approach. An ALAP filter employs a Gaussian kernel to construct a smooth spatial gradient of channel weights and then simultaneously seeks the optimal kernel radius of this spatial filter and the regularization parameter of linear ridge regression. This optimization is based on minimizing the leave-one-out cross-validation error through a gradient descent method and is computationally feasible. Main results. Using a variety of kinds of BCI data from a total of 22 individuals, we compare the performances of ALAP filter to CAR, small LAP, large LAP and CSP filters. With a large number of channels and limited data, ALAP performs significantly better than CSP, CAR, small LAP and large LAP both in classification accuracy and in mean-squared error. Using fewer channels restricted to motor areas, ALAP is still superior to CAR, small LAP and large LAP, but equally matched to CSP. Significance. Thus, ALAP may help to improve the accuracy and robustness of SMR-based BCIs.

  12. Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop

    PubMed Central

    Ewing, Kate C.; Fairclough, Stephen H.; Gilleade, Kiel

    2016-01-01

    Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed. PMID:27242486

  13. Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop.

    PubMed

    Ewing, Kate C; Fairclough, Stephen H; Gilleade, Kiel

    2016-01-01

    Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed. PMID:27242486

  14. A 3D approach for object recognition in illuminated scenes with adaptive correlation filters

    NASA Astrophysics Data System (ADS)

    Picos, Kenia; Díaz-Ramírez, Víctor H.

    2015-09-01

    In this paper we solve the problem of pose recognition of a 3D object in non-uniformly illuminated and noisy scenes. The recognition system employs a bank of space-variant correlation filters constructed with an adaptive approach based on local statistical parameters of the input scene. The position and orientation of the target are estimated with the help of the filter bank. For an observed input frame, the algorithm computes the correlation process between the observed image and the bank of filters using a combination of data and task parallelism by taking advantage of a graphics processing unit (GPU) architecture. The pose of the target is estimated by finding the template that better matches the current view of target within the scene. The performance of the proposed system is evaluated in terms of recognition accuracy, location and orientation errors, and computational performance.

  15. Adaptive filtering for reduction of speckle in ultrasonic pulse-echo images.

    PubMed

    Bamber, J C; Daft, C

    1986-01-01

    Current medical ultrasonic scanning instrumentation permits the display of fine image detail (speckle) which does not transfer useful information but degrades the apparent low contrast resolution in the image. An adaptive two-dimensional filter has been developed which uses local features of image texture to recognize and maximally low-pass filter those parts of the image which correspond to fully developed speckle, while substantially preserving information associated with resolved-object structure. A first implementation of the filter is described which uses the ratio of the local variance and the local mean as the speckle recognition feature. Preliminary results of applying this form of display processing to medical ultrasound images are very encouraging; it appears that the visual perception of features such as small discrete structures, subtle fluctuations in mean echo level and changes in image texture may be enhanced relative to that for unprocessed images. PMID:3510500

  16. Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum

    PubMed Central

    Wilson, Emma D.; Assaf, Tareq; Pearson, Martin J.; Rossiter, Jonathan M.; Dean, Paul; Anderson, Sean R.; Porrill, John

    2015-01-01

    The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks. PMID:26257638

  17. Vibration control of a flexible beam driven by a ball-screw stage with adaptive notch filters and a line enhancer

    NASA Astrophysics Data System (ADS)

    Wu, Shang-Teh; Lian, Sing-Han; Chen, Sheng-Han

    2015-07-01

    For a low-stiffness beam driven by a ball-screw stage, the lateral vibrations cannot be adequately controlled by a collocated compensator based on rotary-encoder feedback alone. Acceleration signals at the tip of the flexible beam are measured for active vibration control in addition to the collocated compensator. A second-order bandpass filter (a line enhancer) and two notch filters are included in the acceleration-feedback loop to raise modal dampings for the first and the second flexible modes without exciting higher-frequency resonances. A novel adaptation algorithm is devised to tune the center frequencies of the notch filters in real time. It consists of a second-order low-pass filter, a second-order bandpass filter and a phase detector. Improvement of the control system is elaborated progressively with the root-locus and bode-plot analyses, along with a physical interpretation. Extensive testings are conducted on an experimental device to verify the effectiveness of the control method.

  18. Sensorless control of salient PMSM with adaptive integrator and resistance online identification using strong tracking filter

    NASA Astrophysics Data System (ADS)

    Ma, Shaokang; Wu, Peijun; Ji, Jinhu; Li, Xuchun

    2016-02-01

    This article presents a sensorless control approach of salient PMSM with an online parameter identifier. Adaptive Integrator is proposed and utilised for the estimation of active flux and rotor position. As a result, integrator overflow caused by DC offset is avoided. Meanwhile, an online stator resistance identification algorithm using strong tracking filter is employed, and the identified stator resistance is fed back to the estimating algorithm. Thus, the estimating algorithm can calculate the rotor position correctly. Simulations and experimental results validate the feasibility of both adaptive integrator and the parameter identification method.

  19. Particle filter based visual tracking with multi-cue adaptive fusion

    NASA Astrophysics Data System (ADS)

    Li, Anping; Jing, Zhongliang; Hu, Shiqiang

    2005-06-01

    To improve the robustness of visual tracking in complex environments such as: cluttered backgrounds, partial occlusions, similar distraction and pose variations, a novel tracking method based on adaptive fusion and particle filter is proposed in this paper. In this method, the image color and shape cues are adaptively fused to represent the target observation; fuzzy logic is applied to dynamically adjust each cue weight according to its associated reliability in the past frame; particle filter is adopted to deal with non-linear and non-Gaussian problems in visual tracking. The method is demonstrated to be robust to illumination changes, pose variations, partial occlusions, cluttered backgrounds and camera motion for a test image sequence.

  20. Denoising preterm EEG by signal decomposition and adaptive filtering: a comparative study.

    PubMed

    Navarro, X; Porée, F; Beuchée, A; Carrault, G

    2015-03-01

    Electroencephalography (EEG) from preterm infant monitoring systems is usually contaminated by several sources of noise that have to be removed in order to correctly interpret signals and perform automated analysis reliably. Band-pass and adaptive filters (AF) continue to be systematically applied, but their efficacy may be decreased facing preterm EEG patterns such as the tracé alternant and slow delta-waves. In this paper, we propose the combination of EEG decomposition with AF to improve the overall denoising process. Using artificially contaminated signals from real EEGs, we compared the quality of filtered signals applying different decomposition techniques: the discrete wavelet transform, the empirical mode decomposition (EMD) and a recent improved version, the complete ensemble EMD with adaptive noise. Simulations demonstrate that introducing EMD-based techniques prior to AF can reduce up to 30% the root mean squared errors in denoised EEGs. PMID:25659233

  1. Signal subspace analysis for decoherent processes during interferometric fiber-optic gyroscopes using synchronous adaptive filters.

    PubMed

    Li, Yongxiao; Wang, Zinan; Peng, Chao; Li, Zhengbin

    2014-10-10

    Conventional signal processing methods for improving the random walk coefficient and the bias stability of interferometric fiber-optic gyroscopes are usually implemented in one-dimension sequence. In this paper, as a comparison, we allocated synchronous adaptive filters with the calculations of correlations of multidimensional signals in the perspective of the signal subspace. First, two synchronous independent channels are obtained through quadrature demodulation. Next, synchronous adaptive filters were carried out in order to project the original channels to the high related error channels and the approximation channels. The error channel signals were then processed by principal component analysis for suppressing coherent noises. Finally, an optimal state estimation of these error channels and approximation channels based on the Kalman gain coefficient was operated. Experimental results show that this signal processing method improved the raw measurements' variance from 0.0630 [(°/h)2] to 0.0103 [(°/h)2]. PMID:25322393

  2. Adaptive filtering and maximum entropy spectra with application to changes in atmospheric angular momentum

    NASA Technical Reports Server (NTRS)

    Penland, Cecile; Ghil, Michael; Weickmann, Klaus M.

    1991-01-01

    The spectral resolution and statistical significance of a harmonic analysis obtained by low-order MEM can be improved by subjecting the data to an adaptive filter. This adaptive filter consists of projecting the data onto the leading temporal empirical orthogonal functions obtained from singular spectrum analysis (SSA). The combined SSA-MEM method is applied both to a synthetic time series and a time series of AAM data. The procedure is very effective when the background noise is white and less so when the background noise is red. The latter case obtains in the AAM data. Nevertheless, reliable evidence for intraseasonal and interannual oscillations in AAM is detected. The interannual periods include a quasi-biennial one and an LF one, of 5 years, both related to the El Nino/Southern Oscillation. In the intraseasonal band, separate oscillations of about 48.5 and 51 days are ascertained.

  3. Ensembles of adaptive spatial filters increase BCI performance: an online evaluation

    NASA Astrophysics Data System (ADS)

    Sannelli, Claudia; Vidaurre, Carmen; Müller, Klaus-Robert; Blankertz, Benjamin

    2016-08-01

    Objective: In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain–computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Approach: Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. Main results: The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. Significance: CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI

  4. Blended particle methods with adaptive subspaces for filtering turbulent dynamical systems

    NASA Astrophysics Data System (ADS)

    Qi, Di; Majda, Andrew J.

    2015-04-01

    It is a major challenge throughout science and engineering to improve uncertain model predictions by utilizing noisy data sets from nature. Hybrid methods combining the advantages of traditional particle filters and the Kalman filter offer a promising direction for filtering or data assimilation in high dimensional turbulent dynamical systems. In this paper, blended particle filtering methods that exploit the physical structure of turbulent dynamical systems are developed. Non-Gaussian features of the dynamical system are captured adaptively in an evolving-in-time low dimensional subspace through particle methods, while at the same time statistics in the remaining portion of the phase space are amended by conditional Gaussian mixtures interacting with the particles. The importance of both using the adaptively evolving subspace and introducing conditional Gaussian statistics in the orthogonal part is illustrated here by simple examples. For practical implementation of the algorithms, finding the most probable distributions that characterize the statistics in the phase space as well as effective resampling strategies is discussed to handle realizability and stability issues. To test the performance of the blended algorithms, the forty dimensional Lorenz 96 system is utilized with a five dimensional subspace to run particles. The filters are tested extensively in various turbulent regimes with distinct statistics and with changing observation time frequency and both dense and sparse spatial observations. In real applications perfect dynamical models are always inaccessible considering the complexities in both modeling and computation of high dimensional turbulent system. The effects of model errors from imperfect modeling of the systems are also checked for these methods. The blended methods show uniformly high skill in both capturing non-Gaussian statistics and achieving accurate filtering results in various dynamical regimes with and without model errors.

  5. Gas image enhancement based on adaptive time-domain filtering and morphology

    NASA Astrophysics Data System (ADS)

    Zhang, Changxing; Wang, Lingxue; Li, Jiakun; Long, Yunting; Zhang, Bei

    2011-05-01

    The fingerprint region of most gases is within 3 to 14μm. A mid-wave or long-wave infrared thermal imager is therefore commonly applied in gas detection. With further influence of low gas concentration and heterogeneity of infrared focal plane arrays, the image has numerous drawbacks. These include loud noise, weak gas signal, gridding, and dead points, all of which are particularly evident in sequential images. In order to solve these problems, we take into account the characteristics of the leaking gas image and propose an enhancement method based on adaptive time-domain filtering with morphology. The adaptive time-domain filtering which operates on time sequence images is a hybrid method combining the recursive filtering and mean filtering. It segments gas and background according to a selected threshold; removes speckle noise according to the median; and removes background domain using weighted difference image. The morphology method can not only dilate the gas region along the direction of gas diffusion to greatly enhance the visibility of the leakage area, but also effectively remove the noise, and smooth the contour. Finally, the false color is added to the gas domain. Results show that the gas infrared region is effectively enhanced.

  6. Adaptive filter design based on the LMS algorithm for delay elimination in TCR/FC compensators.

    PubMed

    Hooshmand, Rahmat Allah; Torabian Esfahani, Mahdi

    2011-04-01

    Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on adaptive filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm designed for the adaptive filters is performed based on the least mean square (LMS) algorithm. In this design, instead of fixed capacitors, band-pass LC filters are used. To evaluate the filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system. PMID:21193194

  7. Removal of Cardiopulmonary Resuscitation Artifacts with an Enhanced Adaptive Filtering Method: An Experimental Trial

    PubMed Central

    Gong, Yushun; Yu, Tao; Chen, Bihua; He, Mi; Li, Yongqin

    2014-01-01

    Current automated external defibrillators mandate interruptions of chest compression to avoid the effect of artifacts produced by CPR for reliable rhythm analyses. But even seconds of interruption of chest compression during CPR adversely affects the rate of restoration of spontaneous circulation and survival. Numerous digital signal processing techniques have been developed to remove the artifacts or interpret the corrupted ECG with promising result, but the performance is still inadequate, especially for nonshockable rhythms. In the present study, we suppressed the CPR artifacts with an enhanced adaptive filtering method. The performance of the method was evaluated by comparing the sensitivity and specificity for shockable rhythm detection before and after filtering the CPR corrupted ECG signals. The dataset comprised 283 segments of shockable and 280 segments of nonshockable ECG signals during CPR recorded from 22 adult pigs that experienced prolonged cardiac arrest. For the unfiltered signals, the sensitivity and specificity were 99.3% and 46.8%, respectively. After filtering, a sensitivity of 93.3% and a specificity of 96.0% were achieved. This animal trial demonstrated that the enhanced adaptive filtering method could significantly improve the detection of nonshockable rhythms without compromising the ability to detect a shockable rhythm during uninterrupted CPR. PMID:24795878

  8. Adaptive non-local means filtering based on local noise level for CT denoising

    NASA Astrophysics Data System (ADS)

    Li, Zhoubo; Yu, Lifeng; Trzasko, Joshua D.; Fletcher, Joel G.; McCollough, Cynthia H.; Manduca, Armando

    2012-03-01

    Radiation dose from CT scans is an increasing health concern in the practice of radiology. Higher dose scans can produce clearer images with high diagnostic quality, but may increase the potential risk of radiation-induced cancer or other side effects. Lowering radiation dose alone generally produces a noisier image and may degrade diagnostic performance. Recently, CT dose reduction based on non-local means (NLM) filtering for noise reduction has yielded promising results. However, traditional NLM denoising operates under the assumption that image noise is spatially uniform noise, while in CT images the noise level varies significantly within and across slices. Therefore, applying NLM filtering to CT data using a global filtering strength cannot achieve optimal denoising performance. In this work, we have developed a technique for efficiently estimating the local noise level for CT images, and have modified the NLM algorithm to adapt to local variations in noise level. The local noise level estimation technique matches the true noise distribution determined from multiple repetitive scans of a phantom object very well. The modified NLM algorithm provides more effective denoising of CT data throughout a volume, and may allow significant lowering of radiation dose. Both the noise map calculation and the adaptive NLM filtering can be performed in times that allow integration with the clinical workflow.

  9. Data assimilation for unsaturated flow models with restart adaptive probabilistic collocation based Kalman filter

    NASA Astrophysics Data System (ADS)

    Man, Jun; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng

    2016-06-01

    The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a sufficiently large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the polynomial chaos expansion (PCE) to represent and propagate the uncertainties in parameters and states. However, PCKF suffers from the so-called "curse of dimensionality". Its computational cost increases drastically with the increasing number of parameters and system nonlinearity. Furthermore, PCKF may fail to provide accurate estimations due to the joint updating scheme for strongly nonlinear models. Motivated by recent developments in uncertainty quantification and EnKF, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problems. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected at each assimilation step; the "restart" scheme is utilized to eliminate the inconsistency between updated model parameters and states variables. The performance of RAPCKF is systematically tested with numerical cases of unsaturated flow models. It is shown that the adaptive approach and restart scheme can significantly improve the performance of PCKF. Moreover, RAPCKF has been demonstrated to be more efficient than EnKF with the same computational cost.

  10. Ship detection for high resolution optical imagery with adaptive target filter

    NASA Astrophysics Data System (ADS)

    Ju, Hongbin

    2015-10-01

    Ship detection is important due to both its civil and military use. In this paper, we propose a novel ship detection method, Adaptive Target Filter (ATF), for high resolution optical imagery. The proposed framework can be grouped into two stages, where in the first stage, a test image is densely divided into different detection windows and each window is transformed to a feature vector in its feature space. The Histograms of Oriented Gradients (HOG) is accumulated as a basic feature descriptor. In the second stage, the proposed ATF highlights all the ship regions and suppresses the undesired backgrounds adaptively. Each detection window is assigned a score, which represents the degree of the window belonging to a certain ship category. The ATF can be adaptively obtained by the weighted Logistic Regression (WLR) according to the distribution of backgrounds and targets of the input image. The main innovation of our method is that we only need to collect positive training samples to build the filter, while the negative training samples are adaptively generated by the input image. This is different to other classification method such as Support Vector Machine (SVM) and Logistic Regression (LR), which need to collect both positive and negative training samples. The experimental result on 1-m high resolution optical images shows the proposed method achieves a desired ship detection performance with higher quality and robustness than other methods, e.g., SVM and LR.

  11. Filter accuracy for the Lorenz 96 model: Fixed versus adaptive observation operators

    DOE PAGESBeta

    Stuart, Andrew M.; Shukla, Abhishek; Sanz-Alonso, Daniel; Law, K. J. H.

    2016-02-23

    In the context of filtering chaotic dynamical systems it is well-known that partial observations, if sufficiently informative, can be used to control the inherent uncertainty due to chaos. The purpose of this paper is to investigate, both theoretically and numerically, conditions on the observations of chaotic systems under which they can be accurately filtered. In particular, we highlight the advantage of adaptive observation operators over fixed ones. The Lorenz ’96 model is used to exemplify our findings. Here, we consider discrete-time and continuous-time observations in our theoretical developments. We prove that, for fixed observation operator, the 3DVAR filter can recovermore » the system state within a neighbourhood determined by the size of the observational noise. It is required that a sufficiently large proportion of the state vector is observed, and an explicit form for such sufficient fixed observation operator is given. Numerical experiments, where the data is incorporated by use of the 3DVAR and extended Kalman filters, suggest that less informative fixed operators than given by our theory can still lead to accurate signal reconstruction. Adaptive observation operators are then studied numerically; we show that, for carefully chosen adaptive observation operators, the proportion of the state vector that needs to be observed is drastically smaller than with a fixed observation operator. Indeed, we show that the number of state coordinates that need to be observed may even be significantly smaller than the total number of positive Lyapunov exponents of the underlying system.« less

  12. Adaptive Particle Filter for Nonparametric Estimation with Measurement Uncertainty in Wireless Sensor Networks.

    PubMed

    Li, Xiaofan; Zhao, Yubin; Zhang, Sha; Fan, Xiaopeng

    2016-01-01

    Particle filters (PFs) are widely used for nonlinear signal processing in wireless sensor networks (WSNs). However, the measurement uncertainty makes the WSN observations unreliable to the actual case and also degrades the estimation accuracy of the PFs. In addition to the algorithm design, few works focus on improving the likelihood calculation method, since it can be pre-assumed by a given distribution model. In this paper, we propose a novel PF method, which is based on a new likelihood fusion method for WSNs and can further improve the estimation performance. We firstly use a dynamic Gaussian model to describe the nonparametric features of the measurement uncertainty. Then, we propose a likelihood adaptation method that employs the prior information and a belief factor to reduce the measurement noise. The optimal belief factor is attained by deriving the minimum Kullback-Leibler divergence. The likelihood adaptation method can be integrated into any PFs, and we use our method to develop three versions of adaptive PFs for a target tracking system using wireless sensor network. The simulation and experimental results demonstrate that our likelihood adaptation method has greatly improved the estimation performance of PFs in a high noise environment. In addition, the adaptive PFs are highly adaptable to the environment without imposing computational complexity. PMID:27249002

  13. Adaptive Particle Filter for Nonparametric Estimation with Measurement Uncertainty in Wireless Sensor Networks

    PubMed Central

    Li, Xiaofan; Zhao, Yubin; Zhang, Sha; Fan, Xiaopeng

    2016-01-01

    Particle filters (PFs) are widely used for nonlinear signal processing in wireless sensor networks (WSNs). However, the measurement uncertainty makes the WSN observations unreliable to the actual case and also degrades the estimation accuracy of the PFs. In addition to the algorithm design, few works focus on improving the likelihood calculation method, since it can be pre-assumed by a given distribution model. In this paper, we propose a novel PF method, which is based on a new likelihood fusion method for WSNs and can further improve the estimation performance. We firstly use a dynamic Gaussian model to describe the nonparametric features of the measurement uncertainty. Then, we propose a likelihood adaptation method that employs the prior information and a belief factor to reduce the measurement noise. The optimal belief factor is attained by deriving the minimum Kullback–Leibler divergence. The likelihood adaptation method can be integrated into any PFs, and we use our method to develop three versions of adaptive PFs for a target tracking system using wireless sensor network. The simulation and experimental results demonstrate that our likelihood adaptation method has greatly improved the estimation performance of PFs in a high noise environment. In addition, the adaptive PFs are highly adaptable to the environment without imposing computational complexity. PMID:27249002

  14. Contrast enhancement in microscopy of human thyroid tumors by means of acousto-optic adaptive spatial filtering

    NASA Astrophysics Data System (ADS)

    Yushkov, Konstantin B.; Molchanov, Vladimir Y.; Belousov, Pavel V.; Abrosimov, Aleksander Y.

    2016-01-01

    We report a method for edge enhancement in the images of transparent samples using analog image processing in coherent light. The experimental technique is based on adaptive spatial filtering with an acousto-optic tunable filter in a telecentric optical system. We demonstrate processing of microscopic images of unstained and stained histological sections of human thyroid tumor with improved contrast.

  15. Adaptive Spatial Filtering of Interferometric Data Stack Oriented to Distributed Scatterers

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Xie, C.; Shao, Y.; Yuan, M.

    2013-07-01

    Standard interferometry poses a challenge in non-urban areas due to temporal and spatial decorrelation of the radar signal, where there is high signal noise. Techniques such as Small Baseline Subset Algorithm (SBAS) have been proposed to make use of multiple interferometric combinations to alleviate the problem. However, the interferograms used in SBAS are multilooked with a boxcar (rectangle) filter to reduce phase noise, resulting in a loss of resolution and signal superstition from different objects. In this paper, we proposed a modified adaptive spatial filtering algorithm for accurate estimation of interferogram and coherence without resolution loss even in rural areas, to better support the deformation monitoring with time series interferometric synthetic aperture radar (InSAR) technique. The implemented method identifies the statistically homogenous pixels in a neighbourhood based on the goodness-of-fit test, and then applies an adaptive spatial filtering of interferograms. Three statistical tests for the identification of distributed targets will be presented, applied to real data. PALSAR data of the yellow river delta in China is used for demonstrating the effectiveness of this algorithm in rural areas.

  16. Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters

    PubMed Central

    Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg; Fernández, Eduardo

    2010-01-01

    In this paper, the least-mean-squares (LMS) algorithm was used to eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications. This kind of accelerometer is designed to be easily mounted in hard to reach places on vehicles under test, and they usually feature ranges from 50 to 2,000 g (where is the gravitational acceleration, 9.81 m/s2) and frequency responses to 3,000 Hz or higher, with DC response, durable cables, reliable performance and relatively low cost. However, here we show that the response of the sensor under test had a lot of noise and we carried out the signal processing stage by using both conventional and optimal adaptive filtering. Usually, designers have to build their specific analog and digital signal processing circuits, and this fact increases considerably the cost of the entire sensor system and the results are not always satisfactory, because the relevant signal is sometimes buried in a broad-band noise background where the unwanted information and the relevant signal sometimes share a very similar frequency band. Thus, in order to deal with this problem, here we used the LMS adaptive filtering algorithm and compare it with others based on the kind of filters that are typically used for automotive applications. The experimental results are satisfactory. PMID:22315542

  17. Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

    NASA Astrophysics Data System (ADS)

    Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi

    2013-03-01

    Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

  18. High performance 3D adaptive filtering for DSP based portable medical imaging systems

    NASA Astrophysics Data System (ADS)

    Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

    2015-03-01

    Portable medical imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. Despite their constraints on power, size and cost, portable imaging devices must still deliver high quality images. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often cannot be run with sufficient performance on a portable platform. In recent years, advanced multicore digital signal processors (DSP) have been developed that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms on a portable platform. In this study, the performance of a 3D adaptive filtering algorithm on a DSP is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec with an Ultrasound 3D probe. Relative performance and power is addressed between a reference PC (Quad Core CPU) and a TMS320C6678 DSP from Texas Instruments.

  19. Chip design of a 5.8-GHz fractional-N frequency synthesizer with a tunable Gm-C loop filter

    NASA Astrophysics Data System (ADS)

    Huang, Jhin-Fang; Liu, Ron-Yi; Lai, Wen-Cheng; Shin, Chun-Wei; Hsu, Chien-Ming

    2012-08-01

    This paper proposes a novel Gm-C loop filter instead of a conventional passive loop filter used in a phase-locked loop. The innovative advantage of the proposed architecture is tunable loop filter bandwidth and hence the process variations of passive elements of resistance R and capacitance C can be overcome and the chip area is greatly reduced. Furthermore, the MASH 1-1-1 sigma-delta (ΣΔ) modulator is adopted for performing the fractional division number and hence improves the phase noise as well. Measured results show that the locked phase noise is -114.1 dBc/Hz with lower Gm-C bandwidth and -111.7 dBm/C with higher Gm-C bandwidth at 1 MHz offset from carrier of 5.68 GHz. Including pads and built-in Gm-C filter, the chip area of the proposed frequency synthesizer is 1.06 mm2. The output power is -8.69 dBm at 5.68 GHz and consumes 56 mW with an off-chip buffer from 1.8-V supply voltage.

  20. A robust state-of-charge estimator for multiple types of lithium-ion batteries using adaptive extended Kalman filter

    NASA Astrophysics Data System (ADS)

    Xiong, Rui; Gong, Xianzhi; Mi, Chunting Chris; Sun, Fengchun

    2013-12-01

    This paper presents a novel data-driven based approach for the estimation of the state of charge (SoC) of multiple types of lithium ion battery (LiB) cells with adaptive extended Kalman filter (AEKF). A modified second-order RC network based battery model is employed for the state estimation. Based on the battery model and experimental data, the SoC variation per mV voltage for different types of battery chemistry is analyzed and the parameters are identified. The AEKF algorithm is then employed to achieve accurate data-driven based SoC estimation, and the multi-parameter, closed loop feedback system is used to achieve robustness. The accuracy and convergence of the proposed approach is analyzed for different types of LiB cells, including convergence behavior of the model with a large initial SoC error. The results show that the proposed approach has good accuracy for different types of LiB cells, especially for C/LFP LiB cell that has a flat open circuit voltage (OCV) curve. The experimental results show good agreement with the estimation results with maximum error being less than 3%.

  1. Using high-order methods on adaptively refined block-structured meshes - discretizations, interpolations, and filters.

    SciTech Connect

    Ray, Jaideep; Lefantzi, Sophia; Najm, Habib N.; Kennedy, Christopher A.

    2006-01-01

    Block-structured adaptively refined meshes (SAMR) strive for efficient resolution of partial differential equations (PDEs) solved on large computational domains by clustering mesh points only where required by large gradients. Previous work has indicated that fourth-order convergence can be achieved on such meshes by using a suitable combination of high-order discretizations, interpolations, and filters and can deliver significant computational savings over conventional second-order methods at engineering error tolerances. In this paper, we explore the interactions between the errors introduced by discretizations, interpolations and filters. We develop general expressions for high-order discretizations, interpolations, and filters, in multiple dimensions, using a Fourier approach, facilitating the high-order SAMR implementation. We derive a formulation for the necessary interpolation order for given discretization and derivative orders. We also illustrate this order relationship empirically using one and two-dimensional model problems on refined meshes. We study the observed increase in accuracy with increasing interpolation order. We also examine the empirically observed order of convergence, as the effective resolution of the mesh is increased by successively adding levels of refinement, with different orders of discretization, interpolation, or filtering.

  2. A novel spatially adaptive guide-filter total variation (SAGFTV) regularization for image restoration

    NASA Astrophysics Data System (ADS)

    Fang, Hao; Li, Qian; Huang, Zhenghua

    2015-12-01

    Denoising algorithms based on gradient dependent energy functionals, such as Perona-Malik, total variation and adaptive total variation denoising, modify images towards piecewise constant functions. Although edge sharpness and location is well preserved, important information, encoded in image features like textures or certain details, is often compromised in the process of denoising. In this paper, We propose a novel Spatially Adaptive Guide-Filtering Total Variation (SAGFTV) regularization with image restoration algorithm for denoising images. The guide-filter is extended to the variational formulations of imaging problem, and the spatially adaptive operator can easily distinguish flat areas from texture areas. Our simulating experiments show the improvement of peak signal noise ratio (PSNR), root mean square error (RMSE) and structure similarity increment measurement (SSIM) over other prior algorithms. The results of both simulating and practical experiments are more appealing visually. This type of processing can be used for a variety of tasks in PDE-based image processing and computer vision, and is stable and meaningful from a mathematical viewpoint.

  3. Time synchronization over the Internet using an adaptive frequency-locked loop.

    PubMed

    Levine, J

    1999-01-01

    This paper describes the operation of an algorithm for synchronizing the time of computers using messages transmitted over packet-switched networks such as the Internet. The algorithm configures itself to realize any specified performance level at minimum cost (measured in computer cycles or network bandwidth). If the highest possible accuracy is requested, the performance will be limited by the larger of the instability of the local clock oscillator or the noise in the measurement process between the client and the server; uncertainties of about 8 ms RMS have been obtained using standard workstations and average network connections. Lower accuracy can be realized at substantially lower cost because the cost varies approximately as the inverse of the accuracy squared over a wide range of these parameters. The algorithm makes better use of scarce network bandwidth than previous methods. This improvement is realized by using a pure frequency-locked loop (rather than mixed frequency/phase locking algorithms currently proposed for the NTP) with unequal spacing between calibration cycles. The result is a cleaner separation between network noise and clock noise, which is especially important when the highest possible accuracy is desired. In addition, the algorithm is an improvement over the pure-FLL "Interlock" algorithm described previously because it is self configuring. In addition to supporting an explicit trade-off between cost and accuracy, the algorithm provides better performance than previous methods because it is better able to adapt itself to fluctuations in the asymmetry of the network delay. PMID:18238493

  4. Multichannel spike detector with an adaptive threshold based on a Sigma-delta control loop.

    PubMed

    Gagnon-Turcotte, G; Gosselin, B

    2015-08-01

    In this paper, we present a digital spike detector using an adaptive threshold which is suitable for real time processing of 32 electrophysiological channels in parallel. Such a new scheme is based on a Sigma-delta control loop that precisely estimates the standard deviation of the amplitude of the noise of the input signal to optimize the detection rate. Additionally, it is not dependent on the amplitude of the input signal thanks to a robust algorithm. The spike detector is implemented inside a Spartan-6 FPGA using low resources, only FPGA basic logic blocks, and is using a low clock frequency under 6 MHz for minimal power consumption. We present a comparison showing that the proposed system can compete with a dedicated off-line spike detection software. The whole system achieves up to 100% of true positive detection rate for SNRs down to 5 dB while achieving 62.3% of true positive detection rate for an SNR as low as -2 dB at a 150 AP/s firing rate. PMID:26737934

  5. Application of Open Loop H-Adaptation to an Unstructured Grid Tidal Flat Model

    NASA Astrophysics Data System (ADS)

    Cowles, G. W.

    2008-12-01

    The complex topology of tidal flats presents a challenge to coastal ocean models. Recently, several models have been developed employing unstructured grids, which can provide the flexibility in mesh resolution required to resolve the complex bathymetry and coastline. However, the distribution of element size in the initial mesh can be somewhat arbitrary, and is in general the product of the operator tailoring the resolution to the underlying bathymetry and regions of interest. In this work, the flow solution from an idealized tidal flat application is used to drive an open loop h-adaptation of the mesh. The model used for this work is the Finite Volume Coastal Ocean Model (FVCOM), an open source, terrain following model. A background length scale distribution derived from model output is used to generate a new initial mesh for the model run, thus defining an iteration of the procedure. Several metrics for computing the background length scale will be examined. These include direct estimation of spatial discretization error using Richardson's extrapolation from a sequence of meshes as well as heuristics derived from gradients in the primitive variables. Examination of grid independence, computational efficiency, and performance of the scheme for idealized tidal flats with inclusion of morphodynamics will be discussed.

  6. Closed-loop optical stabilization and digital image registration in adaptive optics scanning light ophthalmoscopy

    PubMed Central

    Yang, Qiang; Zhang, Jie; Nozato, Koji; Saito, Kenichi; Williams, David R.; Roorda, Austin; Rossi, Ethan A.

    2014-01-01

    Eye motion is a major impediment to the efficient acquisition of high resolution retinal images with the adaptive optics (AO) scanning light ophthalmoscope (AOSLO). Here we demonstrate a solution to this problem by implementing both optical stabilization and digital image registration in an AOSLO. We replaced the slow scanning mirror with a two-axis tip/tilt mirror for the dual functions of slow scanning and optical stabilization. Closed-loop optical stabilization reduced the amplitude of eye-movement related-image motion by a factor of 10–15. The residual RMS error after optical stabilization alone was on the order of the size of foveal cones: ~1.66–2.56 μm or ~0.34–0.53 arcmin with typical fixational eye motion for normal observers. The full implementation, with real-time digital image registration, corrected the residual eye motion after optical stabilization with an accuracy of ~0.20–0.25 μm or ~0.04–0.05 arcmin RMS, which to our knowledge is more accurate than any method previously reported. PMID:25401030

  7. Fuzzy adaptive strong tracking scaled unscented Kalman filter for initial alignment of large misalignment angles.

    PubMed

    Li, Jing; Song, Ningfang; Yang, Gongliu; Jiang, Rui

    2016-07-01

    In the initial alignment process of strapdown inertial navigation system (SINS), large misalignment angles always bring nonlinear problem, which can usually be processed using the scaled unscented Kalman filter (SUKF). In this paper, the problem of large misalignment angles in SINS alignment is further investigated, and the strong tracking scaled unscented Kalman filter (STSUKF) is proposed with fixed parameters to improve convergence speed, while these parameters are artificially constructed and uncertain in real application. To further improve the alignment stability and reduce the parameters selection, this paper proposes a fuzzy adaptive strategy combined with STSUKF (FUZZY-STSUKF). As a result, initial alignment scheme of large misalignment angles based on FUZZY-STSUKF is designed and verified by simulations and turntable experiment. The results show that the scheme improves the accuracy and convergence speed of SINS initial alignment compared with those based on SUKF and STSUKF. PMID:27475606

  8. Fuzzy adaptive strong tracking scaled unscented Kalman filter for initial alignment of large misalignment angles

    NASA Astrophysics Data System (ADS)

    Li, Jing; Song, Ningfang; Yang, Gongliu; Jiang, Rui

    2016-07-01

    In the initial alignment process of strapdown inertial navigation system (SINS), large misalignment angles always bring nonlinear problem, which can usually be processed using the scaled unscented Kalman filter (SUKF). In this paper, the problem of large misalignment angles in SINS alignment is further investigated, and the strong tracking scaled unscented Kalman filter (STSUKF) is proposed with fixed parameters to improve convergence speed, while these parameters are artificially constructed and uncertain in real application. To further improve the alignment stability and reduce the parameters selection, this paper proposes a fuzzy adaptive strategy combined with STSUKF (FUZZY-STSUKF). As a result, initial alignment scheme of large misalignment angles based on FUZZY-STSUKF is designed and verified by simulations and turntable experiment. The results show that the scheme improves the accuracy and convergence speed of SINS initial alignment compared with those based on SUKF and STSUKF.

  9. Automatic artifact suppression in simultaneous tDCS-EEG using adaptive filtering.

    PubMed

    Mancini, Matteo; Pellicciari, Maria Concetta; Brignani, Debora; Mauri, Piercarlo; De Marchis, Cristiano; Miniussi, Carlo; Conforto, Silvia

    2015-08-01

    Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that can be used in cognitive and clinical protocols in order to modulate neural activity. Although some macro effects are known, the underlying mechanisms are still not clear. tDCS in combination with electroencephalography (EEG) could help to understand these mechanisms from a neural point of view. However, simultaneous tDCS-EEG still remains challenging because of the artifacts that affect the recorded signals. In this paper, an automated artifact cancellation method based on adaptive filtering is proposed. Using independent component analysis (ICA), the artifacts were characterized using data from both a phantom and a group of healthy subjects. The resulting filter can successfully remove tDCS-related artifacts during anodal and cathodal stimulations. PMID:26736856

  10. A DSP-Based Beam Current Monitoring System for Machine Protection Using Adaptive Filtering

    SciTech Connect

    J. Musson; H. Dong; R. Flood; C. Hovater; J. Hereford

    2001-06-01

    The CEBAF accelerator at Jefferson Lab is currently using an analog beam current monitoring (BCM) system for its machine protection system (MPS), which has a loss accuracy of 2 micro-amps. Recent burn-through simulations predict catastrophic beam line component failures below 1 micro-amp of loss, resulting in a blind spot for the MPS. Revised MPS requirements target an ultimate beam loss accuracy of 250 nA. A new beam current monitoring system has been developed which utilizes modern digital receiver technology and digital signal processing concepts. The receiver employs a direct-digital down converter integrated circuit, mated with a Jefferson Lab digital signal processor VME card. Adaptive filtering is used to take advantage of current-dependent burn-through rates. Benefits of such a system include elimination of DC offsets, generic algorithm development, extensive filter options, and interfaces to UNIX-based control systems.

  11. Cardiac fiber tracking using adaptive particle filtering based on tensor rotation invariant in MRI

    NASA Astrophysics Data System (ADS)

    Kong, Fanhui; Liu, Wanyu; Magnin, Isabelle E.; Zhu, Yuemin

    2016-03-01

    Diffusion magnetic resonance imaging (dMRI) is a non-invasive method currently available for cardiac fiber tracking. However, accurate and efficient cardiac fiber tracking is still a challenge. This paper presents a probabilistic cardiac fiber tracking method based on particle filtering. In this framework, an adaptive sampling technique is presented to describe the posterior distribution of fiber orientations by adjusting the number and status of particles according to the fractional anisotropy of diffusion. An observation model is then proposed to update the weight of particles by rotating diffusion tensor from the primary eigenvector to a given fiber orientation while keeping the shape of the tensor invariant. The results on human cardiac dMRI show that the proposed method is robust to noise and outperforms conventional streamline and particle filtering techniques.

  12. A 2-D orientation-adaptive prediction filter in lifting structures for image coding.

    PubMed

    Gerek, Omer N; Cetin, A Enis

    2006-01-01

    Lifting-style implementations of wavelets are widely used in image coders. A two-dimensional (2-D) edge adaptive lifting structure, which is similar to Daubechies 5/3 wavelet, is presented. The 2-D prediction filter predicts the value of the next polyphase component according to an edge orientation estimator of the image. Consequently, the prediction domain is allowed to rotate +/-45 degrees in regions with diagonal gradient. The gradient estimator is computationally inexpensive with additional costs of only six subtractions per lifting instruction, and no multiplications are required. PMID:16435541

  13. Evaluation of an adaptive filtering algorithm for CT cardiac imaging with EKG modulated tube current

    NASA Astrophysics Data System (ADS)

    Li, Jianying; Hsieh, Jiang; Mohr, Kelly; Okerlund, Darin

    2005-04-01

    We have developed an adaptive filtering algorithm for cardiac CT scans with EKG-modulated tube current to optimize resolution and noise for different cardiac phases and to provide safety net for cases where end-systole phase is used for coronary imaging. This algorithm has been evaluated using patient cardiac CT scans where lower tube currents are used for the systolic phases. In this paper, we present the evaluation results. The results demonstrated that with the use of the proposed algorithm, we could improve image quality for all cardiac phases, while providing greater noise and streak artifact reduction for systole phases where lower CT dose were used.

  14. Impulse noise removal using 1-D switching median filter with adaptive scanning order based on structural context of image

    NASA Astrophysics Data System (ADS)

    Koga, Takanori; Suetake, Noriaki

    2015-02-01

    This paper describes the detail-preserving impulse noise removal performance of a one-dimensional (1-D) switching median filter (SMF) applied along an adaptive space-filling curve. Usually, a SMF with a two-dimensional (2-D) filter window is widely used for impulse noise removal while still preserving detailed parts in an input image. However, the noise detector of the 2-D filter does not always distinguish between the original pixels and the noise-corrupted ones perfectly. In particular, pixels constituting thin lines in an input image tend to be incorrectly detected as noise-corrupted pixels, and such pixels are filtered regardless of the necessity of the filtering. To cope with this problem, we propose a new impulse noise removal method based on a 1-D SMF and a space-filling curve which is adaptively drawn using a minimum spanning tree reflecting structural context of an input image.

  15. Adaptive Fuzzy Hysteresis Band Current Controller for Four-Wire Shunt Active Filter

    NASA Astrophysics Data System (ADS)

    Hamoudi, F.; Chaghi, A.; Amimeur, H.; Merabet, E.

    2008-06-01

    This paper presents an adaptive fuzzy hysteresis band current controller for four-wire shunt active power filters to eliminate harmonics and to compensate reactive power in distribution systems in order to keep currents at the point of common coupling sinusoidal and in phase with the corresponding voltage and the cancel neutral current. The conventional hysteresis band known for its robustness and its advantage in current controlled applications is adapted with a fuzzy logic controller to change the bandwidth according to the operating point in order to keep the frequency modulation at tolerable limits. The algorithm used to identify the reference currents is based on the synchronous reference frame theory (dqγ). Finally, simulation results using Matlab/Simulink are given to validate the proposed control.

  16. A stable multi-wavelength PM-EDF laser based on a nonlinear amplifying loop mirror and a TCF comb filter

    NASA Astrophysics Data System (ADS)

    Zou, Hui; Lou, Shuqin; Su, Wei; Han, Bolin

    2014-01-01

    A stable multi-wavelength polarization-maintaining erbium-doped fiber (PM-EDF) ring cavity laser employing a twin-core fiber (TCF) comb filter and a nonlinear amplifying loop mirror (NALM) is proposed and demonstrated. By appropriately adjusting the polarization controllers, the NALM as an amplitude equalizer can effectively reduce the mode competition caused by the homogeneous broadening gain medium in the PM-EDF. Under 150 mW pump power, up to 26 wavelength outputs within a 3 dB bandwidth are achieved and their signal-to-noise ratio (SNR) is 39.5 dB. Besides, the TCF comb filter is experimentally fabricated using a length of 0.78 m TCF spliced between two segments of the single-mode fiber. The transmission spectra of the filter in experimental measurements are in accord with the results of theoretical analysis, and its wavelength spacing is 0.29 nm. Meanwhile, the power fluctuation and wavelength shift are within 0.1 dB and 0.02 nm, respectively. The experimental results indicate that the proposed multi-wavelength fiber laser performs with high stability at room temperature. In addition, the multi-wavelength laser with the TCF comb filter can offer more wavelengths in a 3 dB spectral range and higher SNR than one using a Sagnac loop filter, and the length of the filter is also reduced by more than six times.

  17. Wavefront response matrix for closed-loop adaptive optics system based on non-modulation pyramid wavefront sensor

    NASA Astrophysics Data System (ADS)

    Wang, Jianxin; Bai, Fuzhong; Ning, Yu; Li, Fei; Jiang, Wenhan

    2012-06-01

    Pyramid wavefront sensor (PWFS) is a kind of wavefront sensor with high spatial resolution and high energy utilization. In this paper an adaptive optics system with PWFS as wavefront sensor and liquid-crystal spatial light modulator (LC-SLM) as wavefront corrector is built in the laboratory. The wavefront response matrix is a key element in the close-loop operation. It can be obtained by measuring the real response to given aberrations, which is easily contaminated by noise and influenced by the inherent aberration in the optical system. A kind of analytic solution of response matrix is proposed, with which numerical simulation and experiment are also implemented to verify the performance of closed-loop correction of static aberration based on linear reconstruction theory. Results show that this AO system with the proposed matrix can work steadily in closed-loop operation.

  18. AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.

    PubMed

    Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

    2015-01-01

    An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665

  19. AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal

    PubMed Central

    Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

    2015-01-01

    An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal. PMID:26512665

  20. Adaptive Bloom Filter: A Space-Efficient Counting Algorithm for Unpredictable Network Traffic

    NASA Astrophysics Data System (ADS)

    Matsumoto, Yoshihide; Hazeyama, Hiroaki; Kadobayashi, Youki

    The Bloom Filter (BF), a space-and-time-efficient hashcoding method, is used as one of the fundamental modules in several network processing algorithms and applications such as route lookups, cache hits, packet classification, per-flow state management or network monitoring. BF is a simple space-efficient randomized data structure used to represent a data set in order to support membership queries. However, BF generates false positives, and cannot count the number of distinct elements. A counting Bloom Filter (CBF) can count the number of distinct elements, but CBF needs more space than BF. We propose an alternative data structure of CBF, and we called this structure an Adaptive Bloom Filter (ABF). Although ABF uses the same-sized bit-vector used in BF, the number of hash functions employed by ABF is dynamically changed to record the number of appearances of a each key element. Considering the hash collisions, the multiplicity of a each key element on ABF can be estimated from the number of hash functions used to decode the membership of the each key element. Although ABF can realize the same functionality as CBF, ABF requires the same memory size as BF. We describe the construction of ABF and IABF (Improved ABF), and provide a mathematical analysis and simulation using Zipf's distribution. Finally, we show that ABF can be used for an unpredictable data set such as real network traffic.

  1. A characterization of a single-trial adaptive filter and its implementation in the frequency domain.

    PubMed

    Arpaia, J P; Isenhart, R; Sandman, C A

    1989-10-01

    A single-trial adaptive filter (SAF) was implemented in the frequency domain (FDAF) by using the Fast Fourier Transform. The FDAF is significantly more efficient than the SAF. In the data presented the FDAF ran approximately 2 times faster than the SAF. For time series containing larger numbers of data points (n) the efficiency of the calculation will increase on the order of N/Ln(N). The FDAF was tested under a variety of conditions to determine the limits of its usefulness. Pre-filtering the data was found to be necessary to prevent the FDAF from lining up on high frequency activity not related to the signal. The importance of minimizing the amount of low frequency noise was emphasized since it adversely affected the performance of the FDAF and was difficult to filter. The single-trial latencies predicted by the FDAF were much more sensitive to increasing noise than the final wave form. In the absence of excessive low frequency noise a negative exponential relationship was found between the mean error in latency prediction and the SNR estimate. Since the SAF technique is also used to determine signal latency in single sweep data the SNR estimate can be a useful test to determine if the FDAF is locating the signal correctly or merely amplifying chance regularities in noisy data. PMID:2477222

  2. Echo motion imaging with adaptive clutter filter for assessment of cardiac blood flow

    NASA Astrophysics Data System (ADS)

    Takahashi, Hiroki; Hasegawa, Hideyuki; Kanai, Hiroshi

    2015-07-01

    Visualization of the vortex blood flow in the cardiac chamber is a potential diagnostic tool for the evaluation of cardiac function. In the present study, a method for automatic selection of the desirable cutoff frequency of a moving target indicator filter, namely, a clutter filter, was proposed in order to visualize complex blood flows by the ultrahigh-frame-rate imaging of echoes from blood particles while suppressing clutter echoes. In this method, the cutoff frequency was adaptively changed as a function of the velocity of the heart wall (clutter source) in each frame. The feasibility of the proposed method was examined through the measurement of a healthy volunteer using parallel receive beamforming with a single transmission of a non-steered diverging beam. Using the moving target indicator filter as above with the cutoff frequency determined by the proposed method, the vortex-like blood flow in the cardiac chamber was visualized as movements of echoes from blood particles at a very high frame rate of 6024 Hz while suppressing clutter echoes.

  3. Efficiency and adaptability of the benthic methane filter at Quepos Slide cold seeps, offshore Costa Rica

    NASA Astrophysics Data System (ADS)

    Steeb, P.; Krause, S.; Linke, P.; Hensen, C.; Dale, A. W.; Nuzzo, M.; Treude, T.

    2014-11-01

    Large amounts of methane are delivered by fluids through the erosive forearc of the convergent margin offshore Costa Rica and lead to the formation of cold seeps at the sediment surface. Besides mud extrusion, numerous cold seeps are created by landslides induced by seamount subduction or fluid migration along major faults. Most of the dissolved methane reaching the seafloor at cold seeps is oxidized within the benthic microbial methane filter by anaerobic oxidation of methane (AOM). Measurements of AOM and sulfate reduction as well as numerical modeling of porewater profiles revealed a highly active and efficient benthic methane filter at Quepos Slide site; a landslide on the continental slope between the Nicoya and Osa Peninsula. Integrated areal rates of AOM ranged from 12.9 ± 6.0 to 45.2 ± 11.5 mmol m-2 d-1, with only 1 to 2.5% of the upward methane flux being released into the water column. Additionally, two parallel sediment cores from Quepos Slide were used for in vitro experiments in a recently developed Sediment-F low-Through (SLOT) system to simulate an increased fluid and methane flux from the bottom of the sediment core. The benthic methane filter revealed a high adaptability whereby the methane oxidation efficiency responded to the increased fluid flow within 150-170 days. To our knowledge, this study provides the first estimation of the natural biogeochemical response of seep sediments to changes in fluid flow.

  4. Array model interpolation and subband iterative adaptive filters applied to beamforming-based acoustic echo cancellation.

    PubMed

    Bai, Mingsian R; Chi, Li-Wen; Liang, Li-Huang; Lo, Yi-Yang

    2016-02-01

    In this paper, an evolutionary exposition is given in regard to the enhancing strategies for acoustic echo cancellers (AECs). A fixed beamformer (FBF) is utilized to focus on the near-end speaker while suppressing the echo from the far end. In reality, the array steering vector could differ considerably from the ideal freefield plane wave model. Therefore, an experimental procedure is developed to interpolate a practical array model from the measured frequency responses. Subband (SB) filtering with polyphase implementation is exploited to accelerate the cancellation process. Generalized sidelobe canceller (GSC) composed of an FBF and an adaptive blocking module is combined with AEC to maximize cancellation performance. Another enhancement is an internal iteration (IIT) procedure that enables efficient convergence in the adaptive SB filters within a sample time. Objective tests in terms of echo return loss enhancement (ERLE), perceptual evaluation of speech quality (PESQ), word recognition rate for automatic speech recognition (ASR), and subjective listening tests are conducted to validate the proposed AEC approaches. The results show that the GSC-SB-AEC-IIT approach has attained the highest ERLE without speech quality degradation, even in double-talk scenarios. PMID:26936567

  5. Adaptive Kalman filter based state of charge estimation algorithm for lithium-ion battery

    NASA Astrophysics Data System (ADS)

    Zheng, Hong; Liu, Xu; Wei, Min

    2015-09-01

    In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded. Project supported by the National Natural Science Foundation of China (Grant Nos. 61004048 and 61201010).

  6. Reduction of EEG artifacts in simultaneous EEG-fMRI: Reference layer adaptive filtering (RLAF).

    PubMed

    Steyrl, David; Patz, Franz; Krausz, Gunther; Edlinger, Günter; Müller-Putz, Gernot R

    2015-08-01

    Although simultaneous measurement of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is one of the most valuable methods for studying human brain activity non-invasively, it remains challenging to measure high quality EEG inside the MRI scanner. Recently, a new approach for minimizing residual MRI scanner artifacts in the EEG was presented: reference layer artifact subtraction (RLAS). Here, reference electrodes capture only the artifacts, which are subsequently subtracted from the measurement electrodes. With the present work we demonstrate that replacing the subtraction by adaptive filtering statistically significantly outperforms RLAS. Reference layer adaptive filtering (RLAF) attenuates the average artifact root-mean-square (RMS) voltage of the passive MRI scanner to 0.7 μV (-14.4 dB). RLAS achieves 0.78 μV (-13.5 dB). The combination of average artifact subtraction (AAS) and RLAF reduces the residual average gradient artifact RMS voltage to 2.3 μV (-49.2 dB). AAS alone achieves 5.7 μV (-39.0 dB). All measurements were conducted with an MRI phantom, as the reference layer cap available to us was a prototype. PMID:26737122

  7. Small Sample Properties of an Adaptive Filter with Application to Low Volume Statistical Process Control

    SciTech Connect

    CROWDER, STEPHEN V.

    1999-09-01

    In many manufacturing environments such as the nuclear weapons complex, emphasis has shifted from the regular production and delivery of large orders to infrequent small orders. However, the challenge to maintain the same high quality and reliability standards while building much smaller lot sizes remains. To meet this challenge, specific areas need more attention, including fast and on-target process start-up, low volume statistical process control, process characterization with small experiments, and estimating reliability given few actual performance tests of the product. In this paper we address the issue of low volume statistical process control. We investigate an adaptive filtering approach to process monitoring with a relatively short time series of autocorrelated data. The emphasis is on estimation and minimization of mean squared error rather than the traditional hypothesis testing and run length analyses associated with process control charting. We develop an adaptive filtering technique that assumes initial process parameters are unknown, and updates the parameters as more data become available. Using simulation techniques, we study the data requirements (the length of a time series of autocorrelated data) necessary to adequately estimate process parameters. We show that far fewer data values are needed than is typically recommended for process control applications. We also demonstrate the techniques with a case study from the nuclear weapons manufacturing complex.

  8. Small sample properties of an adaptive filter with application to low volume statistical process control

    SciTech Connect

    Crowder, S.V.; Eshleman, L.

    1998-08-01

    In many manufacturing environments such as the nuclear weapons complex, emphasis has shifted from the regular production and delivery of large orders to infrequent small orders. However, the challenge to maintain the same high quality and reliability standards white building much smaller lot sizes remains. To meet this challenge, specific areas need more attention, including fast and on-target process start-up, low volume statistical process control, process characterization with small experiments, and estimating reliability given few actual performance tests of the product. In this paper the authors address the issue of low volume statistical process control. They investigate an adaptive filtering approach to process monitoring with a relatively short time series of autocorrelated data. The emphasis is on estimation and minimization of mean squared error rather than the traditional hypothesis testing and run length analyses associated with process control charting. The authors develop an adaptive filtering technique that assumes initial process parameters are unknown, and updates the parameters as more data become available. Using simulation techniques, they study the data requirements (the length of a time series of autocorrelated data) necessary to adequately estimate process parameters. They show that far fewer data values are needed than is typically recommended for process control applications. And they demonstrate the techniques with a case study from the nuclear weapons manufacturing complex.

  9. Development of Shunt-Type Three-Phase Active Power Filter with Novel Adaptive Control for Wind Generators

    PubMed Central

    Chen, Ming-Hung

    2015-01-01

    This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC-link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low-pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low-pass filter and is more economical because of its short computation time compared with other types of adaptive filters. PMID:26451391

  10. Development of Shunt-Type Three-Phase Active Power Filter with Novel Adaptive Control for Wind Generators.

    PubMed

    Chen, Ming-Hung

    2015-01-01

    This paper proposes a new adaptive filter for wind generators that combines instantaneous reactive power compensation technology and current prediction controller, and therefore this system is characterized by low harmonic distortion, high power factor, and small DC-link voltage variations during load disturbances. The performance of the system was first simulated using MATLAB/Simulink, and the possibility of an adaptive digital low-pass filter eliminating current harmonics was confirmed in steady and transient states. Subsequently, a digital signal processor was used to implement an active power filter. The experimental results indicate, that for the rated operation of 2 kVA, the system has a total harmonic distortion of current less than 5.0% and a power factor of 1.0 on the utility side. Thus, the transient performance of the adaptive filter is superior to the traditional digital low-pass filter and is more economical because of its short computation time compared with other types of adaptive filters. PMID:26451391

  11. Instructional Modifications, Adaptations, and Accommodations of Coteachers Who Loop: A Descriptive Case Study

    ERIC Educational Resources Information Center

    Nevin, Ann I.; Cramer, Elizabeth; Voigt, Jorine; Salazar, Liliana

    2008-01-01

    When teachers move to the next grade with their students, they are sometimes referred to as teachers who loop with the children. In this descriptive case study, the authors describe the experiences of two teachers who collaborate with others as they move with a class of students from third to fourth grade (i.e., looping). The classroom context,…

  12. Adaptive anisotropic gaussian filtering to reduce acquisition time in cardiac diffusion tensor imaging.

    PubMed

    Mazumder, Ria; Clymer, Bradley D; Mo, Xiaokui; White, Richard D; Kolipaka, Arunark

    2016-06-01

    Diffusion tensor imaging (DTI) is used to quantify myocardial fiber orientation based on helical angles (HA). Accurate HA measurements require multiple excitations (NEX) and/or several diffusion encoding directions (DED). However, increasing NEX and/or DED increases acquisition time (TA). Therefore, in this study, we propose to reduce TA by implementing a 3D adaptive anisotropic Gaussian filter (AAGF) on the DTI data acquired from ex-vivo healthy and infarcted porcine hearts. DTI was performed on ex-vivo hearts [9-healthy, 3-myocardial infarction (MI)] with several combinations of DED and NEX. AAGF, mean (AVF) and median filters (MF) were applied on the primary eigenvectors of the diffusion tensor prior to HA estimation. The performance of AAGF was compared against AVF and MF. Root mean square error (RMSE), concordance correlation-coefficients and Bland-Altman's technique was used to determine optimal combination of DED and NEX that generated the best HA maps in the least possible TA. Lastly, the effect of implementing AAGF on the infarcted porcine hearts was also investigated. RMSE in HA estimation for AAGF was lower compared to AVF or MF. Post-filtering (AAGF) fewer DED and NEX were required to achieve HA maps with similar integrity as those obtained from higher NEX and/or DED. Pathological alterations caused in HA orientation in the MI model were preserved post-filtering (AAGF). Our results demonstrate that AAGF reduces TA without affecting the integrity of the myocardial microstructure. PMID:26843150

  13. Improvement in Accuracy of Ultrasonic Measurement of Transient Change in Viscoelasticity of Radial Arterial Wall Due to Flow-Mediated Dilation by Adaptive Low-Pass Filtering

    NASA Astrophysics Data System (ADS)

    Ikeshita, Kazuki; Hasegawa, Hideyuki; Kanai, Hiroshi

    2012-07-01

    In our previous study, the stress-strain relationship of the radial arterial wall was measured and the viscoelasticity of the intima-media region was estimated from the stress-strain relationship. Furthermore, the transient change in viscoelasticity due to flow-mediated dilation (FMD) was estimated by the automated detection of wall boundaries. In the present study, the strain rate was adaptively filtered to improve the accuracy of viscoelasticity estimation by decreasing the high-frequency noise. Additionally, in a basic experiment, this method was validated using a silicone tube (simulating artery). In the basic experiment, the elasticity was estimated with a mean error of 1.2%. The elasticity measured at each beam position was highly reproducible among measurements, whereas there was a slight variation in measured elasticity among beams. Consequently, in in vivo measurements, the normalized mean square error (MSE) was clearly decreased. Additionally, the stress-strain relationship of the radial arterial wall was obtained and the viscoelasticity was estimated accurately. The inner small loop, which corresponds to the negative pressure wave caused by the closure of the aortic valve, can be observed using the adaptive low-pass filtering (LPF). Moreover, the transient changes in these parameters were similar to those in the previous study. These results show the potential of the proposed method for the thorough analysis of the transient change in viscoelasticity due to FMD.

  14. Rician noise reduction in magnetic resonance images using adaptive non-local mean and guided image filtering

    NASA Astrophysics Data System (ADS)

    Mahmood, Muhammad Tariq; Chu, Yeon-Ho; Choi, Young-Kyu

    2016-05-01

    This paper proposes a Rician noise reduction method for magnetic resonance (MR) images. The proposed method is based on adaptive non-local mean and guided image filtering techniques. In the first phase, a guidance image is obtained from the noisy image through an adaptive non-local mean filter. Sobel operators are applied to compute the strength of edges which is further used to control the spread of the kernel in non-local mean filtering. In the second phase, the noisy and the guidance images are provided to the guided image filter as input to restore the noise-free image. The improved performance of the proposed method is investigated using the simulated and real data sets of MR images. Its performance is also compared with the previously proposed state-of-the art methods. Comparative analysis demonstrates the superiority of the proposed scheme over the existing approaches.

  15. Rician noise reduction in magnetic resonance images using adaptive non-local mean and guided image filtering

    NASA Astrophysics Data System (ADS)

    Mahmood, Muhammad Tariq; Chu, Yeon-Ho; Choi, Young-Kyu

    2016-06-01

    This paper proposes a Rician noise reduction method for magnetic resonance (MR) images. The proposed method is based on adaptive non-local mean and guided image filtering techniques. In the first phase, a guidance image is obtained from the noisy image through an adaptive non-local mean filter. Sobel operators are applied to compute the strength of edges which is further used to control the spread of the kernel in non-local mean filtering. In the second phase, the noisy and the guidance images are provided to the guided image filter as input to restore the noise-free image. The improved performance of the proposed method is investigated using the simulated and real data sets of MR images. Its performance is also compared with the previously proposed state-of-the art methods. Comparative analysis demonstrates the superiority of the proposed scheme over the existing approaches.

  16. Loop Mediated Isothermal Amplification (LAMP) Accurately Detects Malaria DNA from Filter Paper Blood Samples of Low Density Parasitaemias

    PubMed Central

    González, Iveth J.; Polley, Spencer D.; Bell, David; Shakely, Delér; Msellem, Mwinyi I.; Björkman, Anders; Mårtensson, Andreas

    2014-01-01

    Background Loop mediated isothermal amplification (LAMP) provides an opportunity for improved, field-friendly detection of malaria infections in endemic areas. However data on the diagnostic accuracy of LAMP for active case detection, particularly low-density parasitaemias, are lacking. We therefore evaluated the performance of a new LAMP kit compared with PCR using DNA from filter paper blood spots. Methods and Findings Samples from 865 fever patients and 465 asymptomatic individuals collected in Zanzibar were analysed for Pan (all species) and Pf (P. falciparum) DNA with the Loopamp MALARIA Pan/Pf kit. Samples were amplified at 65°C for 40 minutes in a real-time turbidimeter and results were compared with nested PCR. Samples with discordant results between LAMP and nested PCR were analysed with real-time PCR. The real-time PCR corrected nested PCR result was defined as gold standard. Among the 117 (13.5%) PCR detected P. falciparum infections from fever patients (mean parasite density 7491/µL, range 6–782,400) 115, 115 and 111 were positive by Pan-LAMP, Pf-LAMP and nested PCR, respectively. The sensitivities were 98.3% (95%CI 94–99.8) for both Pan and Pf-LAMP. Among the 54 (11.6%) PCR positive samples from asymptomatic individuals (mean parasite density 10/µL, range 0–4972) Pf-LAMP had a sensitivity of 92.7% (95%CI 80.1–98.5) for detection of the 41 P. falciparum infections. Pan-LAMP had sensitivities of 97% (95%CI 84.2–99.9) and 76.9% (95%CI 46.2–95) for detection of P. falciparum and P. malariae, respectively. The specificities for both Pan and Pf-LAMP were 100% (95%CI 99.1–100) in both study groups. Conclusion Both components of the Loopamp MALARIA Pan/Pf detection kit revealed high diagnostic accuracy for parasite detection among fever patients and importantly also among asymptomatic individuals of low parasite densities from minute blood volumes preserved on filter paper. These data support LAMPs potential role for improved detection of low

  17. Adaptive sliding mode dynamic controller with integrator in the loop for nonholonomic wheeled mobile robot trajectory tracking

    NASA Astrophysics Data System (ADS)

    Asif, Muhammad; Junaid Khan, Muhammad; Cai, Ning

    2014-05-01

    In this paper, novel adaptive sliding mode dynamic controller with integrator in the loop is proposed for nonholonomic wheeled mobile robot (WMR). The modified kinematics controller is used to generate kinematics velocities of WMR which are subsequently used as the input to adaptive dynamic controller. Actuator dynamics are also derived to generate actuator voltage of WMR through torque and velocity vectors. Stability of both kinematics and dynamic controller is presented using Lyapunov stability analysis. The proposed scheme is verified and validated using computer simulations for tracking the desired trajectory of WMR. The performance of proposed scheme is compared with standard backstepping kinematics controller and classical sliding mode control. In addition, the performance is further compared with standard backstepping kinematics controller with adaptive sliding mode controller without integrator. It is shown that the proposed scheme exhibits zero steady state error, fast error convergence and robustness in the presence of continuous disturbances and uncertainties.

  18. Powerline interference reduction in ECG signals using empirical wavelet transform and adaptive filtering.

    PubMed

    Singh, Omkar; Sunkaria, Ramesh Kumar

    2015-01-01

    Separating an information-bearing signal from the background noise is a general problem in signal processing. In a clinical environment during acquisition of an electrocardiogram (ECG) signal, The ECG signal is corrupted by various noise sources such as powerline interference (PLI), baseline wander and muscle artifacts. This paper presents novel methods for reduction of powerline interference in ECG signals using empirical wavelet transform (EWT) and adaptive filtering. The proposed methods are compared with the empirical mode decomposition (EMD) based PLI cancellation methods. A total of six methods for PLI reduction based on EMD and EWT are analysed and their results are presented in this paper. The EWT-based de-noising methods have less computational complexity and are more efficient as compared with the EMD-based de-noising methods. PMID:25412942

  19. Adaptation of Gabor filters for simulation of human preattentive mechanism for a mobile robot

    NASA Astrophysics Data System (ADS)

    Kulkarni, Naren; Naghdy, Golshah A.

    1993-08-01

    Vision guided mobile robot navigation is complex and requires analysis of tremendous amounts of information in real time. In order to simplify the task and reduce the amount of information, human preattentive mechanism can be adapted [Nag90]. During the preattentive search the scene is analyzed rapidly but in sufficient detail for the attention to be focused on the `area of interest.' The `area of interest' can further be scrutinized in more detail for recognition purposes. This `area of interest' can be a text message to facilitate navigation. Gabor filters and an automated turning mechanism are used to isolate the `area of interest.' These regions are subsequently processed with optimal spatial resolution for perception tasks. This method has clear advantages over the global operators in that, after an initial search, it scans each region of interest with optimum resolution. This reduces the volume of information for recognition stages and ensures that no region is over or under estimated.

  20. Adaptive UAV Attitude Estimation Employing Unscented Kalman Filter, FOAM and Low-Cost MEMS Sensors

    PubMed Central

    de Marina, Héctor García; Espinosa, Felipe; Santos, Carlos

    2012-01-01

    Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance. PMID:23012559

  1. Adaptive Kalman filter for indoor localization using Bluetooth Low Energy and inertial measurement unit.

    PubMed

    Yoon, Paul K; Zihajehzadeh, Shaghayegh; Bong-Soo Kang; Park, Edward J

    2015-08-01

    This paper proposes a novel indoor localization method using the Bluetooth Low Energy (BLE) and an inertial measurement unit (IMU). The multipath and non-line-of-sight errors from low-power wireless localization systems commonly result in outliers, affecting the positioning accuracy. We address this problem by adaptively weighting the estimates from the IMU and BLE in our proposed cascaded Kalman filter (KF). The positioning accuracy is further improved with the Rauch-Tung-Striebel smoother. The performance of the proposed algorithm is compared against that of the standard KF experimentally. The results show that the proposed algorithm can maintain high accuracy for position tracking the sensor in the presence of the outliers. PMID:26736389

  2. An adaptive Kalman filter technique for context-aware heart rate monitoring.

    PubMed

    Xu, Min; Goldfain, Albert; Dellostritto, Jim; Iyengar, Satish

    2012-01-01

    Traditional physiological monitoring systems convert a person's vital sign waveforms, such as heart rate, respiration rate and blood pressure, into meaningful information by comparing the instant reading with a preset threshold or a baseline without considering the contextual information of the person. It would be beneficial to incorporate the contextual data such as activity status of the person to the physiological data in order to obtain a more accurate representation of a person's physiological status. In this paper, we proposed an algorithm based on adaptive Kalman filter that describes the heart rate response with respect to different activity levels. It is towards our final goal of intelligent detection of any abnormality in the person's vital signs. Experimental results are provided to demonstrate the feasibility of the algorithm. PMID:23367423

  3. Adaptive UAV attitude estimation employing unscented Kalman Filter, FOAM and low-cost MEMS sensors.

    PubMed

    de Marina, Héctor García; Espinosa, Felipe; Santos, Carlos

    2012-01-01

    Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance. PMID:23012559

  4. Motion artifact reduction in electrocardiogram using adaptive filtering based on half cell potential monitoring.

    PubMed

    Ko, Byung-hoon; Lee, Takhyung; Choi, Changmok; Kim, Youn-ho; Park, Gunguk; Kang, KyoungHo; Bae, Sang Kon; Shin, Kunsoo

    2012-01-01

    The electrocardiogram (ECG) is the main measurement parameter for effectively diagnosing chronic disease and guiding cardio-fitness therapy. ECGs contaminated by noise or artifacts disrupt the normal functioning of the automatic analysis algorithm. The objective of this study is to evaluate a method of measuring the HCP variation in motion artifacts through direct monitoring. The proposed wearable sensing device has two channels. One channel is used to measure the ECG through a differential amplifier. The other is for monitoring motion artifacts using the modified electrode and the same differential amplifier. Noise reduction was performed using adaptive filtering, based on a reference signal highly correlated with it. Direct measurement of HCP variations can eliminate the need for additional sensors. PMID:23366209

  5. Adaptive filters for monitoring localized brain activity from surface potential time series

    SciTech Connect

    Spencer, M.E. |; Leahy, R.M.; Mosher, J.C. |; Lewis, P.S.

    1992-12-01

    We address the problem of processing electroencephalographic (EEG) data to monitor the time series of the components of a current dipole source vector at a given location in the head. This is the spatial filtering problem for vector sources in a lossy, three dimensional, zero delay medium. Dipolar and distributed sources at other than the desired location are canceled or attenuated with an adaptive linearly constrained minimum variance (LCMV) beamformer. Actual EEG data acquired from a human subject serves as the interference in a case where the desired source is simulated and superimposed on the actual data. It is shown that the LCMV beamformer extracts the desired dipole time series while effectively canceling the subjects interference.

  6. Adaptive filters for monitoring localized brain activity from surface potential time series

    SciTech Connect

    Spencer, M.E. . Signal and Image Processing Inst. TRW, Inc., Redondo Beach, CA ); Leahy, R.M. . Signal and Image Processing Inst.); Mosher, J.C. . Signal and Image Processing Inst. Lo

    1992-01-01

    We address the problem of processing electroencephalographic (EEG) data to monitor the time series of the components of a current dipole source vector at a given location in the head. This is the spatial filtering problem for vector sources in a lossy, three dimensional, zero delay medium. Dipolar and distributed sources at other than the desired location are canceled or attenuated with an adaptive linearly constrained minimum variance (LCMV) beamformer. Actual EEG data acquired from a human subject serves as the interference in a case where the desired source is simulated and superimposed on the actual data. It is shown that the LCMV beamformer extracts the desired dipole time series while effectively canceling the subjects interference.

  7. Color filter array demosaicing: an adaptive progressive interpolation based on the edge type

    NASA Astrophysics Data System (ADS)

    Dong, Qiqi; Liu, Zhaohui

    2015-10-01

    Color filter array (CFA) is one of the key points for single-sensor digital cameras to produce color images. Bayer CFA is the most commonly used pattern. In this array structure, the sampling frequency of green is two times of red or blue, which is consistent with the sensitivity of human eyes to colors. However, each sensor pixel only samples one of three primary color values. To render a full-color image, an interpolation process, commonly referred to CFA demosaicing, is required to estimate the other two missing color values at each pixel. In this paper, we explore an adaptive progressive interpolation based on the edge type algorithm. The proposed demosaicing method consists of two successive steps: an interpolation step that estimates missing color values according to various edges and a post-processing step by iterative interpolation.

  8. Adaptive Kalman filtering for real-time mapping of the visual field

    PubMed Central

    Ward, B. Douglas; Janik, John; Mazaheri, Yousef; Ma, Yan; DeYoe, Edgar A.

    2013-01-01

    This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results. Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field. Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications. The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume. PMID:22100663

  9. A novel nonlinear adaptive filter using a pipelined second-order Volterra recurrent neural network.

    PubMed

    Zhao, Haiquan; Zhang, Jiashu

    2009-12-01

    To enhance the performance and overcome the heavy computational complexity of recurrent neural networks (RNN), a novel nonlinear adaptive filter based on a pipelined second-order Volterra recurrent neural network (PSOVRNN) is proposed in this paper. A modified real-time recurrent learning (RTRL) algorithm of the proposed filter is derived in much more detail. The PSOVRNN comprises of a number of simple small-scale second-order Volterra recurrent neural network (SOVRNN) modules. In contrast to the standard RNN, these modules of a PSOVRNN can be performed simultaneously in a pipelined parallelism fashion, which can lead to a significant improvement in its total computational efficiency. Moreover, since each module of the PSOVRNN is a SOVRNN in which nonlinearity is introduced by the recursive second-order Volterra (RSOV) expansion, its performance can be further improved. Computer simulations have demonstrated that the PSOVRNN performs better than the pipelined recurrent neural network (PRNN) and RNN for nonlinear colored signals prediction and nonlinear channel equalization. However, the superiority of the PSOVRNN over the PRNN is at the cost of increasing computational complexity due to the introduced nonlinear expansion of each module. PMID:19523787

  10. Bilateral filtering and adaptive tone-mapping for qualified edge and image enhancement

    NASA Astrophysics Data System (ADS)

    Hu, Kuo-Jui; Chang, Ting-Ting; Lu, Min-Yao; Li, Wu-Jeng; Huang, Jih-Fon

    2009-01-01

    Most of high-contrast images are common with dark and bright area. It is difficult to present the detail on both dark and high light areas on display devices. In order to resolve this problem, we proposed a method of image enhancement to improve this image quality and used bilateral filter to keep the detail. In paper, we applied an appropriate algorithm to process images. At first, we use bilateral filter to separate image. One is large scale image and the other is detail image. Second, we made large scale image which was translated into histogram. In order to make the images divided into three stairs, such as lightness, middle-tone and darkness region. We decided two optimal threshold parameters. Finally, according to three images we use different tone-mapping method to process each stair. The tone-mapping method includes adaptive s-curve and gamma curve algorithms. The experiment results of this study revealed image detail and enhancement. To avoid contour phenomenon is in lightness region.

  11. Use of adaptive hybrid filtering process in Crohn's disease lesion detection from real capsule endoscopy videos.

    PubMed

    Charisis, Vasileios S; Hadjileontiadis, Leontios J

    2016-03-01

    The aim of this Letter is to present a new capsule endoscopy (CE) image analysis scheme for the detection of small bowel ulcers that relate to Crohn's disease. More specifically, this scheme is based on: (i) a hybrid adaptive filtering (HAF) process, that utilises genetic algorithms to the curvelet-based representation of images for efficient extraction of the lesion-related morphological characteristics, (ii) differential lacunarity (DL) analysis for texture feature extraction from the HAF-filtered images and (iii) support vector machines for robust classification performance. For the training of the proposed scheme, namely HAF-DL, an 800-image database was used and the evaluation was based on ten 30-second long endoscopic videos. Experimental results, along with comparison with other related efforts, have shown that the HAF-DL approach evidently outperforms the latter in the field of CE image analysis for automated lesion detection, providing higher classification results. The promising performance of HAF-DL paves the way for a complete computer-aided diagnosis system that could support the physicians' clinical practice. PMID:27222730

  12. Adaptive Filter-bank Approach to Restoration and Spectral Analysis of Gapped Data

    NASA Astrophysics Data System (ADS)

    Stoica, Petre; Larsson, Erik G.; Li, Jian

    2000-10-01

    The main topic of this paper is the nonparametric estimation of complex (both amplitude and phase) spectra from gapped data, as well as the restoration of such data. The focus is on the extension of the APES (amplitude and phase estimation) approach to data sequences with gaps. APES, which is one of the most successful existing nonparametric approaches to the spectral analysis of full data sequences, uses a bank of narrowband adaptive (both frequency and data dependent) filters to estimate the spectrum. A recent interpretation of this approach showed that the filterbank used by APES and the resulting spectrum minimize a least-squares (LS) fitting criterion between the filtered sequence and its spectral decomposition. The extended approach, which is called GAPES for somewhat obvious reasons, capitalizes on the aforementioned interpretation: it minimizes the APES-LS fitting criterion with respect to the missing data as well. This should be a sensible thing to do whenever the full data sequence is stationary, and hence the missing data have the same spectral content as the available data. We use both simulated and real data examples to show that GAPES estimated spectra and interpolated data sequences have excellent accuracy. We also show the performance gain achieved by GAPES over two of the most commonly used approaches for gapped-data spectral analysis, viz., the periodogram and the parametric CLEAN method. This work was partly supported by the Swedish Foundation for Strategic Research.

  13. Adaptive spatial filtering of daytime sky noise in a satellite quantum key distribution downlink receiver

    NASA Astrophysics Data System (ADS)

    Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.

    2016-02-01

    Spatial filtering is an important technique for reducing sky background noise in a satellite quantum key distribution downlink receiver. Atmospheric turbulence limits the extent to which spatial filtering can reduce sky noise without introducing signal losses. Using atmospheric propagation and compensation simulations, the potential benefit of adaptive optics (AO) to secure key generation (SKG) is quantified. Simulations are performed assuming optical propagation from a low-Earth-orbit satellite to a terrestrial receiver that includes AO. Higher-order AO correction is modeled assuming a Shack-Hartmann wavefront sensor and a continuous-face-sheet deformable mirror. The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain wave-optics hardware emulator. SKG rates are calculated for a decoy-state protocol as a function of the receiver field of view for various strengths of turbulence, sky radiances, and pointing angles. The results show that at fields of view smaller than those discussed by others, AO technologies can enhance SKG rates in daylight and enable SKG where it would otherwise be prohibited as a consequence of background optical noise and signal loss due to propagation and turbulence effects.

  14. Local stimulus disambiguation with global motion filters predicts adaptive surround modulation.

    PubMed

    Dellen, Babette; Torras, Carme

    2013-10-01

    Humans have no problem segmenting different motion stimuli despite the ambiguity of local motion signals. Adaptive surround modulation, i.e., the apparent switching between integrative and antagonistic modes, is assumed to play a crucial role in this process. However, so far motion processing models based on local integration have not been able to provide a unifying explanation for this phenomenon. This motivated us to investigate the problem of local stimulus disambiguation in an alternative and fundamentally distinct motion-processing model which uses global motion filters for velocity computation. Local information is reconstructed at the end of the processing stream through the constructive interference of global signals, i.e., inverse transformations. We show that in this model local stimulus disambiguation can be achieved by means of a novel filter embedded in this architecture. This gives rise to both integrative and antagonistic effects which are in agreement with those observed in psychophysical experiments with humans, providing a functional explanation for effects of motion repulsion. PMID:23685285

  15. Optical single sideband modulation based on a high-order birefringent filter using cascaded Solc-Sagnac and Lyot-Sagnac loops.

    PubMed

    Feng, Danqi; Sun, Junqiang

    2016-08-01

    We propose and experimentally demonstrate a simple and flexible photonic approach to implementing single sideband (SSB) modulation based on optical spectral filtering. The high-order birefringent filter is realized through the cascaded Solc-Sagnac and Lyot-Sagnac loops. By adjusting the rotation angle of the polarization controller (PC), the notch position to remove undesired sidebands changes. The frequency for SSB modulation varies accordingly. The periodical response of the filter spectrum allows both the carrier wavelength and the optical carrier to sideband ratio (OCSR) to be tunable. SSB modulation over a frequency range from 5 to 40 GHz and tunable OCSR ranging from -9.174 to 34.408 dB are obtained. The significant merits of the proposed approach are the simple structure, easy operation, large frequency range, tunable OCSR, and wavelength independence. The approach has potential applications in optimizing the transmission performance of photonic microwave signal processing systems. PMID:27472643

  16. Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

    NASA Astrophysics Data System (ADS)

    Jia, Ying-Hong; Hu, Quan; Xu, Shi-Jie

    2014-02-01

    A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the position and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane's equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters being estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov's method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach. [Figure not available: see fulltext.

  17. Emergence of band-pass filtering through adaptive spiking in the owl's cochlear nucleus.

    PubMed

    Fontaine, Bertrand; MacLeod, Katrina M; Lubejko, Susan T; Steinberg, Louisa J; Köppl, Christine; Peña, Jose L

    2014-07-15

    In the visual, auditory, and electrosensory modalities, stimuli are defined by first- and second-order attributes. The fast time-pressure signal of a sound, a first-order attribute, is important, for instance, in sound localization and pitch perception, while its slow amplitude-modulated envelope, a second-order attribute, can be used for sound recognition. Ascending the auditory pathway from ear to midbrain, neurons increasingly show a preference for the envelope and are most sensitive to particular envelope modulation frequencies, a tuning considered important for encoding sound identity. The level at which this tuning property emerges along the pathway varies across species, and the mechanism of how this occurs is a matter of debate. In this paper, we target the transition between auditory nerve fibers and the cochlear nucleus angularis (NA). While the owl's auditory nerve fibers simultaneously encode the fast and slow attributes of a sound, one synapse further, NA neurons encode the envelope more efficiently than the auditory nerve. Using in vivo and in vitro electrophysiology and computational analysis, we show that a single-cell mechanism inducing spike threshold adaptation can explain the difference in neural filtering between the two areas. We show that spike threshold adaptation can explain the increased selectivity to modulation frequency, as input level increases in NA. These results demonstrate that a spike generation nonlinearity can modulate the tuning to second-order stimulus features, without invoking network or synaptic mechanisms. PMID:24790170

  18. Iterative version of the QRD for adaptive recursive least squares (RLS) filtering

    NASA Astrophysics Data System (ADS)

    Goetze, Juergen

    1994-10-01

    A modified version of the QR-decomposition (QRD) is presented. It uses approximate Givens rotations instead of exact Givens rotations, i.e., a matrix entry usually annihilated with an exact rotation by an angle (sigma) is only reduced by using an approximate rotation by an angle (sigma) . The approximation of the rotations is based on the idea of CORDIC. Evaluating a CORDIC-based approximate rotation is to determine the angle (sigma) equals (sigma) t equals arctan 2-t, which is closest to the exact rotation angle (sigma) . This angle (sigma) t is applied instead of (sigma) . Using approximate rotations for computing the QRD results in an iterative version of the original QRD. A recursive version of this QRD using CORDIC-based approximate rotations is applied to adaptive RLS filtering. Only a few angles of the CORDIC sequence, r say (r << b, where b is the word length), work as well as using exact rotations (r equals b, original CORDIC). The misadjustment error decreases as r increases. The convergence of the QRD-RLS algorithm, however, is insensitive to the value of r. Adapting the approximation accuracy during the course of the QRD-RLS algorithm is also discussed. Simulations (channel equalization) confirm the results.

  19. Emergence of band-pass filtering through adaptive spiking in the owl's cochlear nucleus

    PubMed Central

    MacLeod, Katrina M.; Lubejko, Susan T.; Steinberg, Louisa J.; Köppl, Christine; Peña, Jose L.

    2014-01-01

    In the visual, auditory, and electrosensory modalities, stimuli are defined by first- and second-order attributes. The fast time-pressure signal of a sound, a first-order attribute, is important, for instance, in sound localization and pitch perception, while its slow amplitude-modulated envelope, a second-order attribute, can be used for sound recognition. Ascending the auditory pathway from ear to midbrain, neurons increasingly show a preference for the envelope and are most sensitive to particular envelope modulation frequencies, a tuning considered important for encoding sound identity. The level at which this tuning property emerges along the pathway varies across species, and the mechanism of how this occurs is a matter of debate. In this paper, we target the transition between auditory nerve fibers and the cochlear nucleus angularis (NA). While the owl's auditory nerve fibers simultaneously encode the fast and slow attributes of a sound, one synapse further, NA neurons encode the envelope more efficiently than the auditory nerve. Using in vivo and in vitro electrophysiology and computational analysis, we show that a single-cell mechanism inducing spike threshold adaptation can explain the difference in neural filtering between the two areas. We show that spike threshold adaptation can explain the increased selectivity to modulation frequency, as input level increases in NA. These results demonstrate that a spike generation nonlinearity can modulate the tuning to second-order stimulus features, without invoking network or synaptic mechanisms. PMID:24790170

  20. Performance Enhancement of Pharmacokinetic Diffuse Fluorescence Tomography by Use of Adaptive Extended Kalman Filtering.

    PubMed

    Wang, Xin; Wu, Linhui; Yi, Xi; Zhang, Yanqi; Zhang, Limin; Zhao, Huijuan; Gao, Feng

    2015-01-01

    Due to both the physiological and morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic diffuse fluorescence tomography (DFT) can provide contrast-enhanced and comprehensive information for tumor diagnosis and staging. In this regime, the extended Kalman filtering (EKF) based method shows numerous advantages including accurate modeling, online estimation of multiparameters, and universal applicability to any optical fluorophore. Nevertheless the performance of the conventional EKF highly hinges on the exact and inaccessible prior knowledge about the initial values. To address the above issues, an adaptive-EKF scheme is proposed based on a two-compartmental model for the enhancement, which utilizes a variable forgetting-factor to compensate the inaccuracy of the initial states and emphasize the effect of the current data. It is demonstrated using two-dimensional simulative investigations on a circular domain that the proposed adaptive-EKF can obtain preferable estimation of the pharmacokinetic-rates to the conventional-EKF and the enhanced-EKF in terms of quantitativeness, noise robustness, and initialization independence. Further three-dimensional numerical experiments on a digital mouse model validate the efficacy of the method as applied in realistic biological systems. PMID:26089975

  1. Multiframe adaptive Wiener filter super-resolution with JPEG2000-compressed images

    NASA Astrophysics Data System (ADS)

    Narayanan, Barath Narayanan; Hardie, Russell C.; Balster, Eric J.

    2014-12-01

    Historically, Joint Photographic Experts Group 2000 (JPEG2000) image compression and multiframe super-resolution (SR) image processing techniques have evolved separately. In this paper, we propose and compare novel processing architectures for applying multiframe SR with JPEG2000 compression. We propose a modified adaptive Wiener filter (AWF) SR method and study its performance as JPEG2000 is incorporated in different ways. In particular, we perform compression prior to SR and compare this to compression after SR. We also compare both independent-frame compression and difference-frame compression approaches. We find that some of the SR artifacts that result from compression can be reduced by decreasing the assumed global signal-to-noise ratio (SNR) for the AWF SR method. We also propose a novel spatially adaptive SNR estimate for the AWF designed to compensate for the spatially varying compression artifacts in the input frames. The experimental results include the use of simulated imagery for quantitative analysis. We also include real-video results for subjective analysis.

  2. Adaptive Resampling Particle Filters for GPS Carrier-Phase Navigation and Collision Avoidance System

    NASA Astrophysics Data System (ADS)

    Hwang, Soon Sik

    This dissertation addresses three problems: 1) adaptive resampling technique (ART) for Particle Filters, 2) precise relative positioning using Global Positioning System (GPS) Carrier-Phase (CP) measurements applied to nonlinear integer resolution problem for GPS CP navigation using Particle Filters, and 3) collision detection system based on GPS CP broadcasts. First, Monte Carlo filters, called Particle Filters (PF), are widely used where the system is non-linear and non-Gaussian. In real-time applications, their estimation accuracies and efficiencies are significantly affected by the number of particles and the scheduling of relocating weights and samples, the so-called resampling step. In this dissertation, the appropriate number of particles is estimated adaptively such that the error of the sample mean and variance stay in bounds. These bounds are given by the confidence interval of a normal probability distribution for a multi-variate state. Two required number of samples maintaining the mean and variance error within the bounds are derived. The time of resampling is determined when the required sample number for the variance error crosses the required sample number for the mean error. Second, the PF using GPS CP measurements with adaptive resampling is applied to precise relative navigation between two GPS antennas. In order to make use of CP measurements for navigation, the unknown number of cycles between GPS antennas, the so called integer ambiguity, should be resolved. The PF is applied to this integer ambiguity resolution problem where the relative navigation states estimation involves nonlinear observations and nonlinear dynamics equation. Using the PF, the probability density function of the states is estimated by sampling from the position and velocity space and the integer ambiguities are resolved without using the usual hypothesis tests to search for the integer ambiguity. The ART manages the number of position samples and the frequency of the

  3. Adaptive Correlation Space Adjusted Open-Loop Tracking Approach for Vehicle Positioning with Global Navigation Satellite System in Urban Areas.

    PubMed

    Ruan, Hang; Li, Jian; Zhang, Lei; Long, Teng

    2015-01-01

    For vehicle positioning with Global Navigation Satellite System (GNSS) in urban areas, open-loop tracking shows better performance because of its high sensitivity and superior robustness against multipath. However, no previous study has focused on the effects of the code search grid size on the code phase measurement accuracy of open-loop tracking. Traditional open-loop tracking methods are performed by the batch correlators with fixed correlation space. The code search grid size, which is the correlation space, is a constant empirical value and the code phase measuring accuracy will be largely degraded due to the improper grid size, especially when the signal carrier-to-noise density ratio (C/N₀) varies. In this study, the Adaptive Correlation Space Adjusted Open-Loop Tracking Approach (ACSA-OLTA) is proposed to improve the code phase measurement dependent pseudo range accuracy. In ACSA-OLTA, the correlation space is adjusted according to the signal C/N₀. The novel Equivalent Weighted Pseudo Range Error (EWPRE) is raised to obtain the optimal code search grid sizes for different C/N₀. The code phase measuring errors of different measurement calculation methods are analyzed for the first time. The measurement calculation strategy of ACSA-OLTA is derived from the analysis to further improve the accuracy but reduce the correlator consumption. Performance simulation and real tests confirm that the pseudo range and positioning accuracy of ASCA-OLTA are better than the traditional open-loop tracking methods in the usual scenarios of urban area. PMID:26343683

  4. Adaptive Correlation Space Adjusted Open-Loop Tracking Approach for Vehicle Positioning with Global Navigation Satellite System in Urban Areas

    PubMed Central

    Ruan, Hang; Li, Jian; Zhang, Lei; Long, Teng

    2015-01-01

    For vehicle positioning with Global Navigation Satellite System (GNSS) in urban areas, open-loop tracking shows better performance because of its high sensitivity and superior robustness against multipath. However, no previous study has focused on the effects of the code search grid size on the code phase measurement accuracy of open-loop tracking. Traditional open-loop tracking methods are performed by the batch correlators with fixed correlation space. The code search grid size, which is the correlation space, is a constant empirical value and the code phase measuring accuracy will be largely degraded due to the improper grid size, especially when the signal carrier-to-noise density ratio (C/N0) varies. In this study, the Adaptive Correlation Space Adjusted Open-Loop Tracking Approach (ACSA-OLTA) is proposed to improve the code phase measurement dependent pseudo range accuracy. In ACSA-OLTA, the correlation space is adjusted according to the signal C/N0. The novel Equivalent Weighted Pseudo Range Error (EWPRE) is raised to obtain the optimal code search grid sizes for different C/N0. The code phase measuring errors of different measurement calculation methods are analyzed for the first time. The measurement calculation strategy of ACSA-OLTA is derived from the analysis to further improve the accuracy but reduce the correlator consumption. Performance simulation and real tests confirm that the pseudo range and positioning accuracy of ASCA-OLTA are better than the traditional open-loop tracking methods in the usual scenarios of urban area. PMID:26343683

  5. A novel adaptive discrete cosine transform-domain filter for gap-inpainting of high resolution PET scanners

    SciTech Connect

    Shih, Cheng-Ting; Lin, Hsin-Hon; Chuang, Keh-Shih; Wu, Jay; Chang, Shu-Jun

    2014-08-15

    Purpose: Several positron emission tomography (PET) scanners with special detector block arrangements have been developed in recent years to improve the resolution of PET images. However, the discontinuous detector blocks cause gaps in the sinogram. This study proposes an adaptive discrete cosine transform-based (aDCT) filter for gap-inpainting. Methods: The gap-corrupted sinogram was morphologically closed and subsequently converted to the DCT domain. A certain number of the largest coefficients in the DCT spectrum were identified to determine the low-frequency preservation region. The weighting factors for the remaining coefficients were determined by an exponential weighting function. The aDCT filter was constructed and applied to two digital phantoms and a simulated phantom introduced with various levels of noise. Results: For the Shepp-Logan head phantom, the aDCT filter filled the gaps effectively. For the Jaszczak phantom, no secondary artifacts were induced after aDCT filtering. The percent mean square error and mean structure similarity of the aDCT filter were superior to those of the DCT2 filter at all noise levels. For the simulated striatal dopamine innervation study, the aDCT filter recovered the shape of the striatum and restored the striatum to reference activity ratios to the ideal value. Conclusions: The proposed aDCT filter can recover the missing gap data in the sinogram and improve the image quality and quantitative accuracy of PET images.

  6. Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition

    NASA Astrophysics Data System (ADS)

    Wu, Chunyan; Liu, Jian; Peng, Fuqiang; Yu, Dejie; Li, Rong

    2013-07-01

    When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.

  7. Adaptive clutter filter in 2-D color flow imaging based on in vivo I/Q signal.

    PubMed

    Zhou, Xiaoming; Zhang, Congyao; Liu, Dong C

    2014-01-01

    Color flow imaging has been well applied in clinical diagnosis. For the high quality color flow images, clutter filter is important to separate the Doppler signals from blood and tissue. Traditional clutter filters, such as finite impulse response, infinite impulse response and regression filters, were applied, which are based on the hypothesis that the clutter signal is stationary or tissue moves slowly. However, in realistic clinic color flow imaging, the signals are non-stationary signals because of accelerated moving tissue. For most related papers, simulated RF signals are widely used without in vivo I/Q signal. Hence, in this paper, adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, was proposed based on in vivo carotid I/Q signal in realistic color flow imaging. To get the best performance, the optimal polynomial order of polynomial regression filter and the optimal polynomial order for estimation of instantaneous clutter frequency respectively were confirmed. Finally, compared with the mean blood velocity and quality of 2-D color flow image, the experiment results show that adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, can significantly enhance the mean blood velocity and get high quality 2-D color flow image. PMID:24211911

  8. Simulation of mid-infrared clutter rejection. 1: One-dimensional LMS spatial filter and adaptive threshold algorithms.

    PubMed

    Longmire, M S; Milton, A F; Takken, E H

    1982-11-01

    Several 1-D signal processing techniques have been evaluated by simulation with a digital computer using high-spatial-resolution (0.15 mrad) noise data gathered from back-lit clouds and uniform sky with a scanning data collection system operating in the 4.0-4.8-microm spectral band. Two ordinary bandpass filters and a least-mean-square (LMS) spatial filter were evaluated in combination with a fixed or adaptive threshold algorithm. The combination of a 1-D LMS filter and a 1-D adaptive threshold sensor was shown to reject extreme cloud clutter effectively and to provide nearly equal signal detection in a clear and cluttered sky, at least in systems whose NEI (noise equivalent irradiance) exceeds 1.5 x 10(-13) W/cm(2) and whose spatial resolution is better than 0.15 x 0.36 mrad. A summary gives highlights of the work, key numerical results, and conclusions. PMID:20396326

  9. Some adaptive filtering techniques applied to the passive remote sensing problem. [for Tiros-N and Nimbus 6 experiments

    NASA Technical Reports Server (NTRS)

    Toldalagi, P. M.

    1980-01-01

    A review is made of recursive statistical regression techniques incorporating past or past and future observations through smoothing and Kalman filtering, respectively; with results for the cases of the Tiros-N/MSU and Nimbus-6/Scams remote sensing satellite experiments. In response to the lack of a satisfactory model for the medium sounded, which is presently a major limitation on retrieval technique performance, a novel, global approach is proposed which casts the retrieval problem into the framework of adaptive filtering. A numerical implementation of such an adaptive system is presented, with a multilayer, semi-spectral general circulation model for the atmosphere being used to fine-tune the sensor as well as the dynamical equations of a Kalman filter. It is shown that the assimilation of radiometric data becomes a straightforward subproblem.

  10. Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter

    PubMed Central

    2014-01-01

    Background In magnetic resonance electrical impedance tomography (MREIT), we reconstruct conductivity images using magnetic flux density data induced by externally injected currents. Since we extract magnetic flux density data from acquired MR phase images, the amount of measurement noise increases in regions of weak MR signals. Especially for local regions of MR signal void, there may occur excessive amounts of noise to deteriorate the quality of reconstructed conductivity images. In this paper, we propose a new conductivity image enhancement method as a postprocessing technique to improve the image quality. Methods Within a magnetic flux density image, the amount of noise varies depending on the position-dependent MR signal intensity. Using the MR magnitude image which is always available in MREIT, we estimate noise levels of measured magnetic flux density data in local regions. Based on the noise estimates, we adjust the window size and weights of a spatial averaging filter, which is applied to reconstructed conductivity images. Without relying on a partial differential equation, the new method is fast and can be easily implemented. Results Applying the novel conductivity image enhancement method to experimental data, we could improve the image quality to better distinguish local regions with different conductivity contrasts. From phantom experiments, the estimated conductivity values had 80% less variations inside regions of homogeneous objects. Reconstructed conductivity images from upper and lower abdominal regions of animals showed much less artifacts in local regions of weak MR signals. Conclusion We developed the fast and simple method to enhance the conductivity image quality by adaptively adjusting the weights and window size of the spatial averaging filter using MR magnitude images. Since the new method is implemented as a postprocessing step, we suggest adopting it without or with other preprocessing methods for application studies where conductivity

  11. Improved characterization of slow-moving landslides by means of adaptive NL-InSAR filtering

    NASA Astrophysics Data System (ADS)

    Albiol, David; Iglesias, Rubén.; Sánchez, Francisco; Duro, Javier

    2014-10-01

    Advanced remote sensing techniques based on space-borne Synthetic Aperture Radar (SAR) have been developed during the last decade showing their applicability for the monitoring of surface displacements in landslide areas. This paper presents an advanced Persistent Scatterer Interferometry (PSI) processing based on the Stable Point Network (SPN) technique, developed by the company Altamira-Information, for the monitoring of an active slowmoving landslide in the mountainous environment of El Portalet, Central Spanish Pyrenees. For this purpose, two TerraSAR-X data sets acquired in ascending mode corresponding to the period from April to November 2011, and from August to November 2013, respectively, are employed. The objective of this work is twofold. On the one hand, the benefits of employing Nonlocal Interferomtric SAR (NL-InSAR) adaptive filtering techniques over vegetated scenarios to maximize the chances of detecting natural distributed scatterers, such as bare or rocky areas, and deterministic point-like scatterers, such as man-made structures or poles, is put forward. In this context, the final PSI displacement maps retrieved with the proposed filtering technique are compared in terms of pixels' density and quality with classical PSI, showing a significant improvement. On the other hand, since SAR systems are only sensitive to detect displacements in the line-of-sight (LOS) direction, the importance of projecting the PSI displacement results retrieved along the steepest gradient of the terrain slope is discussed. The improvements presented in this paper are particularly interesting in these type of applications since they clearly allow to better determine the extension and dynamics of complex landslide phenomena.

  12. Modular high-voltage bias generator powered by dual-looped self-adaptive wireless power transmission.

    PubMed

    Xie, Kai; Huang, An-Feng; Li, Xiao-Ping; Guo, Shi-Zhong; Zhang, Han-Lu

    2015-04-01

    We proposed a modular high-voltage (HV) bias generator powered by a novel transmitter-sharing inductive coupled wireless power transmission technology, aimed to extend the generator's flexibility and configurability. To solve the problems caused through an uncertain number of modules, a dual-looped self-adaptive control method is proposed that is capable of tracking resonance frequency while maintaining a relatively stable induction voltage for each HV module. The method combines a phase-locked loop and a current feedback loop, which ensures an accurate resonance state and a relatively constant boost ratio for each module, simplifying the architecture of the boost stage and improving the total efficiency. The prototype was built and tested. The input voltage drop of each module is less than 14% if the module number varies from 3 to 10; resonance tracking is completed within 60 ms. The efficiency of the coupling structure reaches up to 95%, whereas the total efficiency approaches 73% for a rated output. Furthermore, this technology can be used in various multi-load wireless power supply applications. PMID:25933880

  13. Modular high-voltage bias generator powered by dual-looped self-adaptive wireless power transmission

    NASA Astrophysics Data System (ADS)

    Xie, Kai; Huang, An-Feng; Li, Xiao-Ping; Guo, Shi-Zhong; Zhang, Han-Lu

    2015-04-01

    We proposed a modular high-voltage (HV) bias generator powered by a novel transmitter-sharing inductive coupled wireless power transmission technology, aimed to extend the generator's flexibility and configurability. To solve the problems caused through an uncertain number of modules, a dual-looped self-adaptive control method is proposed that is capable of tracking resonance frequency while maintaining a relatively stable induction voltage for each HV module. The method combines a phase-locked loop and a current feedback loop, which ensures an accurate resonance state and a relatively constant boost ratio for each module, simplifying the architecture of the boost stage and improving the total efficiency. The prototype was built and tested. The input voltage drop of each module is less than 14% if the module number varies from 3 to 10; resonance tracking is completed within 60 ms. The efficiency of the coupling structure reaches up to 95%, whereas the total efficiency approaches 73% for a rated output. Furthermore, this technology can be used in various multi-load wireless power supply applications.

  14. A New Model Based on Adaptation of the External Loop to Compensate the Hysteresis of Tactile Sensors

    PubMed Central

    Sánchez-Durán, José A.; Vidal-Verdú, Fernando; Oballe-Peinado, Óscar; Castellanos-Ramos, Julián; Hidalgo-López, José A.

    2015-01-01

    This paper presents a novel method to compensate for hysteresis nonlinearities observed in the response of a tactile sensor. The External Loop Adaptation Method (ELAM) performs a piecewise linear mapping of the experimentally measured external curves of the hysteresis loop to obtain all possible internal cycles. The optimal division of the input interval where the curve is approximated is provided by the error minimization algorithm. This process is carried out off line and provides parameters to compute the split point in real time. A different linear transformation is then performed at the left and right of this point and a more precise fitting is achieved. The models obtained with the ELAM method are compared with those obtained from three other approaches. The results show that the ELAM method achieves a more accurate fitting. Moreover, the involved mathematical operations are simpler and therefore easier to implement in devices such as Field Programmable Gate Array (FPGAs) for real time applications. Furthermore, the method needs to identify fewer parameters and requires no previous selection process of operators or functions. Finally, the method can be applied to other sensors or actuators with complex hysteresis loop shapes. PMID:26501279

  15. Design of a constant-voltage and constant-current controller with dual-loop and adaptive switching frequency control

    NASA Astrophysics Data System (ADS)

    Yingping, Chen; Zhiqian, Li

    2015-05-01

    A 5.0-V 2.0-A flyback power supply controller providing constant-voltage (CV) and constant-current (CC) output regulation without the use of an optical coupler is presented. Dual-close-loop control is proposed here due to its better regulation performance of tolerance over process and temperature compared with open loop control used in common. At the same time, the two modes, CC and CV, could switch to each other automatically and smoothly according to the output voltage level not sacrificing the regulation accuracy at the switching phase, which overcomes the drawback of the digital control scheme depending on a hysteresis comparator to change the mode. On-chip compensation using active capacitor multiplier technique is applied to stabilize the voltage loop, eliminate an additional package pin, and save on the die area. The system consumes as little as 100 mW at no-load condition without degrading the transient response performance by utilizing the adaptive switching frequency control mode. The proposed controller has been implemented in a commercial 0.35-μm 40-V BCD process, and the active chip area is 1.5 × 1.0 mm2. The total error of the output voltage due to line and load variations is less than ±1.7%.

  16. A new model based on adaptation of the external loop to compensate the hysteresis of tactile sensors.

    PubMed

    Sánchez-Durán, José A; Vidal-Verdú, Fernando; Oballe-Peinado, Óscar; Castellanos-Ramos, Julián; Hidalgo-López, José A

    2015-01-01

    This paper presents a novel method to compensate for hysteresis nonlinearities observed in the response of a tactile sensor. The External Loop Adaptation Method (ELAM) performs a piecewise linear mapping of the experimentally measured external curves of the hysteresis loop to obtain all possible internal cycles. The optimal division of the input interval where the curve is approximated is provided by the error minimization algorithm. This process is carried out off line and provides parameters to compute the split point in real time. A different linear transformation is then performed at the left and right of this point and a more precise fitting is achieved. The models obtained with the ELAM method are compared with those obtained from three other approaches. The results show that the ELAM method achieves a more accurate fitting. Moreover, the involved mathematical operations are simpler and therefore easier to implement in devices such as Field Programmable Gate Array (FPGAs) for real time applications. Furthermore, the method needs to identify fewer parameters and requires no previous selection process of operators or functions. Finally, the method can be applied to other sensors or actuators with complex hysteresis loop shapes. PMID:26501279

  17. The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

    NASA Astrophysics Data System (ADS)

    Schneider, Martin; Kellermann, Walter

    2016-01-01

    Acoustic echo cancellation (AEC) is a well-known application of adaptive filters in communication acoustics. To implement AEC for multichannel reproduction systems, powerful adaptation algorithms like the generalized frequency-domain adaptive filtering (GFDAF) algorithm are required for satisfactory convergence behavior. In this paper, the GFDAF algorithm is rigorously derived as an approximation of the block recursive least-squares (RLS) algorithm. Thereby, the original formulation of the GFDAF algorithm is generalized while avoiding an error that has been in the original derivation. The presented algorithm formulation is applied to pruned transform-domain loudspeaker-enclosure-microphone models in a mathematically consistent manner. Such pruned models have recently been proposed to cope with the tremendous computational demands of massive multichannel AEC. Beyond its generalization, a regularization of the GFDAF is shown to have a close relation to the well-known block least-mean-squares algorithm.

  18. A family of variable step-size affine projection adaptive filter algorithms using statistics of channel impulse response

    NASA Astrophysics Data System (ADS)

    Shams Esfand Abadi, Mohammad; AbbasZadeh Arani, Seyed Ali Asghar

    2011-12-01

    This paper extends the recently introduced variable step-size (VSS) approach to the family of adaptive filter algorithms. This method uses prior knowledge of the channel impulse response statistic. Accordingly, optimal step-size vector is obtained by minimizing the mean-square deviation (MSD). The presented algorithms are the VSS affine projection algorithm (VSS-APA), the VSS selective partial update NLMS (VSS-SPU-NLMS), the VSS-SPU-APA, and the VSS selective regressor APA (VSS-SR-APA). In VSS-SPU adaptive algorithms the filter coefficients are partially updated which reduce the computational complexity. In VSS-SR-APA, the optimal selection of input regressors is performed during the adaptation. The presented algorithms have good convergence speed, low steady state mean square error (MSE), and low computational complexity features. We demonstrate the good performance of the proposed algorithms through several simulations in system identification scenario.

  19. Adaptive Square-Root Cubature-Quadrature Kalman Particle Filter for satellite attitude determination using vector observations

    NASA Astrophysics Data System (ADS)

    Kiani, Maryam; Pourtakdoust, Seid H.

    2014-12-01

    A novel algorithm is presented in this study for estimation of spacecraft's attitudes and angular rates from vector observations. In this regard, a new cubature-quadrature particle filter (CQPF) is initially developed that uses the Square-Root Cubature-Quadrature Kalman Filter (SR-CQKF) to generate the importance proposal distribution. The developed CQPF scheme avoids the basic limitation of particle filter (PF) with regards to counting the new measurements. Subsequently, CQPF is enhanced to adjust the sample size at every time step utilizing the idea of confidence intervals, thus improving the efficiency and accuracy of the newly proposed adaptive CQPF (ACQPF). In addition, application of the q-method for filter initialization has intensified the computation burden as well. The current study also applies ACQPF to the problem of attitude estimation of a low Earth orbit (LEO) satellite. For this purpose, the undertaken satellite is equipped with a three-axis magnetometer (TAM) as well as a sun sensor pack that provide noisy geomagnetic field data and Sun direction measurements, respectively. The results and performance of the proposed filter are investigated and compared with those of the extended Kalman filter (EKF) and the standard particle filter (PF) utilizing a Monte Carlo simulation. The comparison demonstrates the viability and the accuracy of the proposed nonlinear estimator.

  20. Adapting Enzyme-Free DNA Circuits to the Detection of Loop-Mediated Isothermal Amplification Reactions

    PubMed Central

    Li, Bingling; Chen, Xi; Ellington, Andrew D.

    2012-01-01

    Loop-mediated isothermal amplification of DNA (LAMP) is a powerful isothermal nucleic acid amplification technique that can accumulate ~109 copies from less than 10 copies of input template within an hour or two. Unfortunately, while the amplification reactions are extremely powerful, the quantitative detection of LAMP products is still analytically difficult. In this article, in order to both improve the specificity of LAMP detection and to make direct readout of LAMP amplification simpler and much more reliable, we have developed a non-enzymatic nucleic acid circuit (catalyzed hairpin assembly, CHA) that can both amplify and integrate the specific sequence signals present in LAMP amplicons. Through a hairpin acceptor, one of the four loop products amplified from the LAMP is transduced to an active catalyst ssDNA which can in turn trigger a CHA reaction. After CHA detection, even less than 10 molecules/μL model templates (M13mp18) can produce significant signal, and both non-specific template and parasitic amplicons cannot bring interference at all. More importantly, to further enhance the specificity, we have designed a dual-CHA circuit that only gave positive responses in presence of two LAMP loops. The AND-GATE detector will act as a simultaneous, specific readout of the LAMP product, rather than of competing and parasitic amplicons. PMID:22947054

  1. A new adaptive method to filter terrestrial laser scanner point clouds using morphological filters and spectral information to conserve surface micro-topography

    NASA Astrophysics Data System (ADS)

    Rodríguez-Caballero, E.; Afana, A.; Chamizo, S.; Solé-Benet, A.; Canton, Y.

    2016-07-01

    Terrestrial laser scanning (TLS), widely known as light detection and ranging (LiDAR) technology, is increasingly used to provide highly detailed digital terrain models (DTM) with millimetric precision and accuracy. In order to generate a DTM, TLS data has to be filtered from undesired spurious objects, such as vegetation, artificial structures, etc., Early filtering techniques, successfully applied to airborne laser scanning (ALS), fail when applied to TLS data, as they heavily smooth the terrain surface and do not retain their real morphology. In this article, we present a new methodology for filtering TLS data based on the geometric and radiometric properties of the scanned surfaces. This methodology was built on previous morphological filters that select the minimum point height within a sliding window as the real surface. However, contrary to those methods, which use a fixed window size, the new methodology operates under different spatial scales represented by different window sizes, and can be adapted to different types and sizes of plants. This methodology has been applied to two study areas of differing vegetation type and density. The accuracy of the final DTMs was improved by ∼30% under dense canopy plants and over ∼40% on the open spaces between plants, where other methodologies drastically underestimated the real surface heights. This resulted in more accurate representation of the soil surface and microtopography than up-to-date techniques, eventually having strong implications in hydrological and geomorphological studies.

  2. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    PubMed Central

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  3. Flexible Riser Monitoring Using Hybrid Magnetic/Optical Strain Gage Techniques through RLS Adaptive Filtering

    NASA Astrophysics Data System (ADS)

    Pipa, Daniel; Morikawa, Sérgio; Pires, Gustavo; Camerini, Claudio; Santos, JoãoMárcio

    2010-12-01

    Flexible riser is a class of flexible pipes which is used to connect subsea pipelines to floating offshore installations, such as FPSOs (floating production/storage/off-loading unit) and SS (semisubmersible) platforms, in oil and gas production. Flexible risers are multilayered pipes typically comprising an inner flexible metal carcass surrounded by polymer layers and spiral wound steel ligaments, also referred to as armor wires. Since these armor wires are made of steel, their magnetic properties are sensitive to the stress they are subjected to. By measuring their magnetic properties in a nonintrusive manner, it is possible to compare the stress in the armor wires, thus allowing the identification of damaged ones. However, one encounters several sources of noise when measuring electromagnetic properties contactlessly, such as movement between specimen and probe, and magnetic noise. This paper describes the development of a new technique for automatic monitoring of armor layers of flexible risers. The proposed approach aims to minimize these current uncertainties by combining electromagnetic measurements with optical strain gage data through a recursive least squares (RLSs) adaptive filter.

  4. Seismic random noise attenuation based on adaptive time-frequency peak filtering

    NASA Astrophysics Data System (ADS)

    Deng, Xinhuan; Ma, Haitao; Li, Yue; Zeng, Qian

    2015-02-01

    Time-frequency peak filtering (TFPF) method uses a specific window with fixed length to recover band-limited signal in stationary random noise. However, the derivatives of signal such as seismic wavelets may change rapidly in some short time intervals. In this case, TFPF equipped with fixed window length will not provide an optimal solution. In this letter, we present an adaptive version of TFPF for seismic random noise attenuation. In our version, the improved intersection of confidence intervals combined with short-time energy criterion is used to preprocess the noisy signal. And then, we choose an appropriate threshold to divide the noisy signal into signal, buffer and noise. Different optimal window lengths are used in each type of segments. We test the proposed method on both synthetic and field seismic data. The experimental results illustrate that the proposed method makes the degree of amplitude preservation raise more than 10% and signal-to-noise (SNR) improve 2-4 dB compared with the original algorithm.

  5. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  6. Adaptive-weighted bilateral filtering and other pre-processing techniques for optical coherence tomography.

    PubMed

    Anantrasirichai, N; Nicholson, Lindsay; Morgan, James E; Erchova, Irina; Mortlock, Katie; North, Rachel V; Albon, Julie; Achim, Alin

    2014-09-01

    This paper presents novel pre-processing image enhancement algorithms for retinal optical coherence tomography (OCT). These images contain a large amount of speckle causing them to be grainy and of very low contrast. To make these images valuable for clinical interpretation, we propose a novel method to remove speckle, while preserving useful information contained in each retinal layer. The process starts with multi-scale despeckling based on a dual-tree complex wavelet transform (DT-CWT). We further enhance the OCT image through a smoothing process that uses a novel adaptive-weighted bilateral filter (AWBF). This offers the desirable property of preserving texture within the OCT image layers. The enhanced OCT image is then segmented to extract inner retinal layers that contain useful information for eye research. Our layer segmentation technique is also performed in the DT-CWT domain. Finally we describe an OCT/fundus image registration algorithm which is helpful when two modalities are used together for diagnosis and for information fusion. PMID:25034317

  7. Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

    PubMed Central

    Garrido, Jesús A.; Luque, Niceto R.; D'Angelo, Egidio; Ros, Eduardo

    2013-01-01

    Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario

  8. Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation.

    PubMed

    Garrido, Jesús A; Luque, Niceto R; D'Angelo, Egidio; Ros, Eduardo

    2013-01-01

    Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario

  9. A 1microW 85nV/ radicalHz pseudo open-loop preamplifier with programmable band-pass filter for neural interface system.

    PubMed

    Chang, Sun-Il; Yoon, Euisik

    2009-01-01

    We report an energy efficient pseudo open-loop amplifier with programmable band-pass filter developed for neural interface systems. The proposed amplifier consumes 400nA at 2.5V power supply. The measured thermal noise level is 85nV/ radicalHz and input-referred noise is 1.69microV(rms) from 0.3Hz to 1 kHz. The amplifier has a noise efficiency factor of 2.43, the lowest in the differential topologies reported up to date to our knowledge. By programming the switched-capacitor frequency and bias current, we could control the bandwidth of the preamplifier from 138 mHz to 2.2 kHz to meet various application requirements. The entire preamplifier including band-pass filters has been realized in a small area of 0.043mm(2) using a 0.25microm CMOS technology. PMID:19964762

  10. Exploring the Role of Mechanotransduction Activation and Adaptation Kinetics in Hair Cell Filtering Using a Hodgkin-Huxley Approach

    NASA Astrophysics Data System (ADS)

    Wells, Gregg B.; Ricci, Anthony J.

    2011-11-01

    In the auditory system, mechanotransduction occurs in the hair cell sensory hair bundle and is the first major step in the translation of mechanical energy into electrical. Tonotopic variations in the activation kinetics of this process are posited to provide a low pass filter to the input. An adaptation process, also associated with mechanotransduction, is postulated to provide a high pass filter to the input in a tonotopic manner. Together a bandpass filter is created at the hair cell input. Corresponding mechanical components to both activation and adaptation are also suggested to be involved in generating cochlear amplification. A paradox to this story is that hair cells where the mechanotransduction properties are most robust possess an intrinsic electrical resonance mechanism proposed to account for all required tuning and amplification. A simple Hodgkin-Huxley type model is presented to attempt to determine the role of the activation and adaptation kinetics in further tuning hair cells that exhibit electrical resonance. Results further support that steady state mechanotransduction properties are critical for setting the resting potential of the hair cell while the kinetics of activation and adaptation are important for sharpening tuning around the characteristic frequency of the hair cell.

  11. Adaptable Single Active Loop Thermal Control System (TCS) for Future Space Missions

    NASA Technical Reports Server (NTRS)

    Mudawar, Issam; Lee, Seunghyun; Hasan, Mohammad

    2015-01-01

    This presentation will examine the development of a thermal control system (TCS) for future space missions utilizing a single active cooling loop. The system architecture enables the TCS to be reconfigured during the various mission phases to respond, not only to varying heat load, but to heat rejection temperature as well. The system will consist of an accumulator, pump, cold plates (evaporators), condenser radiator, and compressor, in addition to control, bypass and throttling valves. For cold environments, the heat will be rejected by radiation, during which the compressor will be bypassed, reducing the system to a simple pumped loop that, depending on heat load, can operate in either a single-phase liquid mode or two-phase mode. For warmer environments, the pump will be bypassed, enabling the TCS to operate as a heat pump. This presentation will focus on recent findings concerning two-phase flow regimes, pressure drop, and heat transfer coefficient trends in the cabin and avionics micro-channel heat exchangers when using the heat pump mode. Also discussed will be practical implications of using micro-channel evaporators for the heat pump.

  12. Design of adaptive reconfigurable control systems using extended-Kalman-filter-based system identification and eigenstructure assignments

    NASA Astrophysics Data System (ADS)

    Wang, Xudong; Syrmos, Vassilis L.

    2004-07-01

    In this paper, an adaptive reconfigurable control system based on extended Kalman filter approach and eigenstructure assignments is proposed. System identification is carried out using an extended Kalman filter (EKF) approach. An eigenstructure assignment (EA) technique is applied for reconfigurable feedback control law design to recover the system dynamic performance. The reconfigurable feedforward controllers are designed to achieve the steady-state tracking using input weighting approach. The proposed scheme can identify not only actuator and sensor variations, but also changes in the system structures using the extended Kalman filtering method. The overall design is robust with respect to uncertainties in the state-space matrices of the reconfigured system. To illustrate the effectiveness of the proposed reconfigurable control system design technique, an aircraft longitudinal vertical takeoff and landing (VTOL) control system is used to demonstrate the reconfiguration procedure.

  13. A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

    NASA Astrophysics Data System (ADS)

    Ushaq, Muhammad; Fang, Jiancheng

    2013-10-01

    Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be

  14. High-performance RC bandpass filter is adapted to miniaturized construction

    NASA Technical Reports Server (NTRS)

    1966-01-01

    Miniaturized bandpass filter with RC networks is suitable for use in integrated circuits. The circuit consists of three stages of amplification with additional resistive and capacitive components to obtain the desired characteristics. The advantages of the active RC filter network are the reduction in size and weight and elimination of magnetic materials.

  15. Adaptive feedforward of estimated ripple improves the closed loop system performance significantly

    SciTech Connect

    Kwon, S.; Regan, A.; Wang, Y.M.; Rohlev, T.

    1998-12-31

    The Low Energy Demonstration Accelerator (LEDA) being constructed at Los Alamos National Laboratory will serve as the prototype for the low energy section of Acceleration Production of Tritium (APT) accelerator. This paper addresses the problem of LLRF control system for LEDA. The authors propose an estimator of the ripple and its time derivative and a control law which is based on PID control and adaptive feedforward of estimated ripple. The control law reduces the effect of the deterministic cathode ripple that is due to high voltage power supply and achieves tracking of desired set points.

  16. Woofer-tweeter deformable mirror control for closed-loop adaptive optics: theory and practice

    NASA Astrophysics Data System (ADS)

    Gavel, Donald; Norton, Andrew

    2014-08-01

    Deformable mirrors with very high order correction generally have smaller dynamic range of motion than what is required to correct seeing over large aperture telescopes. As a result, systems will need to have an architecture that employs two deformable mirrors in series, one for the low-order but large excursion parts of the wavefront and one for the finer and smaller excursion components. The closed-loop control challenge is to a) keep the overall system stable, b) avoid the two mirrors using control energy to cancel each others correction, c) resolve actuator saturations stably, d) assure that on average the mirrors are each correcting their assigned region of spatial frequency space. We present the control architecture and techniques for assuring that it is linear and stable according to the above criteria. We derived the analytic forms for stability and performance and show results from simulations and on-sky testing using the new ShaneAO system on the Lick 3-meter telescope.

  17. Estimating diffusion properties in complex fiber configurations based on structure-adaptive multi-valued tensor-field filtering

    NASA Astrophysics Data System (ADS)

    Yang, Jianfei; Poot, Dirk H. J.; Arkesteijn, Georgius A. M.; Caan, Matthan W.; van Vliet, Lucas J.; Vos, Frans M.

    2015-03-01

    Conventionally, a single rank-2 tensor is used to assess the white matter integrity in diffusion imaging of the human brain. However, a single tensor fails to describe the diffusion in fiber crossings. Although a dual tensor model is able to do so, the low signal-to-noise ratio hampers reliable parameter estimation as the number of parameters is doubled. We present a framework for structure-adaptive tensor field filtering to enhance the statistical analysis in complex fiber structures. In our framework, a tensor model will be fitted based on an automated relevance determination method. Particularly, a single tensor model is applied to voxels in which the data seems to represent a single fiber and a dualtensor model to voxels appearing to contain crossing fibers. To improve the estimation of the model parameters we propose a structure-adaptive tensor filter that is applied to tensors belonging to the same fiber compartment only. It is demonstrated that the structure-adaptive tensor-field filter improves the continuity and regularity of the estimated tensor field. It outperforms an existing denoising approach called LMMSE, which is applied to the diffusion-weighted images. Track-based spatial statistics analysis of fiber-specific FA maps show that the method sustains the detection of more subtle changes in white matter tracts than the classical single-tensor-based analysis. Thus, the filter enhances the applicability of the dual-tensor model in diffusion imaging research. Specifically, the reliable estimation of two tensor diffusion properties facilitates fiber-specific extraction of diffusion features.

  18. A double-loop structure in the adaptive generalized predictive control algorithm for control of robot end-point contact force.

    PubMed

    Wen, Shuhuan; Zhu, Jinghai; Li, Xiaoli; Chen, Shengyong

    2014-09-01

    Robot force control is an essential issue in robotic intelligence. There is much high uncertainty when robot end-effector contacts with the environment. Because of the environment stiffness effects on the system of the robot end-effector contact with environment, the adaptive generalized predictive control algorithm based on quantitative feedback theory is designed for robot end-point contact force system. The controller of the internal loop is designed on the foundation of QFT to control the uncertainty of the system. An adaptive GPC algorithm is used to design external loop controller to improve the performance and the robustness of the system. Two closed loops used in the design approach realize the system׳s performance and improve the robustness. The simulation results show that the algorithm of the robot end-effector contacting force control system is effective. PMID:24973336

  19. Radiation dose reduction with application of non-linear adaptive filters for abdominal CT

    PubMed Central

    Singh, Sarabjeet; Kalra, Mannudeep K; Sung, Mi Kim; Back, Anni; Blake, Michael A

    2012-01-01

    AIM: To evaluate the effect of non-linear adaptive filters (NLAF) on abdominal computed tomography (CT) images acquired at different radiation dose levels. METHODS: Nineteen patients (mean age 61.6 ± 7.9 years, M:F = 8:11) gave informed consent for an Institutional Review Board approved prospective study involving acquisition of 4 additional image series (200, 150, 100, 50 mAs and 120 kVp) on a 64 slice multidetector row CT scanner over an identical 10 cm length in the abdomen. The CT images acquired at 150, 100 and 50 mAs were processed with the NLAF. Two radiologists reviewed unprocessed and processed images for image quality in a blinded randomized manner. CT dose index volume, dose length product, patient weight, transverse diameters, objective noise and CT numbers were recorded. Data were analyzed using Analysis of Variance and Wilcoxon signed rank test. RESULTS: Of the 31 lesions detected in abdominal CT images, 28 lesions were less than 1 cm in size. Subjective image noise was graded as unacceptable in unprocessed images at 50 and 100 mAs, and in NLAF processed images at 50 mAs only. In NLAF processed images, objective image noise was decreased by 21% (14.4 ± 4/18.2 ± 4.9) at 150 mAs, 28.3% (15.7 ± 5.6/21.9 ± 4) at 100 mAs and by 39.4% (18.8 ± 9/30.4 ± 9.2) at 50 mAs compared to unprocessed images acquired at respective radiation dose levels. At 100 mAs the visibility of smaller structures improved from suboptimal in unprocessed images to excellent in NLAF processed images, whereas diagnostic confidence was respectively improved from probably confident to fully confident. CONCLUSION: NLAF lowers image noise, improves the visibility of small structures and maintains lesion conspicuity at down to 100 mAs for abdominal CT. PMID:22328968

  20. A new family of Gaussian filters with adaptive lobe location and smoothing strength for efficient image restoration

    NASA Astrophysics Data System (ADS)

    Seddik, Hassene

    2014-12-01

    Noise can occur during image capture, transmission, or processing phases. Image de-noising is a very important step in image processing, and many approaches are developed in order to achieve this goal such as the Gaussian filter which is efficient in noise removal. Its smoothing efficiency depends on the value of its standard deviation. The mask representing the filter presents generally static weights with invariant lobe. In this paper, an adaptive de-noising approach is proposed. The proposed approach uses a Gaussian kernel with variable width and direction called adaptive Gaussian kernel (AGK). In each processed window of the image, the smoothing strength changes according to the image content, noise kind, and intensity. In addition, the location of its lobe changes in eight different directions over the processed window. This directional variability avoids averaging details by the highest mask weights in order to preserve the edges and the borders. The recovered data is de-noised efficiently without introducing blur or losing details. A comparative study with the static Gaussian filter and other recent techniques is presented to prove the efficiency of the proposed approach.

  1. FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

    PubMed

    Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

    2016-01-01

    In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved. PMID:27420062

  2. FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter

    PubMed Central

    Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

    2016-01-01

    In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved. PMID:27420062

  3. Adaptive filtering in spatial vision: evidence from feature marking in plaids.

    PubMed

    Georgeson, M A; Meese, T S

    1999-01-01

    Much evidence shows that early vision employs an array of spatial filters tuned for different spatial frequencies and orientations. We suggest that for moderately low spatial frequencies these preliminary filters are not treated independently, but are used to perform grouping and segmentation in the patchwise Fourier domain. For example, consider a stationary plaid made from two superimposed sinusoidal gratings of the same contrast and spatial frequency oriented +/- 45 degrees from vertical. Most of the energy in a wavelet-like (e.g. simple-cell) transform of this stimulus is in the oblique orientations, but typically it looks like a compound structure containing blurred vertical and horizontal edges. This checkerboard structure corresponds with the locations of zero crossings in the output of an isotropic (circular) filter, synthesised from the linear sum of a set of oriented basis-filters (Georgeson, 1992 Proceedings of the Royal Society of London, Series B 249 235-245). However, the addition of a third harmonic in square-wave phase causes almost complete perceptual segmentation of the plaid into two overlapping oblique gratings. Here we confirm this result psychophysically using a feature-marking technique, and argue that this perceptual segmentation cannot be understood in terms of the zero crossings marked in the output of any static linear filter that is sensitive to all of the plaid's components. If it is assumed that zero crossings or similar are an appropriate feature-primitive in human vision, our results require a flexible process that combines and segments early basis-filters according to prevailing image conditions. Thus, we suggest that combination and segmentation of spatial filters in the patchwise Fourier domain underpins the perceptual segmentation observed in our experiments. Under this kind of image-processing scheme, registration across spatial scales occurs at the level of spatial filters, before features are extracted. This contrasts with

  4. Adaptation of filtered back-projection to compton imaging with non-uniform azimuthal geometry

    NASA Astrophysics Data System (ADS)

    Lee, Hyounggun; Lee, Taewoong; Lee, Wonho

    2016-05-01

    For Compton image reconstruction, analytic reconstruction methods such as filtered backprojection have been used for real-time imaging. The conventional filtered back-projection method assumes a uniformly distributed azimuthal response in the detector system. In this study, we applied filtered back-projection to the experimental data from detector systems with limited azimuthal angle coverage ranges and estimated the limitations of the analytic reconstruction methods when applied to these systems. For the system with a uniform azimuthal response, the images reconstructed by using filtered back-projection showed better angular resolutions than the images obtained by using simple back-projection did. However, when filtered back-projection was applied to reconstruct Compton images based on measurements performed by using Compton cameras with limited response geometries, the reconstructed images exhibited artifacts caused by the geometrical limitations. Our proposed method employs the Compton camera's rotation to overcome the angular response limitations; when the rotation method was applied in this study, the artifacts in the reconstructed images caused by angular response limitations were minimized. With this method, filtered back-projection can be applied to reconstruct real-time Compton images even when the radiation measurements are performed by using Compton cameras with non-uniform azimuthal response geometries.

  5. Guided filter and adaptive learning rate based non-uniformity correction algorithm for infrared focal plane array

    NASA Astrophysics Data System (ADS)

    Sheng-Hui, Rong; Hui-Xin, Zhou; Han-Lin, Qin; Rui, Lai; Kun, Qian

    2016-05-01

    Imaging non-uniformity of infrared focal plane array (IRFPA) behaves as fixed-pattern noise superimposed on the image, which affects the imaging quality of infrared system seriously. In scene-based non-uniformity correction methods, the drawbacks of ghosting artifacts and image blurring affect the sensitivity of the IRFPA imaging system seriously and decrease the image quality visibly. This paper proposes an improved neural network non-uniformity correction method with adaptive learning rate. On the one hand, using guided filter, the proposed algorithm decreases the effect of ghosting artifacts. On the other hand, due to the inappropriate learning rate is the main reason of image blurring, the proposed algorithm utilizes an adaptive learning rate with a temporal domain factor to eliminate the effect of image blurring. In short, the proposed algorithm combines the merits of the guided filter and the adaptive learning rate. Several real and simulated infrared image sequences are utilized to verify the performance of the proposed algorithm. The experiment results indicate that the proposed algorithm can not only reduce the non-uniformity with less ghosting artifacts but also overcome the problems of image blurring in static areas.

  6. Wireless rake-receiver using adaptive filter with a family of partial update algorithms in noise cancellation applications

    NASA Astrophysics Data System (ADS)

    Fayadh, Rashid A.; Malek, F.; Fadhil, Hilal A.; Aldhaibani, Jaafar A.; Salman, M. K.; Abdullah, Farah Salwani

    2015-05-01

    For high data rate propagation in wireless ultra-wideband (UWB) communication systems, the inter-symbol interference (ISI), multiple-access interference (MAI), and multiple-users interference (MUI) are influencing the performance of the wireless systems. In this paper, the rake-receiver was presented with the spread signal by direct sequence spread spectrum (DS-SS) technique. The adaptive rake-receiver structure was shown with adjusting the receiver tap weights using least mean squares (LMS), normalized least mean squares (NLMS), and affine projection algorithms (APA) to support the weak signals by noise cancellation and mitigate the interferences. To minimize the data convergence speed and to reduce the computational complexity by the previous algorithms, a well-known approach of partial-updates (PU) adaptive filters were employed with algorithms, such as sequential-partial, periodic-partial, M-max-partial, and selective-partial updates (SPU) in the proposed system. The simulation results of bit error rate (BER) versus signal-to-noise ratio (SNR) are illustrated to show the performance of partial-update algorithms that have nearly comparable performance with the full update adaptive filters. Furthermore, the SPU-partial has closed performance to the full-NLMS and full-APA while the M-max-partial has closed performance to the full-LMS updates algorithms.

  7. Local Ensemble Transform Kalman Filter: a non stationary control law for complex adaptive optics systems on ELTs

    NASA Astrophysics Data System (ADS)

    Gray, Morgan; Petit, Cyril; Rodionov, Sergey; Bertino, Laurent; Bocquet, Marc; Fusco, Thierry

    2013-12-01

    We propose a new algorithm for an AO control law which allows to reduce the computation burden in the case of an Extremely Large Telescope and to deal with a non stationary behavior of the atmospheric turbulence. This approach uses Ensemble Transform Kalman Filter (ETKF) and localizations by domains decomposition: the assimilation is split into local domains on the pupil of the telescope and each of the update data assimilation for each domain is performed independently. This kind of assimilation enables parallel computation of much less data during the update stage. This is a Kalman Filter adaptation for large scale systems with a non stationary turbulence when the explicit storage and manipulation of extremely large covariance matrices are impossible. This distributed parallel environment implementation is highlighted and studied in the context of an ELT application. First simulation results are proposed to assess our theoretical analysis and to demonstrate the potentiality of this new approach for an AO control law on ELTs.

  8. Development of Tremor Suppression Control System Using Adaptive Filter and Its Application to Meal-assist Robot

    NASA Astrophysics Data System (ADS)

    Yano, Ken'ichi; Ohara, Eiichi; Horihata, Satoshi; Aoki, Takaaki; Nishimoto, Yutaka

    A robot that supports independent living by assisting with eating and other activities which use the operator's own hand would be helpful for people suffering from tremors of the hand or any other body part. The proposed system using adaptive filter estimates tremor frequencies with a time-varying property and individual differences online. In this study, the estimated frequency is used to adjusting the tremor suppression filter which insulates the voluntary motion signal from the sensor signal containing tremor components. These system are integrated into the control system of the Meal-Assist Robot. As a result, the developed system makes it possible for the person with a tremor to manipulate the supporting robot without causing operability to deteriorate and without hazards due to improper operation.

  9. The impact of head movements on EEG and contact impedance: an adaptive filtering solution for motion artifact reduction.

    PubMed

    Mihajlovic, Vojkan; Patki, Shrishail; Grundlehner, Bernard

    2014-01-01

    Designing and developing a comfortable and convenient EEG system for daily usage that can provide reliable and robust EEG signal, encompasses a number of challenges. Among them, the most ambitious is the reduction of artifacts due to body movements. This paper studies the effect of head movement artifacts on the EEG signal and on the dry electrode-tissue impedance (ETI), monitored continuously using the imec's wireless EEG headset. We have shown that motion artifacts have huge impact on the EEG spectral content in the frequency range lower than 20 Hz. Coherence and spectral analysis revealed that ETI is not capable of describing disturbances at very low frequencies (below 2 Hz). Therefore, we devised a motion artifact reduction (MAR) method that uses a combination of a band-pass filtering and multi-channel adaptive filtering (AF), suitable for real-time MAR. This method was capable of substantially reducing artifacts produced by head movements. PMID:25571131

  10. Sensor-fault tolerant control of a powered lower limb prosthesis by mixing mode-specific adaptive Kalman filters.

    PubMed

    Dutta, Anirban; Koerding, Konrad; Perreault, Eric; Hargrove, Levi

    2011-01-01

    Machine learning methods for interfacing humans with machines is an emerging area. Here we propose a novel algorithm for interfacing humans with powered lower limb prostheses for restoring control of naturalistic gait following amputation. Unlike most previous neural machine interfaces, our approach fuses control information from the user with sensor information from the prosthesis to approximate the closed loop behavior of the unimpaired sensorimotor system. We present a Bayesian framework to control an artificial knee by probabilistically mixing of process state estimates from different Kalman filters, each addressing separate regimes of locomotion such as level ground walking, walking up a ramp, and walking down a ramp. We show its utility as a mode classifier that is tolerant to temporary sensor faults which are frequently experienced in practical applications. PMID:22255142

  11. Linear adaptive noise-reduction filters for tomographic imaging: Optimizing for minimum mean square error

    SciTech Connect

    Sun, W Y

    1993-04-01

    This thesis solves the problem of finding the optimal linear noise-reduction filter for linear tomographic image reconstruction. The optimization is data dependent and results in minimizing the mean-square error of the reconstructed image. The error is defined as the difference between the result and the best possible reconstruction. Applications for the optimal filter include reconstructions of positron emission tomographic (PET), X-ray computed tomographic, single-photon emission tomographic, and nuclear magnetic resonance imaging. Using high resolution PET as an example, the optimal filter is derived and presented for the convolution backprojection, Moore-Penrose pseudoinverse, and the natural-pixel basis set reconstruction methods. Simulations and experimental results are presented for the convolution backprojection method.

  12. Optimal-adaptive filters for modelling spectral shape, site amplification, and source scaling

    USGS Publications Warehouse

    Safak, Erdal

    1989-01-01

    This paper introduces some applications of optimal filtering techniques to earthquake engineering by using the so-called ARMAX models. Three applications are presented: (a) spectral modelling of ground accelerations, (b) site amplification (i.e., the relationship between two records obtained at different sites during an earthquake), and (c) source scaling (i.e., the relationship between two records obtained at a site during two different earthquakes). A numerical example for each application is presented by using recorded ground motions. The results show that the optimal filtering techniques provide elegant solutions to above problems, and can be a useful tool in earthquake engineering.

  13. Efficiency and adaptability of the benthic methane filter at Quepos Slide cold seeps, offshore of Costa Rica

    NASA Astrophysics Data System (ADS)

    Steeb, P.; Krause, S.; Linke, P.; Hensen, C.; Dale, A. W.; Nuzzo, M.; Treude, T.

    2015-11-01

    Large amounts of methane are delivered by fluids through the erosive forearc of the convergent margin offshore of Costa Rica and lead to the formation of cold seeps at the sediment surface. Besides mud extrusion, numerous cold seeps are created by landslides induced by seamount subduction or fluid migration along major faults. Most of the dissolved methane migrating through the sediments of cold seeps is oxidized within the benthic microbial methane filter by anaerobic oxidation of methane (AOM). Measurements of AOM and sulfate reduction as well as numerical modeling of porewater profiles revealed a highly active and efficient benthic methane filter at the Quepos Slide site, a landslide on the continental slope between the Nicoya and Osa Peninsula. Integrated areal rates of AOM ranged from 12.9 ± 6.0 to 45.2 ± 11.5 mmol m-2 d-1, with only 1 to 2.5 % of the upward methane flux being released into the water column. Additionally, two parallel sediment cores from Quepos Slide were used for in vitro experiments in a recently developed sediment-flow-through (SLOT) system to simulate an increased fluid and methane flux from the bottom of the sediment core. The benthic methane filter revealed a high adaptability whereby the methane oxidation efficiency responded to the increased fluid flow within ca. 170 d. To our knowledge, this study provides the first estimation of the natural biogeochemical response of seep sediments to changes in fluid flow.

  14. Adaptive Kalman filtering based internal temperature estimation with an equivalent electrical network thermal model for hard-cased batteries

    NASA Astrophysics Data System (ADS)

    Dai, Haifeng; Zhu, Letao; Zhu, Jiangong; Wei, Xuezhe; Sun, Zechang

    2015-10-01

    The accurate monitoring of battery cell temperature is indispensible to the design of battery thermal management system. To obtain the internal temperature of a battery cell online, an adaptive temperature estimation method based on Kalman filtering and an equivalent time-variant electrical network thermal (EENT) model is proposed. The EENT model uses electrical components to simulate the battery thermodynamics, and the model parameters are obtained with a least square algorithm. With a discrete state-space description of the EENT model, a Kalman filtering (KF) based internal temperature estimator is developed. Moreover, considering the possible time-varying external heat exchange coefficient, a joint Kalman filtering (JKF) based estimator is designed to simultaneously estimate the internal temperature and the external thermal resistance. Several experiments using the hard-cased LiFePO4 cells with embedded temperature sensors have been conducted to validate the proposed method. Validation results show that, the EENT model expresses the battery thermodynamics well, the KF based temperature estimator tracks the real central temperature accurately even with a poor initialization, and the JKF based estimator can simultaneously estimate both central temperature and external thermal resistance precisely. The maximum estimation errors of the KF- and JKF-based estimators are less than 1.8 °C and 1 °C respectively.

  15. Acceleration amplitude-phase regulation for electro-hydraulic servo shaking table based on LMS adaptive filtering algorithm

    NASA Astrophysics Data System (ADS)

    Yao, Jianjun; Di, Duotao; Jiang, Guilin; Gao, Shuang

    2012-10-01

    Electro-hydraulic servo shaking table usually requires good control performance for acceleration replication. The poles of the electro-hydraulic servo shaking table are placed by three-variable control method using pole placement theory. The system frequency band is thus extended and the system stability is also enhanced. The phase delay and amplitude attenuation phenomenon occurs in electro-hydraulic servo shaking table corresponding to an acceleration sinusoidal input. The method for phase delay and amplitude attenuation elimination based on LMS adaptive filtering algorithm is proposed here. The task is accomplished by adjusting the weights using LMS adaptive filtering algorithm when there exits phase delay and amplitude attenuation between the input and its corresponding acceleration response. The reference input is weighted in such a way that it makes the system output track the input efficiently. The weighted input signal is inputted to the control system such that the output phase delay and amplitude attenuation are all cancelled. The above concept is used as a basis for the development of amplitude-phase regulation (APR) algorithm. The method does not need to estimate the system model and has good real-time performance. Experimental results demonstrate the efficiency and validity of the proposed APR control scheme.

  16. Adaptive unscented Kalman filter based state of energy and power capability estimation approach for lithium-ion battery

    NASA Astrophysics Data System (ADS)

    Zhang, Weige; Shi, Wei; Ma, Zeyu

    2015-09-01

    Accurate estimations of battery energy and available power capability are of great of importance for realizing an efficient and reliable operation of electric vehicles. To improve the estimation accuracy and reliability for battery state of energy and power capability, a novel model-based joint estimation approach has been proposed against uncertain external operating conditions and internal degradation status of battery cells. Firstly, it proposes a three-dimensional response surface open circuit voltage model to calibrate the estimation inaccuracies of battery state of energy. Secondly, the adaptive unscented Kalman filter (AUKF) is employed to develop a novel model-based joint state estimator for battery state of energy and power capability. The AUKF algorithm utilizes the well-known features of the Kalman filter but employs the method of unscented transform (UT) and adaptive error covariance matching technology to improve the state estimation accuracy. Thirdly, the proposed joint estimator has been verified by a LiFePO4 lithium-ion battery cell under different operating temperatures and aging levels. The result indicates that the estimation errors of battery voltage and state-of-energy are less than 2% even if given a large erroneous initial value, which makes the state of available power capability predict more accurate and reliable for the electric vehicles application.

  17. Feedforward compensation control of rotor imbalance for high-speed magnetically suspended centrifugal compressors using a novel adaptive notch filter

    NASA Astrophysics Data System (ADS)

    Zheng, Shiqiang; Feng, Rui

    2016-03-01

    This paper introduces a feedforward control strategy combined with a novel adaptive notch filter to solve the problem of rotor imbalance in high-speed Magnetically Suspended Centrifugal Compressors (MSCCs). Unbalance vibration force of rotor in MSCC is mainly composed of current stiffness force and displacement stiffness force. In this paper, the mathematical model of the unbalance vibration with the proportional-integral-derivative (PID) control laws is presented. In order to reduce the unbalance vibration, a novel adaptive notch filter is proposed to identify the synchronous frequency displacement of the rotor as a compensation signal to eliminate the current stiffness force. In addition, a feedforward channel from position component to control output is introduced to compensate displacement stiffness force to achieve a better performance. A simplified inverse model of power amplifier is included in the feedforward channel to reject the degrade performance caused by its low-pass characteristic. Simulation and experimental results on a MSCC demonstrate a significant effect on the synchronous vibration suppression of the magnetically suspended rotor at a high speed.

  18. Integrated adaptive filtering and design for control experiments of flexible structures

    NASA Technical Reports Server (NTRS)

    Huang, Jen-Kuang

    1991-01-01

    A novel method is presented of identifying a state space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relations between the state space model and the finite difference model for linear stochastic systems derived through projection filters. It is proven that least squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model. In estimating the corresponding state estimator gain, a z-domain method is used. First the deterministic component of the output is subtracted out, and then the state estimator gain is obtained by whitening the remaining signal. Experimental example is used to illustrate the feasibility of the method.

  19. Adaptive Kalman filter implementation by a neural network scheme for tracking maneuvering targets

    NASA Astrophysics Data System (ADS)

    Amoozegar, Farid; Sundareshan, Malur K.

    1995-07-01

    Conventional target tracking algorithms based on linear estimation techniques perform quite efficiently when the target motion does not involve maneuvers. Target maneuvers involving short term accelerations, however, cause a bias (e.g. jump) in the measurement sequence, which unless compensated, results in divergence of the Kalman filter that provides estimates of target position and velocity, in turn leading to a loss of track. Accurate compensation for the bias requires processing more samples of the input signals which adds to the computational complexity. The waiting time for more samples can also result in a total loss of track since the target can begin a new maneuver and if the target begins a new maneuver before the first one is compensated for, the filter would never converge. Most of the proposed algorithms in the current literature hence have the disadvantage of losing the target in short term accelerations, i.e., when the duration of acceleration is comparable to the time period between the measurements. The time lag for maneuver modelings, which have been based on Bayesian probability calculations and linear estimation shall propose a neural network scheme for the modeling of target maneuvers. The primary motivation for employing compensation. The parallel processing capability of a properly trained neural network can permit fast processing of features to yield correct acceleration estimates and hence can take the burden off the primary Kalman filter which still provides the target position and velocity estimates.

  20. Adaptive DCT-based filtering of images corrupted by spatially correlated noise

    NASA Astrophysics Data System (ADS)

    Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Zelensky, Aleksandr A.; Astola, Jaakko T.; Egiazarian, Karen O.

    2008-02-01

    Majority of image filtering techniques are designed under assumption that noise is of special, a priori known type and it is i.i.d., i.e. spatially uncorrelated. However, in many practical situations the latter assumption is not true due to several reasons. Moreover, spatial correlation properties of noise might be rather different and a priori unknown. Then the assumption that noise is i.i.d. under real conditions of spatially correlated noise commonly leads to considerable decrease of a used filter effectiveness in comparison to a case if this spatial correlation is taken into account. Our paper deals with two basic aspects. The first one is how to modify a denoising algorithm, in particular, a discrete cosine transform (DCT) based filter in order to incorporate a priori or preliminarily obtained knowledge of spatial correlation characteristics of noise. The second aspect is how to estimate spatial correlation characteristics of noise for a given image with appropriate accuracy and robustness under condition that there is some a priori information about, at least, noise type and statistics like variance (for additive noise case) or relative variance (for multiplicative noise). We also present simulation results showing the effectiveness (the benefit) of taking into consideration noise correlation properties.

  1. Genome Filtering for New DNA Biomarkers of Loa loa Infection Suitable for Loop-Mediated Isothermal Amplification

    PubMed Central

    Poole, Catherine B.; Ettwiller, Laurence; Tanner, Nathan A.; Evans, Thomas C.; Wanji, Samuel; Carlow, Clotilde K. S.

    2015-01-01

    Loa loa infections have emerged as a serious public health problem in patients co-infected with Onchocerca volvulus or Wuchereria bancrofti because of severe adverse neurological reactions after treatment with ivermectin. Accurate diagnostic tests are needed for careful mapping in regions where mass drug administration is underway. Loop-mediated isothermal amplification (LAMP) has become a widely adopted screening method because of its operational simplicity, rapidity and versatility of visual detection readout options. Here, we present a multi-step bioinformatic pipeline to generate diagnostic candidates suitable for LAMP and experimentally validate this approach using one of the identified candidates to develop a species-specific LAMP assay for L. loa. The pipeline identified ~140 new L. loa specific DNA repeat families as putative biomarkers of infection. The consensus sequence of one family, repeat family 4 (RF4), was compiled from ~ 350 sequences dispersed throughout the L. loa genome and maps to a L. loa-specific region of the long terminal repeats found at the boundaries of Bel/Pao retrotransposons. PCR and LAMP primer sets targeting RF4 specifically amplified L. loa but not W. bancrofti, O. volvulus, Brugia malayi, human or mosquito DNA. RF4 LAMP detects the DNA equivalent of one microfilaria (100 pg) in 25–30 minutes and as little as 0.060 pg of L. loa DNA (~1/1600th of a microfilaria) purified from spiked blood samples in approximately 50 minutes. In summary, we have successfully employed a bioinformatic approach to mine the L. loa genome for species-specific repeat families that can serve as new DNA biomarkers for LAMP. The RF4 LAMP assay shows promise as a field tool for the implementation and management of mass drug administration programs and warrants further testing on clinical samples as the next stage in development towards this goal. PMID:26414073

  2. Genome Filtering for New DNA Biomarkers of Loa loa Infection Suitable for Loop-Mediated Isothermal Amplification.

    PubMed

    Poole, Catherine B; Ettwiller, Laurence; Tanner, Nathan A; Evans, Thomas C; Wanji, Samuel; Carlow, Clotilde K S

    2015-01-01

    Loa loa infections have emerged as a serious public health problem in patients co-infected with Onchocerca volvulus or Wuchereria bancrofti because of severe adverse neurological reactions after treatment with ivermectin. Accurate diagnostic tests are needed for careful mapping in regions where mass drug administration is underway. Loop-mediated isothermal amplification (LAMP) has become a widely adopted screening method because of its operational simplicity, rapidity and versatility of visual detection readout options. Here, we present a multi-step bioinformatic pipeline to generate diagnostic candidates suitable for LAMP and experimentally validate this approach using one of the identified candidates to develop a species-specific LAMP assay for L. loa. The pipeline identified ~140 new L. loa specific DNA repeat families as putative biomarkers of infection. The consensus sequence of one family, repeat family 4 (RF4), was compiled from ~ 350 sequences dispersed throughout the L. loa genome and maps to a L. loa-specific region of the long terminal repeats found at the boundaries of Bel/Pao retrotransposons. PCR and LAMP primer sets targeting RF4 specifically amplified L. loa but not W. bancrofti, O. volvulus, Brugia malayi, human or mosquito DNA. RF4 LAMP detects the DNA equivalent of one microfilaria (100 pg) in 25-30 minutes and as little as 0.060 pg of L. loa DNA (~1/1600th of a microfilaria) purified from spiked blood samples in approximately 50 minutes. In summary, we have successfully employed a bioinformatic approach to mine the L. loa genome for species-specific repeat families that can serve as new DNA biomarkers for LAMP. The RF4 LAMP assay shows promise as a field tool for the implementation and management of mass drug administration programs and warrants further testing on clinical samples as the next stage in development towards this goal. PMID:26414073

  3. An adaptive extended Kalman filter for fluorescence diffuse optical tomography of tumor pharmacokinetics

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Wu, Linhui; Yi, Xi; Zhang, Limin; Gao, Feng; Zhao, Huijuan

    2014-03-01

    According to the morphological differences in the vascularization between healthy and diseased tissues, pharmacokinetic-rate images of fluorophore can provide diagnostic information for tumor differentiation, and especially have the potential for staging of tumors. In this paper, fluorescence diffuse optical tomography method is firstly used to acquire metabolism-related time-course images of the fluorophore concentration. Based on a two-compartment model comprised of plasma and extracelluar-extravascular space, we next propose an adaptive-EKF framework to estimate the pharmacokinetic-rate images. With the aid of a forgetting factor, the adaptive-EKF compensate the inaccuracy initial values and emphasize the effect of the current data in order to realize a better online estimation compared with the conventional EKF. We use simulate data to evaluate the performance of the proposed methodology. The results suggest that the adaptive-EKF can obtain preferable pharmacokinetic-rate images than the conventional EKF with higher quantitativeness and noise robustness.

  4. High-Pass Filtering at Vestibular Frequencies by Transducer Adaptation in Mammalian Saccular Hair Cells

    NASA Astrophysics Data System (ADS)

    Songer, Jocelyn E.; Eatock, Ruth Anne

    2011-11-01

    The mammalian saccule detects head tilt and low-frequency head accelerations as well as higher-frequency bone vibrations and sounds. It has two different hair cell types, I and II, dispersed throughout two morphologically distinct regions, the striola and extrastriola. Afferents from the two zones have distinct response dynamics which may arise partly from zonal differences in hair cell properties. We find that type II hair cells in the rat saccular epithelium adapt with a time course appropriate for influencing afferent responses to head motions. Moreover, striolar type II hair cells adapted by a greater extent than extrastriolar type II hair cells and had greater phase leads in the mid-frequency range (5-50 Hz). These differences suggest that hair cell transduction may contribute to zonal differences in the adaptation of vestibular afferents to head motions.

  5. Modification of Loop 1 Affects the Nucleotide-Binding Properties of Myo1c, The Adaptation Motor in the Inner Ear†

    PubMed Central

    Adamek, Nancy; Lieto-Trivedi, Alena; Geeves, Michael A.; Coluccio, Lynne M.

    2010-01-01

    Myo1c is one of eight members of the mammalian myosin I family of actin-associated molecular motors. In stereocilia of the hair cells in the inner ear, Myo1c presumably serves as the adaptation motor, which regulates the opening and closing of transduction channels. Although there is conservation of sequence and structure among all myosins in the N-terminal motor domain, which contains the nucleotide- and actin-binding sites, some differences include the length and composition of surface loops, including loop 1, which lies near the nucleotide-binding domain. To investigate the role of loop 1, we expressed in insect cells mutants of a truncated form of Myo1c, Myo1c1IQ, as well as chimeras of Myo1c1IQ with the analogous loop from other myosins. We found that replacement of the charged residues in loop 1 with alanines or the whole loop with a series of alanines did not alter the ATPase activity, transient kinetics properties and Ca2+-sensitivity of Myo1c1IQ. Substitution of loop 1 with that of the corresponding region from tonic smooth muscle myosin II (Myo1c1IQ-tonic) or replacement with a single glycine (Myo1c1IQ-G) accelerated ADP release from A.M 2-3-fold in Ca2+, whereas substitution with loop 1 from phasic muscle myosin II (Myo1c1IQ-phasic) accelerated ADP release 35-fold. Motility assays with chimeras containing a single α-helix, or SAH, domain showed that Myo1cSAH-tonic translocated actin in vitro twice as fast as Myo1cSAH-WT and 3-fold faster than Myo1cSAH-G. The studies show that changes induced in Myo1c by modifying loop 1 showed no resemblance to the behaviour of the loop donor myosins or to the changes previously observed with similar Myo1b chimeras. PMID:20039646

  6. Automatic identification and removal of ocular artifacts in EEG--improved adaptive predictor filtering for portable applications.

    PubMed

    Zhao, Qinglin; Hu, Bin; Shi, Yujun; Li, Yang; Moore, Philip; Sun, Minghou; Peng, Hong

    2014-06-01

    Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. An essential component in EEG-based applications is the removal of Ocular Artifacts (OA) from the EEG signals. In this paper we propose a hybrid de-noising method combining Discrete Wavelet Transformation (DWT) and an Adaptive Predictor Filter (APF). A particularly novel feature of the proposed method is the use of the APF based on an adaptive autoregressive model for prediction of the waveform of signals in the ocular artifact zones. In our test, based on simulated data, the accuracy of noise removal in the proposed model was significantly increased when compared to existing methods including: Wavelet Packet Transform (WPT) and Independent Component Analysis (ICA), Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC). The results demonstrate that the proposed method achieved a lower mean square error and higher correlation between the original and corrected EEG. The proposed method has also been evaluated using data from calibration trials for the Online Predictive Tools for Intervention in Mental Illness (OPTIMI) project. The results of this evaluation indicate an improvement in performance in terms of the recovery of true EEG signals with EEG tracking and computational speed in the analysis. The proposed method is well suited to applications in portable environments where the constraints with respect to acceptable wearable sensor attachments usually dictate single channel devices. PMID:24802943

  7. An adaptive compensation algorithm for temperature drift of micro-electro-mechanical systems gyroscopes using a strong tracking Kalman filter.

    PubMed

    Feng, Yibo; Li, Xisheng; Zhang, Xiaojuan

    2015-01-01

    We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF), the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to -2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation. PMID:25985165

  8. An Adaptive Compensation Algorithm for Temperature Drift of Micro-Electro-Mechanical Systems Gyroscopes Using a Strong Tracking Kalman Filter

    PubMed Central

    Feng, Yibo; Li, Xisheng; Zhang, Xiaojuan

    2015-01-01

    We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF), the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to −2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation. PMID:25985165

  9. Adaptive-filtering of trisomy 21: risk of Down syndrome depends on family size and age of previous child

    NASA Astrophysics Data System (ADS)

    Neuhäuser, Markus; Krackow, Sven

    2007-02-01

    The neonatal incidence rate of Down syndrome (DS) is well-known to accelerate strongly with maternal age. This non-linearity renders mere accumulation of defects at recombination during prolonged first meiotic prophase implausible as an explanation for DS rate increase with maternal age, but might be anticipated from chromosomal drive (CD) for trisomy 21. Alternatively, as there is selection against genetically disadvantaged embryos, the screening system that eliminates embryos with trisomy 21 might decay with maternal age. In this paper, we provide the first evidence for relaxed filtering stringency (RFS) to represent an adaptive maternal response that could explain accelerating DS rates with maternal age. Using historical data, we show that the proportion of aberrant live births decrease with increased family size in older mothers, that inter-birth intervals are longer before affected neonates than before normal ones, and that primiparae exhibit elevated levels of DS incidence at higher age. These findings are predicted by adaptive RFS but cannot be explained by the currently available alternative non-adaptive hypotheses, including CD. The identification of the relaxation control mechanism and therapeutic restoration of a stringent screen may have considerable medical implications.

  10. A tunable electrochromic fabry-perot filter for adaptive optics applications.

    SciTech Connect

    Blaich, Jonathan David; Kammler, Daniel R.; Ambrosini, Andrea; Sweatt, William C.; Verley, Jason C.; Heller, Edwin J.; Yelton, William Graham

    2006-10-01

    The potential for electrochromic (EC) materials to be incorporated into a Fabry-Perot (FP) filter to allow modest amounts of tuning was evaluated by both experimental methods and modeling. A combination of chemical vapor deposition (CVD), physical vapor deposition (PVD), and electrochemical methods was used to produce an ECFP film stack consisting of an EC WO{sub 3}/Ta{sub 2}O{sub 5}/NiO{sub x}H{sub y} film stack (with indium-tin-oxide electrodes) sandwiched between two Si{sub 3}N{sub 4}/SiO{sub 2} dielectric reflector stacks. A process to produce a NiO{sub x}H{sub y} charge storage layer that freed the EC stack from dependence on atmospheric humidity and allowed construction of this complex EC-FP stack was developed. The refractive index (n) and extinction coefficient (k) for each layer in the EC-FP film stack was measured between 300 and 1700 nm. A prototype EC-FP filter was produced that had a transmission at 500 nm of 36%, and a FWHM of 10 nm. A general modeling approach that takes into account the desired pass band location, pass band width, required transmission and EC optical constants in order to estimate the maximum tuning from an EC-FP filter was developed. Modeling shows that minor thickness changes in the prototype stack developed in this project should yield a filter with a transmission at 600 nm of 33% and a FWHM of 9.6 nm, which could be tuned to 598 nm with a FWHM of 12.1 nm and a transmission of 16%. Additional modeling shows that if the EC WO{sub 3} absorption centers were optimized, then a shift from 600 nm to 598 nm could be made with a FWHM of 11.3 nm and a transmission of 20%. If (at 600 nm) the FWHM is decreased to 1 nm and transmission maintained at a reasonable level (e.g. 30%), only fractions of a nm of tuning would be possible with the film stack considered in this study. These tradeoffs may improve at other wavelengths or with EC materials different than those considered here. Finally, based on our limited investigation and material set

  11. Multiple Model Adaptive Two-Step Filter and Motion Tracking Sliding-Mode Guidance for Missiles with Time Lag in Acceleration

    NASA Astrophysics Data System (ADS)

    Zhou, Di; Zhang, Yong-An; Duan, Guang-Ren

    The two-step filter has been combined with a modified Sage-Husa time-varying measurement noise statistical estimator, which is able to estimate the covariance of measurement noise on line, to generate an adaptive two-step filter. In many practical applications such as the bearings-only guidance, some model parameters and the process noise covariance are also unknown a priori. Based on the adaptive two-step filter, we utilize multiple models in the first-step filtering as well as in the time update of the second-step filtering to handle the uncertainties of model parameters and process noise covariance. In each timestep of the multiple model filtering, probabilistic weights punishing the estimates of first-step state from different models, and their associated covariance matrices are acquired according to Bayes’ rule. The weighted sum of the estimates of first-step state and that of the associated covariance matrices are extracted as the ultimate estimate and covariance of the first-step state, and are used as measurement information for the measurement update of the second-step state. Thus there is still only one iteration process and no apparent enhancement of computation burden. A motion tracking sliding-mode guidance law is presented for missiles with non-negligible delays in actual acceleration. This guidance law guarantees guidance accuracy and is able to enhance observability in bearings-only tracking. In bearings-only cases, the multiple model adaptive two-step filter is applied to the motion tracking sliding-mode guidance law, supplying relative range, relative velocity, and target acceleration information. In simulation experiments satisfactory filtering and guidance results are obtained, even if the filter runs into unknown target maneuvers and unknown time-varying measurement noise covariance, and the guidance law has to deal with a large time lag in acceleration.

  12. A reevaluation of achromatic spatio-temporal vision: Nonoriented filters are monocular, they adapt, and can be used for decision making at high flicker speeds

    PubMed Central

    Meese, Tim S; Baker, Daniel H

    2011-01-01

    Masking, adaptation, and summation paradigms have been used to investigate the characteristics of early spatio-temporal vision. Each has been taken to provide evidence for (i) oriented and (ii) nonoriented spatial-filtering mechanisms. However, subsequent findings suggest that the evidence for nonoriented mechanisms has been misinterpreted: those experiments might have revealed the characteristics of suppression (eg, gain control), not excitation, or merely the isotropic subunits of the oriented detecting mechanisms. To shed light on this, we used all three paradigms to focus on the ‘high-speed’ corner of spatio-temporal vision (low spatial frequency, high temporal frequency), where cross-oriented achromatic effects are greatest. We used flickering Gabor patches as targets and a 2IFC procedure for monocular, binocular, and dichoptic stimulus presentations. To account for our results, we devised a simple model involving an isotropic monocular filter-stage feeding orientation-tuned binocular filters. Both filter stages are adaptable, and their outputs are available to the decision stage following nonlinear contrast transduction. However, the monocular isotropic filters (i) adapt only to high-speed stimuli—consistent with a magnocellular subcortical substrate—and (ii) benefit decision making only for high-speed stimuli (ie, isotropic monocular outputs are available only for high-speed stimuli). According to this model, the visual processes revealed by masking, adaptation, and summation are related but not identical. PMID:23145234

  13. An Adaptive Particle Filtering Approach to Tracking Modes in a Varying Shallow Ocean Environment

    SciTech Connect

    Candy, J V

    2011-03-22

    The shallow ocean environment is ever changing mostly due to temperature variations in its upper layers (< 100m) directly affecting sound propagation throughout. The need to develop processors that are capable of tracking these changes implies a stochastic as well as an 'adaptive' design. The stochastic requirement follows directly from the multitude of variations created by uncertain parameters and noise. Some work has been accomplished in this area, but the stochastic nature was constrained to Gaussian uncertainties. It has been clear for a long time that this constraint was not particularly realistic leading a Bayesian approach that enables the representation of any uncertainty distribution. Sequential Bayesian techniques enable a class of processors capable of performing in an uncertain, nonstationary (varying statistics), non-Gaussian, variable shallow ocean. In this paper adaptive processors providing enhanced signals for acoustic hydrophonemeasurements on a vertical array as well as enhanced modal function estimates are developed. Synthetic data is provided to demonstrate that this approach is viable.

  14. Suppression of Rayleigh backscattering noise using cascaded-SOA and microwave photonic filter for 10 Gb/s loop-back WDM-PON.

    PubMed

    Feng, Hanlin; Ge, Jia; Xiao, Shilin; Fok, Mable P

    2014-05-19

    In this paper, we present a novel Rayleigh backscattering (RB) noise mitigation scheme based on central carrier suppression for 10 Gb/s loop-back wavelength division multiplexing passive optical network (WDM-PON). Microwave modulated multi-subcarrier optical signal is used as downstream seeding light, while cascaded semiconductor optical amplifier (SOA) are used in the optical network unit (ONU) for suppressing the central carrier of the multi-subcarrier upstream signal. With central carrier suppression, interference generated by carrier RB noise at low frequency region is eliminated successfully. Transmission performance over 45 km single mode fiber (SMF) is studied experimentally, and the optical-signal-to-Rayleigh-noise-ratio (OSRNR) can be reduced to 15 dB with central carrier suppression ratio (CCSR) of 21 dB. Receiver sensitivity is further improved by 6 dB with the use of microwave photonic filter (MPF) for suppressing residual upstream microwave signal and residual carrier RB at high frequency region. PMID:24921298

  15. Simulation of underresolved turbulent flows by adaptive filtering using the high order discontinuous Galerkin spectral element method

    NASA Astrophysics Data System (ADS)

    Flad, David; Beck, Andrea; Munz, Claus-Dieter

    2016-05-01

    Scale-resolving simulations of turbulent flows in complex domains demand accurate and efficient numerical schemes, as well as geometrical flexibility. For underresolved situations, the avoidance of aliasing errors is a strong demand for stability. For continuous and discontinuous Galerkin schemes, an effective way to prevent aliasing errors is to increase the quadrature precision of the projection operator to account for the non-linearity of the operands (polynomial dealiasing, overintegration). But this increases the computational costs extensively. In this work, we present a novel spatially and temporally adaptive dealiasing strategy by projection filtering. We show this to be more efficient for underresolved turbulence than the classical overintegration strategy. For this novel approach, we discuss the implementation strategy and the indicator details, show its accuracy and efficiency for a decaying homogeneous isotropic turbulence and the transitional Taylor-Green vortex and compare it to the original overintegration approach and a state of the art variational multi-scale eddy viscosity formulation.

  16. An optimized DSP implementation of adaptive filtering and ICA for motion artifact reduction in ambulatory ECG monitoring.

    PubMed

    Berset, Torfinn; Geng, Di; Romero, Iñaki

    2012-01-01

    Noise from motion artifacts is currently one of the main challenges in the field of ambulatory ECG recording. To address this problem, we propose the use of two different approaches. First, an adaptive filter with electrode-skin impedance as a reference signal is described. Secondly, a multi-channel ECG algorithm based on Independent Component Analysis is introduced. Both algorithms have been designed and further optimized for real-time work embedded in a dedicated Digital Signal Processor. We show that both algorithms improve the performance of a beat detection algorithm when applied in high noise conditions. In addition, an efficient way of choosing this methods is suggested with the aim of reduce the overall total system power consumption. PMID:23367417

  17. Computationally Efficient Locally Adaptive Demosaicing of Color Filter Array Images Using the Dual-Tree Complex Wavelet Packet Transform

    PubMed Central

    Aelterman, Jan; Goossens, Bart; De Vylder, Jonas; Pižurica, Aleksandra; Philips, Wilfried

    2013-01-01

    Most digital cameras use an array of alternating color filters to capture the varied colors in a scene with a single sensor chip. Reconstruction of a full color image from such a color mosaic is what constitutes demosaicing. In this paper, a technique is proposed that performs this demosaicing in a way that incurs a very low computational cost. This is done through a (dual-tree complex) wavelet interpretation of the demosaicing problem. By using a novel locally adaptive approach for demosaicing (complex) wavelet coefficients, we show that many of the common demosaicing artifacts can be avoided in an efficient way. Results demonstrate that the proposed method is competitive with respect to the current state of the art, but incurs a lower computational cost. The wavelet approach also allows for computationally effective denoising or deblurring approaches. PMID:23671575

  18. Distributed parameter system coupled ARMA expansion identification and adaptive parallel IIR filtering - A unified problem statement. [Auto Regressive Moving-Average

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Balas, M. J.

    1980-01-01

    A novel interconnection of distributed parameter system (DPS) identification and adaptive filtering is presented, which culminates in a common statement of coupled autoregressive, moving-average expansion or parallel infinite impulse response configuration adaptive parameterization. The common restricted complexity filter objectives are seen as similar to the reduced-order requirements of the DPS expansion description. The interconnection presents the possibility of an exchange of problem formulations and solution approaches not yet easily addressed in the common finite dimensional lumped-parameter system context. It is concluded that the shared problems raised are nevertheless many and difficult.

  19. Mie Light-Scattering Granulometer with an Adaptive Numerical Filtering Method. II. Experiments.

    PubMed

    Hespel, L; Delfour, A; Guillame, B

    2001-02-20

    A nephelometer is presented that theoretically requires no absolute calibration. This instrument is used for determining the particle-size distribution of various scattering media (aerosols, fogs, rocket exhausts, engine plumes, and the like) from angular static light-scattering measurements. An inverse procedure is used, which consists of a least-squares method and a regularization scheme based on numerical filtering. To retrieve the distribution function one matches the experimental data with theoretical patterns derived from Mie theory. The main principles of the inverse method are briefly presented, and the nephelometer is then described with the associated partial calibration procedure. Finally, the whole granulometer system (inverse method and nephelometer) is validated by comparison of measurements of scattering media with calibrated monodisperse or known size distribution functions. PMID:18357082

  20. Signal quality improvement of holographic data storage using adaptive two-dimensional filter

    NASA Astrophysics Data System (ADS)

    Takahata, Yosuke; Kondo, Yo; Yoshida, Shuhei; Yamamoto, Manabu

    2010-05-01

    Holographic data storage is being widely studied for the purpose of developing next-generation large optical memories. A prospective use of this type of memory is in building image archives in large-scale data centers. In particular, demand for energy conservation at data centers, and therefore for holographic data storage, is growing. In holographic data storage, interference between bits occurs owing to wave aberration in the optical system, shrinkage of the medium, and crosstalk noise from neighboring holograms during multiplex recording; as a result of the interference, the reproduced image deteriorates and the bit error rate (BER) increases. In this study, to reduce the BER in both off-axis-type recording and coaxial-type recording, a two-dimensional finite impulse response (FIR) filter is applied to a reproduced image that has been recorded by angle multiplex recording and shift multiplex recording. First, for the optimization of the FIR filter coefficients, the linear minimum mean square error (LMMSE) method is applied; this method optimizes the coefficients by reducing the BER. Furthermore, for evaluating the optimization performance of the LMMSE method, the optimization performance is compared with that of the real-coded genetic algorithm (RCGA), which has the capability to search a wide range of coefficients. The optimization by the LMMSE method has been found to be excellent for off-axis-type recording but not for coaxial-type recording. It is speculated that this is because of the brightness irregularity in the reproduced image, resulting from crosstalk. On the other hand, a marked reduction in the BER is observed using the RCGA, despite the brightness irregularity. In this study, the effectiveness of the LMMSE method for signals recorded by coaxial-type recording, in which large brightness irregularity is expected, is examined using automatic gain control (AGC). It is found that the application of AGC reduces the BER even in the case of coaxial

  1. Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain–computer interface to a virtual reality avatar

    NASA Astrophysics Data System (ADS)

    Phat Luu, Trieu; He, Yongtian; Brown, Samuel; Nakagame, Sho; Contreras-Vidal, Jose L.

    2016-06-01

    Objective. The control of human bipedal locomotion is of great interest to the field of lower-body brain–computer interfaces (BCIs) for gait rehabilitation. While the feasibility of closed-loop BCI systems for the control of a lower body exoskeleton has been recently shown, multi-day closed-loop neural decoding of human gait in a BCI virtual reality (BCI-VR) environment has yet to be demonstrated. BCI-VR systems provide valuable alternatives for movement rehabilitation when wearable robots are not desirable due to medical conditions, cost, accessibility, usability, or patient preferences. Approach. In this study, we propose a real-time closed-loop BCI that decodes lower limb joint angles from scalp electroencephalography (EEG) during treadmill walking to control a walking avatar in a virtual environment. Fluctuations in the amplitude of slow cortical potentials of EEG in the delta band (0.1–3 Hz) were used for prediction; thus, the EEG features correspond to time-domain amplitude modulated potentials in the delta band. Virtual kinematic perturbations resulting in asymmetric walking gait patterns of the avatar were also introduced to investigate gait adaptation using the closed-loop BCI-VR system over a period of eight days. Main results. Our results demonstrate the feasibility of using a closed-loop BCI to learn to control a walking avatar under normal and altered visuomotor perturbations, which involved cortical adaptations. The average decoding accuracies (Pearson’s r values) in real-time BCI across all subjects increased from (Hip: 0.18 ± 0.31 Knee: 0.23 ± 0.33 Ankle: 0.14 ± 0.22) on Day 1 to (Hip: 0.40 ± 0.24 Knee: 0.55 ± 0.20 Ankle: 0.29 ± 0.22) on Day 8. Significance. These findings have implications for the development of a real-time closed-loop EEG-based BCI-VR system for gait rehabilitation after stroke and for understanding cortical plasticity induced by a closed-loop BCI-VR system.

  2. Local ensemble transform Kalman filter, a fast non-stationary control law for adaptive optics on ELTs: theoretical aspects and first simulation results.

    PubMed

    Gray, Morgan; Petit, Cyril; Rodionov, Sergey; Bocquet, Marc; Bertino, Laurent; Ferrari, Marc; Fusco, Thierry

    2014-08-25

    We propose a new algorithm for an adaptive optics system control law, based on the Linear Quadratic Gaussian approach and a Kalman Filter adaptation with localizations. It allows to handle non-stationary behaviors, to obtain performance close to the optimality defined with the residual phase variance minimization criterion, and to reduce the computational burden with an intrinsically parallel implementation on the Extremely Large Telescopes (ELTs). PMID:25321291

  3. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images

    PubMed Central

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-01-01

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

  4. Filtering Based Adaptive Visual Odometry Sensor Framework Robust to Blurred Images.

    PubMed

    Zhao, Haiying; Liu, Yong; Xie, Xiaojia; Liao, Yiyi; Liu, Xixi

    2016-01-01

    Visual odometry (VO) estimation from blurred image is a challenging problem in practical robot applications, and the blurred images will severely reduce the estimation accuracy of the VO. In this paper, we address the problem of visual odometry estimation from blurred images, and present an adaptive visual odometry estimation framework robust to blurred images. Our approach employs an objective measure of images, named small image gradient distribution (SIGD), to evaluate the blurring degree of the image, then an adaptive blurred image classification algorithm is proposed to recognize the blurred images, finally we propose an anti-blurred key-frame selection algorithm to enable the VO robust to blurred images. We also carried out varied comparable experiments to evaluate the performance of the VO algorithms with our anti-blur framework under varied blurred images, and the experimental results show that our approach can achieve superior performance comparing to the state-of-the-art methods under the condition with blurred images while not increasing too much computation cost to the original VO algorithms. PMID:27399704

  5. Robust fundamental frequency estimation in sustained vowels: Detailed algorithmic comparisons and information fusion with adaptive Kalman filtering

    PubMed Central

    Tsanas, Athanasios; Zañartu, Matías; Little, Max A.; Fox, Cynthia; Ramig, Lorraine O.; Clifford, Gari D.

    2014-01-01

    There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F0) of speech signals. This study examines ten F0 estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F0 in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F0 estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F0 estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F0 estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F0 estimation is required. PMID:24815269

  6. ASICs Approach for the Implementation of a Symmetric Triangular Fuzzy Coprocessor and Its Application to Adaptive Filtering

    NASA Technical Reports Server (NTRS)

    Starks, Scott; Abdel-Hafeez, Saleh; Usevitch, Bryan

    1997-01-01

    This paper discusses the implementation of a fuzzy logic system using an ASICs design approach. The approach is based upon combining the inherent advantages of symmetric triangular membership functions and fuzzy singleton sets to obtain a novel structure for fuzzy logic system application development. The resulting structure utilizes a fuzzy static RAM to store the rule-base and the end-points of the triangular membership functions. This provides advantages over other approaches in which all sampled values of membership functions for all universes must be stored. The fuzzy coprocessor structure implements the fuzzification and defuzzification processes through a two-stage parallel pipeline architecture which is capable of executing complex fuzzy computations in less than 0.55us with an accuracy of more than 95%, thus making it suitable for a wide range of applications. Using the approach presented in this paper, a fuzzy logic rule-base can be directly downloaded via a host processor to an onchip rule-base memory with a size of 64 words. The fuzzy coprocessor's design supports up to 49 rules for seven fuzzy membership functions associated with each of the chip's two input variables. This feature allows designers to create fuzzy logic systems without the need for additional on-board memory. Finally, the paper reports on simulation studies that were conducted for several adaptive filter applications using the least mean squared adaptive algorithm for adjusting the knowledge rule-base.

  7. Robust fundamental frequency estimation in sustained vowels: detailed algorithmic comparisons and information fusion with adaptive Kalman filtering.

    PubMed

    Tsanas, Athanasios; Zañartu, Matías; Little, Max A; Fox, Cynthia; Ramig, Lorraine O; Clifford, Gari D

    2014-05-01

    There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F(0)) of speech signals. This study examines ten F(0) estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F(0) in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F(0) estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F(0) estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F(0) estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F(0) estimation is required. PMID:24815269

  8. A multiresolution approach to image enhancement via histogram shaping and adaptive Wiener filtering

    NASA Astrophysics Data System (ADS)

    Pace, T.; Manville, D.; Lee, H.; Cloud, G.; Puritz, J.

    2008-04-01

    It is critical in military applications to be able to extract features in imagery that may be of interest to the viewer at any time of the day or night. Infrared (IR) imagery is ideally suited for producing these types of images. However, even under the best of circumstances, the traditional approach of applying a global automatic gain control (AGC) to the digital image may not provide the user with local area details that may be of interest. Processing the imagery locally can enhance additional features and characteristics in the image which provide the viewer with an improved understanding of the scene being observed. This paper describes a multi-resolution pyramid approach for decomposing an image, enhancing its contrast by remapping the histograms to desired pdfs, filtering them and recombining them to create an output image with much more visible detail than the input image. The technique improves the local area image contrast in light and dark areas providing the warfighter with significantly improved situational awareness.

  9. Background adaptive division filtering for hand-held ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Lee, Matthew A.; Anderson, Derek T.; Ball, John E.; White, Julie L.

    2016-05-01

    The challenge in detecting explosive hazards is that there are multiple types of targets buried at different depths in a highlycluttered environment. A wide array of target and clutter signatures exist, which makes detection algorithm design difficult. Such explosive hazards are typically deployed in past and present war zones and they pose a grave threat to the safety of civilians and soldiers alike. This paper focuses on a new image enhancement technique for hand-held ground penetrating radar (GPR). Advantages of the proposed technique is it runs in real-time and it does not require the radar to remain at a constant distance from the ground. Herein, we evaluate the performance of the proposed technique using data collected from a U.S. Army test site, which includes targets with varying amounts of metal content, placement depths, clutter and times of day. Receiver operating characteristic (ROC) curve-based results are presented for the detection of shallow, medium and deeply buried targets. Preliminary results are very encouraging and they demonstrate the usefulness of the proposed filtering technique.

  10. The algorithm analysis on non-uniformity correction based on LMS adaptive filtering

    NASA Astrophysics Data System (ADS)

    Zhan, Dongjun; Wang, Qun; Wang, Chensheng; Chen, Huawang

    2010-11-01

    The traditional least mean square (LMS) algorithm has the performance of good adaptivity to noise, but there are several disadvantages in the traditional LMS algorithm, such as the defect in desired value of pending pixels, undetermined original coefficients, which result in slow convergence speed and long convergence period. Method to solve the desired value of pending pixel has improved based on these problems, also, the correction gain and offset coefficients worked out by the method of two-point temperature non-uniformity correction (NUC) as the original coefficients, which has improved the convergence speed. The simulation with real infrared images has proved that the new LMS algorithm has the advantages of better correction effect. Finally, the algorithm is implemented on the hardware structure of FPGA+DSP.

  11. Adaptive Iterated Extended Kalman Filter and Its Application to Autonomous Integrated Navigation for Indoor Robot

    PubMed Central

    Chen, Xiyuan; Li, Qinghua

    2014-01-01

    As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve the accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF) which used the noise statistics estimator in the iterated extended Kalman (IEKF), and then AIEKF is used to deal with the nonlinear problem in the inertial navigation systems (INS)/wireless sensors networks (WSNs)-integrated navigation system. Practical test has been done to evaluate the performance of the proposed method. The results show that the proposed method is effective to reduce the mean root-mean-square error (RMSE) of position by about 92.53%, 67.93%, 55.97%, and 30.09% compared with the INS only, WSN, EKF, and IEKF. PMID:24693225

  12. Adaptive iterated extended Kalman filter and its application to autonomous integrated navigation for indoor robot.

    PubMed

    Xu, Yuan; Chen, Xiyuan; Li, Qinghua

    2014-01-01

    As the core of the integrated navigation system, the data fusion algorithm should be designed seriously. In order to improve the accuracy of data fusion, this work proposed an adaptive iterated extended Kalman (AIEKF) which used the noise statistics estimator in the iterated extended Kalman (IEKF), and then AIEKF is used to deal with the nonlinear problem in the inertial navigation systems (INS)/wireless sensors networks (WSNs)-integrated navigation system. Practical test has been done to evaluate the performance of the proposed method. The results show that the proposed method is effective to reduce the mean root-mean-square error (RMSE) of position by about 92.53%, 67.93%, 55.97%, and 30.09% compared with the INS only, WSN, EKF, and IEKF. PMID:24693225

  13. Optimization of exposure in panoramic radiography while maintaining image quality using adaptive filtering.

    PubMed

    Svenson, Björn; Larsson, Lars; Båth, Magnus

    2016-01-01

    Objective The purpose of the present study was to investigate the potential of using advanced external adaptive image processing for maintaining image quality while reducing exposure in dental panoramic storage phosphor plate (SPP) radiography. Materials and methods Thirty-seven SPP radiographs of a skull phantom were acquired using a Scanora panoramic X-ray machine with various tube load, tube voltage, SPP sensitivity and filtration settings. The radiographs were processed using General Operator Processor (GOP) technology. Fifteen dentists, all within the dental radiology field, compared the structural image quality of each radiograph with a reference image on a 5-point rating scale in a visual grading characteristics (VGC) study. The reference image was acquired with the acquisition parameters commonly used in daily operation (70 kVp, 150 mAs and sensitivity class 200) and processed using the standard process parameters supplied by the modality vendor. Results All GOP-processed images with similar (or higher) dose as the reference image resulted in higher image quality than the reference. All GOP-processed images with similar image quality as the reference image were acquired at a lower dose than the reference. This indicates that the external image processing improved the image quality compared with the standard processing. Regarding acquisition parameters, no strong dependency of the image quality on the radiation quality was seen and the image quality was mainly affected by the dose. Conclusions The present study indicates that advanced external adaptive image processing may be beneficial in panoramic radiography for increasing the image quality of SPP radiographs or for reducing the exposure while maintaining image quality. PMID:26478956

  14. Skylab communications carrier 16536G and filter bypass adapter assembly 12535G. [development of communications equipment for use with Skylab spacecraft

    NASA Technical Reports Server (NTRS)

    1974-01-01

    Communications equipment for use with the Skylab project is examined to show compliance with contract requirements. The items of equipment considered are: (1) communications carrier assemblies, (2) filter bypass adapter assemblies, and (3) sub-assemblies, parts, and repairs. Additional information is provided concerning contract requirements, test requirements, and failure investigation actions.

  15. Aortic pressure wave reconstruction during exercise is improved by adaptive filtering: a pilot study.

    PubMed

    Stok, Wim J; Westerhof, Berend E; Guelen, Ilja; Karemaker, John M

    2011-08-01

    Reconstruction of central aortic pressure from a peripheral measurement by a generalized transfer function (genTF) works well at rest and mild exercise at lower heart rates, but becomes less accurate during heavy exercise. Particularly, systolic and pulse pressure estimations deteriorate, thereby underestimating central pressure. We tested individualization of the TF (indTF) by adapting its resonance frequency at the various levels of exercise. In seven males (age 44-57) with coronary artery disease, central and peripheral pressures were measured simultaneously. The optimal resonance frequency was predicted from regression formulas using variables derived from the individual's peripheral pressure pulse, including a pulse contour estimation of cardiac output (pcCO). In addition, reconstructed pressures were calibrated to central mean and diastolic pressure at each exercise level. Using a genTF and without calibration, the error in estimated aortic pulse pressure was -7.5 ± 6.4 mmHg, which was reduced to 0.2 ± 5.7 mmHg with the indTFs using pcCO for prediction. Calibration resulted in less scatter at the cost of a small bias (2.7 mmHg). In exercise, the indTFs predict systolic and pulse pressure better than the genTF. This pilot study shows that it is possible to individualize the peripheral to aortic pressure transfer function, thereby improving accuracy in central blood pressure assessment during exercise. PMID:21720842

  16. Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals.

    PubMed

    Dadashi, Farzin; Crettenand, Florent; Millet, Grégoire P; Seifert, Ludovic; Komar, John; Aminian, Kamiar

    2013-01-01

    This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based system. Three waterproofed IMUs (composed of 3D accelerometer, 3D gyroscope) were placed on both forearms and the sacrum of the swimmer. We used two underwater video cameras in side and frontal views as our reference system. Two independent operators performed the video analysis. To test our methodology, seven well-trained swimmers performed three 300 m trials in a 50 m indoor pool. Each trial was in a different coordination mode quantified by the index of coordination. We detected different phases of the arm stroke by employing orientation estimation techniques and a new adaptive change detection algorithm on inertial signals. The difference of 0.2 ± 3.9% between our estimation and video-based system in assessment of the index of coordination was comparable to experienced operators' difference (1.1 ± 3.6%). The 95% limits of agreement of the difference between the two systems in estimation of the temporal phases were always less than 7.9% of the cycle duration. The inertial system offers an automatic easy-to-use system with timely feedback for the study of swimming. PMID:23560703

  17. Insect-Inspired Self-Motion Estimation with Dense Flow Fields—An Adaptive Matched Filter Approach

    PubMed Central

    Strübbe, Simon; Stürzl, Wolfgang; Egelhaaf, Martin

    2015-01-01

    The control of self-motion is a basic, but complex task for both technical and biological systems. Various algorithms have been proposed that allow the estimation of self-motion from the optic flow on the eyes. We show that two apparently very different approaches to solve this task, one technically and one biologically inspired, can be transformed into each other under certain conditions. One estimator of self-motion is based on a matched filter approach; it has been developed to describe the function of motion sensitive cells in the fly brain. The other estimator, the Koenderink and van Doorn (KvD) algorithm, was derived analytically with a technical background. If the distances to the objects in the environment can be assumed to be known, the two estimators are linear and equivalent, but are expressed in different mathematical forms. However, for most situations it is unrealistic to assume that the distances are known. Therefore, the depth structure of the environment needs to be determined in parallel to the self-motion parameters and leads to a non-linear problem. It is shown that the standard least mean square approach that is used by the KvD algorithm leads to a biased estimator. We derive a modification of this algorithm in order to remove the bias and demonstrate its improved performance by means of numerical simulations. For self-motion estimation it is beneficial to have a spherical visual field, similar to many flying insects. We show that in this case the representation of the depth structure of the environment derived from the optic flow can be simplified. Based on this result, we develop an adaptive matched filter approach for systems with a nearly spherical visual field. Then only eight parameters about the environment have to be memorized and updated during self-motion. PMID:26308839

  18. Assembly Processes under Severe Abiotic Filtering: Adaptation Mechanisms of Weed Vegetation to the Gradient of Soil Constraints

    PubMed Central

    Nikolic, Nina; Böcker, Reinhard; Kostic-Kravljanac, Ljiljana; Nikolic, Miroslav

    2014-01-01

    Questions Effects of soil on vegetation patterns are commonly obscured by other environmental factors; clear and general relationships are difficult to find. How would community assembly processes be affected by a substantial change in soil characteristics when all other relevant factors are held constant? In particular, can we identify some functional adaptations which would underpin such soil-induced vegetation response? Location Eastern Serbia: fields partially damaged by long-term and large-scale fluvial deposition of sulphidic waste from a Cu mine; subcontinental/submediterranean climate. Methods We analysed the multivariate response of cereal weed assemblages (including biomass and foliar analyses) to a strong man-made soil gradient (from highly calcareous to highly acidic, nutrient-poor soils) over short distances (field scale). Results The soil gradient favoured a substitution of calcicoles by calcifuges, and an increase in abundance of pseudometallophytes, with preferences for Atlantic climate, broad geographical distribution, hemicryptophytic life form, adapted to low-nutrient and acidic soils, with lower concentrations of Ca, and very narrow range of Cu concentrations in leaves. The trends of abundance of the different ecological groups of indicator species along the soil gradient were systematically reflected in the maintenance of leaf P concentrations, and strong homeostasis in biomass N:P ratio. Conclusion Using annual weed vegetation at the field scale as a fairly simple model, we demonstrated links between gradients in soil properties (pH, nutrient availability) and floristic composition that are normally encountered over large geographic distances. We showed that leaf nutrient status, in particular the maintenance of leaf P concentrations and strong homeostasis of biomass N:P ratio, underpinned a clear functional response of vegetation to mineral stress. These findings can help to understand assembly processes leading to unusual, novel combinations

  19. A Simplified Baseband Prefilter Model with Adaptive Kalman Filter for Ultra-Tight COMPASS/INS Integration

    PubMed Central

    Luo, Yong; Wu, Wenqi; Babu, Ravindra; Tang, Kanghua; Luo, Bing

    2012-01-01

    COMPASS is an indigenously developed Chinese global navigation satellite system and will share many features in common with GPS (Global Positioning System). Since the ultra-tight GPS/INS (Inertial Navigation System) integration shows its advantage over independent GPS receivers in many scenarios, the federated ultra-tight COMPASS/INS integration has been investigated in this paper, particularly, by proposing a simplified prefilter model. Compared with a traditional prefilter model, the state space of this simplified system contains only carrier phase, carrier frequency and carrier frequency rate tracking errors. A two-quadrant arctangent discriminator output is used as a measurement. Since the code tracking error related parameters were excluded from the state space of traditional prefilter models, the code/carrier divergence would destroy the carrier tracking process, and therefore an adaptive Kalman filter algorithm tuning process noise covariance matrix based on state correction sequence was incorporated to compensate for the divergence. The federated ultra-tight COMPASS/INS integration was implemented with a hardware COMPASS intermediate frequency (IF), and INS's accelerometers and gyroscopes signal sampling system. Field and simulation test results showed almost similar tracking and navigation performances for both the traditional prefilter model and the proposed system; however, the latter largely decreased the computational load. PMID:23012564

  20. Higher-order ambulatory electrocardiogram identification and motion artifact suppression with adaptive second- and third-order Volterra filters

    NASA Astrophysics Data System (ADS)

    Sabry-Rizk, Madiha; Zgallai, Walid; El-Khafif, Sahar; Carson, Ewart; Grattan, Kenneth T. V.

    1998-10-01

    The objective of this paper is to demonstrate how, in a few seconds, a relatively simple ECG monitor, PC and advanced signal processing algorithms could pinpoint microvolts - late potentials - result from an infarct zone in the heart and is used as an indicator in identifying patients prone to ventricular tachycardia which, if left untreated, leads to ventricular fibrillation. We will characterize recorded ECG data obtained from the standard three vector electrodes during exercise in terms of their higher-order statistical features. Essentially we use adaptive LMS- and Kalman-based second- and third-order Volterra filters to model the non- linear low-frequency P and T waves and motion artifacts which might overlap with the QRS complex and lead to false positive QRS detection. We will illustrate the effectiveness of this new approach by mapping out bispectral regions with a strong bicoherence manifestation and showing their corresponding temporal/spatial origins. Furthermore, we will present a few examples of our own application of these non-invasive techniques to illustrate what we see as their promise for analysis of heart abnormality.

  1. Adaptive Volterra filter with continuous lp-norm using a logarithmic cost for nonlinear active noise control

    NASA Astrophysics Data System (ADS)

    Lu, Lu; Zhao, Haiquan

    2016-03-01

    The filtered-x least mean lp-norm (FxLMP) algorithm is proven to be useful for nonlinear active noise control (NANC) systems. However, its performance deteriorates when the impulsive noises are presented in NANC systems. To surmount this shortcoming, a new nonlinear adaptive algorithm based on Volterra expansion model (VFxlogLMP) is developed in this paper, which is derived by minimizing the lp-norm of logarithmic cost. It is found that the FxLMP and VFxlogLMP require to select an appropriate value of p according to the prior information on noise characteristics, which prohibit their practical applications. Based on VFxlogLMP algorithm, we proposed a continuous lp-norm algorithm with logarithmic cost (VFxlogCLMP), which does not need the parameter selection and thresholds estimation. Benefiting from the various error norms for 1≤p≤2, it remains the robustness of VFxlogLMP. Moreover, the convergence behavior of VFxlogCLMP for moving average secondary paths and stochastic input signals is performed. Compared to the existing algorithms, two versions of the proposed algorithms have much better convergence and stability in impulsive noise environments.

  2. Adaptive match filter based method for time vs. amplitude characterization of microvolt ECG T-wave alternans.

    PubMed

    Burattini, Laura; Zareba, Wojciech; Burattini, Roberto

    2008-09-01

    To develop a new method for non-invasive identification of patients prone to ventricular tachyarrhythmia and sudden cardiac death, an adaptive match-filter (AMF) was applied to detect and characterize T-wave alternans (TWA) in 200 coronary artery diseased (CAD) patients compared with 176 healthy (H) subjects. TWA was characterized in terms of duration (TWAD), amplitude (TWAA), and magnitude (TWAM, defined as the product of TWAD times TWAA). A criterion derived from these parameters, estimated over the H-population, allowed discrimination between a risk (TWA+) and a normality (NO TWA) zone in the TWAD-TWAA plane. To gain further ability to discriminate among different risk levels, the TWA+ zone was divided into four sub-zones respectively characterized by low duration and low amplitude (LDLA), low duration and high amplitude (LDHA), high duration and low amplitude (HDLA), and high duration and high amplitude (HDHA). With our methodology, 21 CAD-patients (10.5%) were identified as TWA+, 9 falling in the LDLA zone, 4 in the HDLA, 7 in the LDHA, and 1 in the HDHA. These results are in agreement with clinical expectations and pave the way to further clinical follow-up studies finalized to analyze pathophysiological implications and risk factors associated to each TWA+ zone. PMID:18618261

  3. Closed-Loop Neuroprosthesis for Reach-to-Grasp Assistance: Combining Adaptive Multi-channel Neuromuscular Stimulation with a Multi-joint Arm Exoskeleton

    PubMed Central

    Grimm, Florian; Gharabaghi, Alireza

    2016-01-01

    Stroke patients with severe motor deficits cannot execute task-oriented rehabilitation exercises with their affected upper extremity. Advanced rehabilitation technology may support them in performing such reach-to-grasp movements. The challenge is, however, to provide assistance as needed, while maintaining the participants' commitment during the exercises. In this feasibility study, we introduced a closed-loop neuroprosthesis for reach-to-grasp assistance which combines adaptive multi-channel neuromuscular stimulation with a multi-joint arm exoskeleton. Eighteen severely affected chronic stroke patients were assisted by a gravity-compensating, seven-degree-of-freedom exoskeleton which was attached to the paretic arm for performing reach-to-grasp exercises resembling activities of daily living in a virtual environment. During the exercises, adaptive electrical stimulation was applied to seven different muscles of the upper extremity in a performance-dependent way to enhance the task-oriented movement trajectory. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. Closed-loop neuromuscular stimulation could be well integrated into the exoskeleton-based training, and increased the task-related range of motion (p = 0.0004) and movement velocity (p = 0.015), while preserving accuracy. The highest relative stimulation intensity was required to facilitate the grasping function. The facilitated range of motion correlated with the upper extremity Fugl-Meyer Assessment score of the patients (p = 0.028). Combining adaptive multi-channel neuromuscular stimulation with antigravity assistance amplifies the residual motor capabilities of severely affected stroke patients during rehabilitation exercises and may thus provide a customized training environment for patient-tailored support while preserving the participants' engagement. PMID:27445658

  4. Closed-Loop Neuroprosthesis for Reach-to-Grasp Assistance: Combining Adaptive Multi-channel Neuromuscular Stimulation with a Multi-joint Arm Exoskeleton.

    PubMed

    Grimm, Florian; Gharabaghi, Alireza

    2016-01-01

    Stroke patients with severe motor deficits cannot execute task-oriented rehabilitation exercises with their affected upper extremity. Advanced rehabilitation technology may support them in performing such reach-to-grasp movements. The challenge is, however, to provide assistance as needed, while maintaining the participants' commitment during the exercises. In this feasibility study, we introduced a closed-loop neuroprosthesis for reach-to-grasp assistance which combines adaptive multi-channel neuromuscular stimulation with a multi-joint arm exoskeleton. Eighteen severely affected chronic stroke patients were assisted by a gravity-compensating, seven-degree-of-freedom exoskeleton which was attached to the paretic arm for performing reach-to-grasp exercises resembling activities of daily living in a virtual environment. During the exercises, adaptive electrical stimulation was applied to seven different muscles of the upper extremity in a performance-dependent way to enhance the task-oriented movement trajectory. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. Closed-loop neuromuscular stimulation could be well integrated into the exoskeleton-based training, and increased the task-related range of motion (p = 0.0004) and movement velocity (p = 0.015), while preserving accuracy. The highest relative stimulation intensity was required to facilitate the grasping function. The facilitated range of motion correlated with the upper extremity Fugl-Meyer Assessment score of the patients (p = 0.028). Combining adaptive multi-channel neuromuscular stimulation with antigravity assistance amplifies the residual motor capabilities of severely affected stroke patients during rehabilitation exercises and may thus provide a customized training environment for patient-tailored support while preserving the participants' engagement. PMID:27445658

  5. Adaptive optical filter

    DOEpatents

    Whittemore, Stephen Richard

    2013-09-10

    Imaging systems include a detector and a spatial light modulator (SLM) that is coupled so as to control image intensity at the detector based on predetermined detector limits. By iteratively adjusting SLM element values, image intensity at one or all detector elements or portions of an imaging detector can be controlled to be within limits. The SLM can be secured to the detector at a spacing such that the SLM is effectively at an image focal plane. In some applications, the SLM can be adjusted to impart visible or hidden watermarks to images or to reduce image intensity at one or a selected set of detector elements so as to reduce detector blooming

  6. Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

    NASA Technical Reports Server (NTRS)

    Lai, Jonathan Y.

    1994-01-01

    This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

  7. Anti-aliasing Wiener filtering for wave-front reconstruction in the spatial-frequency domain for high-order astronomical adaptive-optics systems.

    PubMed

    Correia, Carlos M; Teixeira, Joel

    2014-12-01

    Computationally efficient wave-front reconstruction techniques for astronomical adaptive-optics (AO) systems have seen great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered much attention, especially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl ratio) and further develop formulae for the anti-aliasing (AA) Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e., discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise, and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of forward models for the Shack-Hartmann wave-front sensor (using sparse and nonsparse representations) and compute point-spread-function raw intensities. We find that for a 32×32 single-conjugated AOs system the aliasing propagation coefficient is roughly 60% of the least-squares filters, whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in the H band. For current and next-generation high-contrast imagers, despite better aliasing mitigation, AA Wiener filtering cannot be used as a standalone method and must therefore be used in combination with optical spatial filters deployed before image formation actually takes place. PMID:25606767

  8. Regulative Loops, Step Loops and Task Loops

    ERIC Educational Resources Information Center

    VanLehn, Kurt

    2016-01-01

    This commentary suggests a generalization of the conception of the behavior of tutoring systems, which the target article characterized as having an outer loop that was executed once per task and an inner loop that was executed once per step of the task. A more general conception sees these two loops as instances of regulative loops, which…

  9. New Predictive Filters for Compensating the Transport Delay on a Flight Simulator

    NASA Technical Reports Server (NTRS)

    Guo, Liwen; Cardullo, Frank M.; Houck, Jacob A.; Kelly, Lon C.; Wolters, Thomas E.

    2004-01-01

    The problems of transport delay in a flight simulator, such as its sources and effects, are reviewed. Then their effects on a pilot-in-the-loop control system are investigated with simulations. Three current prominent delay compensators the lead/lag filter, McFarland filter, and the Sobiski/Cardullo filter were analyzed and compared. This paper introduces two novel delay compensation techniques an adaptive predictor using the Kalman estimator and a state space predictive filter using a reference aerodynamic model. Applications of these two new compensators on recorded data from the NASA Langley Research Center Visual Motion Simulator show that they achieve better compensation over the current ones.

  10. African Swine Fever Diagnosis Adapted to Tropical Conditions by the Use of Dried-blood Filter Papers.

    PubMed

    Randriamparany, T; Kouakou, K V; Michaud, V; Fernández-Pinero, J; Gallardo, C; Le Potier, M-F; Rabenarivahiny, R; Couacy-Hymann, E; Raherimandimby, M; Albina, E

    2016-08-01

    The performance of Whatman 3-MM filter papers for the collection, drying, shipment and long-term storage of blood at ambient temperature, and for the detection of African swine fever virus and antibodies was assessed. Conventional and real-time PCR, viral isolation and antibody detection by ELISA were performed on paired samples (blood/tissue versus dried-blood 3-MM filter papers) collected from experimentally infected pigs and from farm pigs in Madagascar and Côte d'Ivoire. 3-MM filter papers were used directly in the conventional and real-time PCR without previous extraction of nucleic acids. Tests that performed better with 3-MM filter papers were in descending order: virus isolation, real-time UPL PCR and conventional PCR. The analytical sensitivity of real-time UPL PCR on filter papers was similar to conventional testing (virus isolation or conventional PCR) on organs or blood. In addition, blood-dried filter papers were tested in ELISA for antibody detection and the observed sensitivity was very close to conventional detection on serum samples and gave comparable results. Filter papers were stored up to 9 months at 20-25°C and for 2 months at 37°C without significant loss of sensitivity for virus genome detection. All tests on 3-MM filter papers had 100% specificity compared to the gold standards. Whatman 3-MM filter papers have the advantage of being cheap and of preserving virus viability for future virus isolation and characterization. In this study, Whatman 3-MM filter papers proved to be a suitable support for the collection, storage and use of blood in remote areas of tropical countries without the need for a cold chain and thus provide new possibilities for antibody testing and virus isolation. PMID:25430732

  11. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  12. Study of the algorithm of backtracking decoupling and adaptive extended Kalman filter based on the quaternion expanded to the state variable for underwater glider navigation.

    PubMed

    Huang, Haoqian; Chen, Xiyuan; Zhou, Zhikai; Xu, Yuan; Lv, Caiping

    2014-01-01

    High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle) becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF) based on the quaternion expanded to the state variable (BD-AEKF). The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF) based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method. PMID:25479331

  13. Study of the Algorithm of Backtracking Decoupling and Adaptive Extended Kalman Filter Based on the Quaternion Expanded to the State Variable for Underwater Glider Navigation

    PubMed Central

    Huang, Haoqian; Chen, Xiyuan; Zhou, Zhikai; Xu, Yuan; Lv, Caiping

    2014-01-01

    High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle) becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF) based on the quaternion expanded to the state variable (BD-AEKF). The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF) based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method. PMID:25479331

  14. User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control

    NASA Astrophysics Data System (ADS)

    He, Jiayuan; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Farina, Dario; Zhu, Xiangyang

    2015-08-01

    Objective. Recent studies have reported that the classification performance of electromyographic (EMG) signals degrades over time without proper classification retraining. This problem is relevant for the applications of EMG pattern recognition in the control of active prostheses. Approach. In this study we investigated the changes in EMG classification performance over 11 consecutive days in eight able-bodied subjects and two amputees. Main results. It was observed that, when the classifier was trained on data from one day and tested on data from the following day, the classification error decreased exponentially but plateaued after four days for able-bodied subjects and six to nine days for amputees. The between-day performance became gradually closer to the corresponding within-day performance. Significance. These results indicate that the relative changes in EMG signal features over time become progressively smaller when the number of days during which the subjects perform the pre-defined motions are increased. The performance of the motor tasks is thus more consistent over time, resulting in more repeatable EMG patterns, even if the subjects do not have any external feedback on their performance. The learning curves for both able-bodied subjects and subjects with limb deficiencies could be modeled as an exponential function. These results provide important insights into the user adaptation characteristics during practical long-term myoelectric control applications, with implications for the design of an adaptive pattern recognition system.

  15. Peripheral adaptive filtering in human olfaction? Three studies on prevalence and effects of olfactory training in specific anosmia in more than 1600 participants.

    PubMed

    Croy, Ilona; Olgun, Selda; Mueller, Laura; Schmidt, Anna; Muench, Marcus; Hummel, Cornelia; Gisselmann, Guenter; Hatt, Hanns; Hummel, Thomas

    2015-12-01

    Selective processing of environmental stimuli improves processing capacity and allows adaptive modulation of behavior. The thalamus provides an effective filter of central sensory information processing. As olfactory projections, however, largely bypass the thalamus, other filter mechanisms must consequently have evolved for the sense of smell. We investigated whether specific anosmia - the inability to perceive a specific odor whereas detection of other substances is unaffected - represents an effective peripheral filter of olfactory information processing. In contrast to previous studies, we showed in a sample of 1600 normosmic subjects, that specific anosmia is by no means a rare phenomenon. Instead, while the affected odor is highly individual, the general probability of occurrence of specific anosmia is close to 1. In addition, 25 subjects performed daily olfactory training sessions with enhanced exposure to their particular "missing" smells for the duration of three months. This resulted in a significant improvement of sensitivity towards the respective specific odors. We propose specific anosmia to occur as a rule, rather than an exception, in the sense of smell. The lack of perception of certain odors may constitute a flexible peripheral filter mechanism, which can be altered by exposure. PMID:26457822

  16. Optimized calibration strategy for high order adaptive optics systems in closed-loop: the slope-oriented Hadamard actuation.

    PubMed

    Meimon, Serge; Petit, Cyril; Fusco, Thierry

    2015-10-19

    The accurate calibration of the interaction matrix affects the performance of an adaptive optics system. In the case of high-order systems, when the number of mirror modes is worth a few thousands, the calibration strategy is critical to reach the maximum interaction matrix quality in the minimum time. This is all the more true for the future European Extremely Large Telescope. Here, we propose a novel calibration scheme, the Slope-Oriented Hadamard strategy. We then build a tractable interaction matrix quality criterion, and show that our method tends to optimize it. We demonstrate that for a given level of quality, the calibration time needed using the Slope-Oriented Hadamard method is seven times less than with a classical Hadamard scheme. These analytic and simulation results are confirmed experimentally on the SPHERE XAO system (SAXO). PMID:26480374

  17. A recursive solution for a fading memory filter derived from Kalman filter theory

    NASA Technical Reports Server (NTRS)

    Statman, J. I.

    1986-01-01

    A simple recursive solution for a class of fading memory tracking filters is presented. A fading memory filter provides estimates of filter states based on past measurements, similar to a traditional Kalman filter. Unlike a Kalman filter, an exponentially decaying weight is applied to older measurements, discounting their effect on present state estimates. It is shown that Kalman filters and fading memory filters are closely related solutions to a general least squares estimator problem. Closed form filter transfer functions are derived for a time invariant, steady state, fading memory filter. These can be applied in loop filter implementation of the Deep Space Network (DSN) Advanced Receiver carrier phase locked loop (PLL).

  18. Endoglucanase Peripheral Loops Facilitate Complexation of Glucan Chains on Cellulose via Adaptive Coupling to the Emergent Substrate Structures

    SciTech Connect

    Lin, Yuchun; Beckham, Gregg T.; Himmel, Michael E.; Crowley, Michael F.; Chu, Jhih-wei

    2013-09-19

    We examine how the catalytic domain of a glycoside hydrolase family 7 endoglucanase catalytic domain (Cel7B CD) facilitates complexation of cellulose chains from a crystal surface. With direct relevance to the science of biofuel production, this problem also represents a model system of biopolymer processing by proteins in Nature. Interactions of Cel7B CD with a cellulose microfibril along different paths of complexation are characterized by mapping the atomistic fluctuations recorded in free-energy simulations onto the parameters of a coarse-grain model. The resulting patterns of protein-biopolymer couplings also uncover the sequence signatures of the enzyme in peeling off glucan chains from the microfibril substrate. We show that the semiopen active site of Cel7B CD exhibits similar barriers and free energies of complexation over two distinct routes; namely, scooping of a chain into the active-site cleft and threading from the chain end into the channel. On the other hand, the complexation energetics strongly depends on the surface packing of the targeted chain and the resulting interaction sites with the enzyme. A revealed principle is that Cel7B CD facilitates cellulose deconstruction via adaptive coupling to the emergent substrate. The flexible, peripheral segments of the protein outside of the active-site cleft are able to accommodate the varying features of cellulose along the simulated paths of complexation. The general strategy of linking physics-based molecular interactions to protein sequence could also be helpful in elucidating how other protein machines process biopolymers.

  19. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  20. Time series analysis of Adaptive Optics wave-front sensor telemetry data

    SciTech Connect

    Poyneer, L A; Palmer, D

    2004-03-22

    Time series analysis techniques are applied to wave-front sensor telemetry data from the Lick Adaptive Optics System. For 28 fully-illuminated subapertures, telemetry data of 4096 consecutive slope estimates for each subaperture are available. The primary problem is performance comparison of alternative wave-front sensing algorithms. Using direct comparison of data in open loop and closed-loop trials, we analyze algorithm performance in terms of gain, noise and residual power. We also explore the benefits of multi-input Wiener filtering and analyze the open-loop and closed-loop spatial correlations of the sensor measurements.

  1. Development of adaptive noise reduction filter algorithm for pediatric body images in a multi-detector CT

    NASA Astrophysics Data System (ADS)

    Nishimaru, Eiji; Ichikawa, Katsuhiro; Okita, Izumi; Ninomiya, Yuuji; Tomoshige, Yukihiro; Kurokawa, Takehiro; Ono, Yutaka; Nakamura, Yuko; Suzuki, Masayuki

    2008-03-01

    Recently, several kinds of post-processing image filters which reduce the noise of computed tomography (CT) images have been proposed. However, these image filters are mostly for adults. Because these are not very effective in small (< 20 cm) display fields of view (FOV), we cannot use them for pediatric body images (e.g., premature babies and infant children). We have developed a new noise reduction filter algorithm for pediatric body CT images. This algorithm is based on a 3D post-processing in which the output pixel values are calculated by nonlinear interpolation in z-directions on original volumetric-data-sets. This algorithm does not need the in-plane (axial plane) processing, so the spatial resolution does not change. From the phantom studies, our algorithm could reduce SD up to 40% without affecting the spatial resolution of x-y plane and z-axis, and improved the CNR up to 30%. This newly developed filter algorithm will be useful for the diagnosis and radiation dose reduction of the pediatric body CT images.

  2. The need for command and control instant message adaptive interfaces: lessons learned from Tactical Tomahawk human-in-the-loop simulations.

    PubMed

    Cummings, M L

    2004-12-01

    In the recent development of a human-in-the-loop simulation test bed designed to examine human performance issues for supervisory control of the Navy's new Tactical Tomahawk missile, measurements of operator situation awareness (SA) and workload through secondary tasking were taken through an embedded instant messaging program. Instant message interfaces (otherwise known as "chat"), already a means of communication between Navy ships, allow researchers to query users in real-time in a natural, ecologic setting, and thus provide more realistic and unobtrusive measurements. However, in the course of this testing, results revealed that some subjects fixated on the real-time instant messaging secondary task instead of the primary task of missile control, leading to the overall degradation of mission performance as well as a loss of SA. While this research effort was the first to quantify command and control performance degradation as a result of instant messaging, the military has recognized that in its network centric warfare quest, instant messaging is a critical informal communication tool, but has associated problems. Recently, a military spokesman said that managing chat in current military operations was sometimes a "nightmare," because military personnel have difficulty in handling large amounts of information through chat, and then synthesizing knowledge from this information. This research highlights the need for further investigation of the role of instant messaging interfaces both on task performance and situation awareness, and how the associated problems could be ameliorated through adaptive display design. PMID:15687799

  3. All-optical clock recovery of 20 Gbit/s NRZ-DPSK signals using polarization-maintaining fiber loop mirror filter and semiconductor optical amplifier fiber ring laser

    NASA Astrophysics Data System (ADS)

    Wang, Fei; Yu, Yu; Huang, Xi; Zhang, Xinliang

    2009-06-01

    All-optical clock recovery (CR) from 20 Gbit/s nonreturn-to-zero differential phase-shift-keying (NRZ-DPSK) signals are demonstrated experimentally by using a polarization-maintaining fiber loop mirror filter (PMF-LMF) and a semiconductor optical amplifier (SOA) fiber ring laser. Only by adjusting polarization controller (PC), NRZ-DPSK signals were conveniently and fast converted to pseudo return-to-zero (PRZ) signal via PMF-LMF. Then the PRZ signals are injected into the SOA fiber laser for CR. The recovered clock signals is with the extinction ratio (ER) of 10 dB and the root-mean-square (RMS) timing jitter of 750 fs in 2 31 - 1 long pseudorandom binary sequence (PRBS) NRZ-DPSK signals measurement. Moreover, the broad wavelength tunability of recovered clock stemmed from the use of SOAs as modulator and the gain medium are shown too.

  4. Input filter compensation for switching regulators

    NASA Technical Reports Server (NTRS)

    Lee, F. C.; Kelkar, S. S.

    1982-01-01

    The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.

  5. A digital optical phase-locked loop for diode lasers based on field programmable gate array

    SciTech Connect

    Xu Zhouxiang; Zhang Xian; Huang Kaikai; Lu Xuanhui

    2012-09-15

    We have designed and implemented a highly digital optical phase-locked loop (OPLL) for diode lasers in atom interferometry. The three parts of controlling circuit in this OPLL, including phase and frequency detector (PFD), loop filter and proportional integral derivative (PID) controller, are implemented in a single field programmable gate array chip. A structure type compatible with the model MAX9382/MCH12140 is chosen for PFD and pipeline and parallelism technology have been adapted in PID controller. Especially, high speed clock and twisted ring counter have been integrated in the most crucial part, the loop filter. This OPLL has the narrow beat note line width below 1 Hz, residual mean-square phase error of 0.14 rad{sup 2} and transition time of 100 {mu}s under 10 MHz frequency step. A main innovation of this design is the completely digitalization of the whole controlling circuit in OPLL for diode lasers.

  6. A digital optical phase-locked loop for diode lasers based on field programmable gate array.

    PubMed

    Xu, Zhouxiang; Zhang, Xian; Huang, Kaikai; Lu, Xuanhui

    2012-09-01

    We have designed and implemented a highly digital optical phase-locked loop (OPLL) for diode lasers in atom interferometry. The three parts of controlling circuit in this OPLL, including phase and frequency detector (PFD), loop filter and proportional integral derivative (PID) controller, are implemented in a single field programmable gate array chip. A structure type compatible with the model MAX9382∕MCH12140 is chosen for PFD and pipeline and parallelism technology have been adapted in PID controller. Especially, high speed clock and twisted ring counter have been integrated in the most crucial part, the loop filter. This OPLL has the narrow beat note line width below 1 Hz, residual mean-square phase error of 0.14 rad(2) and transition time of 100 μs under 10 MHz frequency step. A main innovation of this design is the completely digitalization of the whole controlling circuit in OPLL for diode lasers. PMID:23020359

  7. First closed-loop visible AO test results for the advanced adaptive secondary AO system for the Magellan Telescope: MagAO's performance and status

    NASA Astrophysics Data System (ADS)

    Close, Laird M.; Males, Jared R.; Kopon, Derek A.; Gasho, Victor; Follette, Katherine B.; Hinz, Phil; Morzinski, Katie; Uomoto, Alan; Hare, Tyson; Riccardi, Armando; Esposito, Simone; Puglisi, Alfio; Pinna, Enrico; Busoni, Lorenzo; Arcidiacono, Carmelo; Xompero, Marco; Briguglio, Runa; Quiros-Pacheco, Fernando; Argomedo, Javier

    2012-07-01

    The heart of the 6.5 Magellan AO system (MagAO) is a 585 actuator adaptive secondary mirror (ASM) with <1 msec response times (0.7 ms typically). This adaptive secondary will allow low emissivity and high-contrast AO science. We fabricated a high order (561 mode) pyramid wavefront sensor (similar to that now successfully used at the Large Binocular Telescope). The relatively high actuator count (and small projected ~23 cm pitch) allows moderate Strehls to be obtained by MagAO in the “visible” (0.63-1.05 μm). To take advantage of this we have fabricated an AO CCD science camera called "VisAO". Complete “end-to-end” closed-loop lab tests of MagAO achieve a solid, broad-band, 37% Strehl (122 nm rms) at 0.76 μm (i’) with the VisAO camera in 0.8” simulated seeing (13 cm ro at V) with fast 33 mph winds and a 40 m Lo locked on R=8 mag artificial star. These relatively high visible wavelength Strehls are enabled by our powerful combination of a next generation ASM and a Pyramid WFS with 400 controlled modes and 1000 Hz sample speeds (similar to that used successfully on-sky at the LBT). Currently only the VisAO science camera is used for lab testing of MagAO, but this high level of measured performance (122 nm rms) promises even higher Strehls with our IR science cameras. On bright (R=8 mag) stars we should achieve very high Strehls (>70% at H) in the IR with the existing MagAO Clio2 (λ=1-5.3 μm) science camera/coronagraph or even higher (~98% Strehl) the Mid-IR (8-26 microns) with the existing BLINC/MIRAC4 science camera in the future. To eliminate non-common path vibrations, dispersions, and optical errors the VisAO science camera is fed by a common path advanced triplet ADC and is piggy-backed on the Pyramid WFS optical board itself. Also a high-speed shutter can be used to block periods of poor correction. The entire system passed CDR in June 2009, and we finished the closed-loop system level testing phase in December 2011. Final system acceptance (

  8. Optical UWB pulse generator using an N tap microwave photonic filter and phase inversion adaptable to different pulse modulation formats.

    PubMed

    Bolea, Mario; Mora, José; Ortega, Beatriz; Capmany, José

    2009-03-30

    We propose theoretically and demonstrate experimentally an optical architecture for flexible Ultra-Wideband pulse generation. It is based on an N-tap reconfigurable microwave photonic filter fed by a laser array by using phase inversion in a Mach-Zehnder modulator. Since a large number of positive and negative coefficients can be easily implemented, UWB pulses fitted to the FCC mask requirements can be generated. As an example, a four tap pulse generator is experimentally demonstrated which complies with the FCC regulation. The proposed pulse generator allows different pulse modulation formats since the amplitude, polarity and time delay of generated pulse is controlled. PMID:19333263

  9. A continuous-time adaptive particle filter for estimations under measurement time uncertainties with an application to a plasma-leucine mixed effects model

    PubMed Central

    2013-01-01

    Background When mathematical modelling is applied to many different application areas, a common task is the estimation of states and parameters based on measurements. With this kind of inference making, uncertainties in the time when the measurements have been taken are often neglected, but especially in applications taken from the life sciences, this kind of errors can considerably influence the estimation results. As an example in the context of personalized medicine, the model-based assessment of the effectiveness of drugs is becoming to play an important role. Systems biology may help here by providing good pharmacokinetic and pharmacodynamic (PK/PD) models. Inference on these systems based on data gained from clinical studies with several patient groups becomes a major challenge. Particle filters are a promising approach to tackle these difficulties but are by itself not ready to handle uncertainties in measurement times. Results In this article, we describe a variant of the standard particle filter (PF) algorithm which allows state and parameter estimation with the inclusion of measurement time uncertainties (MTU). The modified particle filter, which we call MTU-PF, also allows the application of an adaptive stepsize choice in the time-continuous case to avoid degeneracy problems. The modification is based on the model assumption of uncertain measurement times. While the assumption of randomness in the measurements themselves is common, the corresponding measurement times are generally taken as deterministic and exactly known. Especially in cases where the data are gained from measurements on blood or tissue samples, a relatively high uncertainty in the true measurement time seems to be a natural assumption. Our method is appropriate in cases where relatively few data are used from a relatively large number of groups or individuals, which introduce mixed effects in the model. This is a typical setting of clinical studies. We demonstrate the method on a small

  10. The Zigbee wireless ECG measurement system design with a motion artifact remove algorithm by using adaptive filter and moving weighted factor

    NASA Astrophysics Data System (ADS)

    Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

    2012-04-01

    , a filter including a moving weighted factor, peak to peak detection, and interpolation techniques. In addition, this paper introduces an adaptive filter in order to extract clear ECG signal by using extracted baseline noise signal and measured signal from sensor.

  11. Tracking Comb Filter Suppresses Welder Harmonics

    NASA Technical Reports Server (NTRS)

    Delcher, Ray C.

    1992-01-01

    Tracking comb filter includes charge-coupled-device delay line and phase-locked loop. Filter removes harmonics of frequency of repetition of welding-current pulses from acoustic-emission signal. Spurious signals reduced almost to fundamental limit.

  12. Remotely serviced filter and housing

    DOEpatents

    Ross, Maurice J.; Zaladonis, Larry A.

    1988-09-27

    A filter system for a hot cell comprises a housing adapted for input of air or other gas to be filtered, flow of the air through a filter element, and exit of filtered air. The housing is tapered at the top to make it easy to insert a filter cartridge using an overhead crane. The filter cartridge holds the filter element while the air or other gas is passed through the filter element. Captive bolts in trunnion nuts are readily operated by electromechanical manipulators operating power wrenches to secure and release the filter cartridge. The filter cartridge is adapted to make it easy to change a filter element by using a master-slave manipulator at a shielded window station.

  13. The stochastic control of the F-8C aircraft using the Multiple Model Adaptive Control (MMAC) method

    NASA Technical Reports Server (NTRS)

    Athans, M.; Dunn, K. P.; Greene, E. S.; Lee, W. H.; Sandel, N. R., Jr.

    1975-01-01

    The purpose of this paper is to summarize results obtained for the adaptive control of the F-8C aircraft using the so-called Multiple Model Adaptive Control method. The discussion includes the selection of the performance criteria for both the lateral and the longitudinal dynamics, the design of the Kalman filters for different flight conditions, the 'identification' aspects of the design using hypothesis testing ideas, and the performance of the closed loop adaptive system.

  14. A new adaptive classifier using iterative filtering. [classification of remotely sensed data in visible and near infrared bands

    NASA Technical Reports Server (NTRS)

    Actkinson, A. L.

    1974-01-01

    To cope with signature variability, an algorithm has been defined which will adaptively classify remotely sensed data in the visible and near infrared band. The signal is divided into a space-dependent component and a target-dependent component. The target-dependent component is assumed fixed across the image for each target type. The space-dependent component is estimated iteratively by a weighted, least-squares algorithm. Included are the derivations of the sensor model and the two-dimensional, estimation algorithm.

  15. Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach

    NASA Astrophysics Data System (ADS)

    Trigo, F. C.; Martins, F. P. R.; Fleury, A. T.; Silva, H. C.

    2014-02-01

    Aiming at overcoming the difficulties derived from the traditional camera calibration methods to record the underwater environment of a towing tank where experiments of scaled-model risers are carried on, a computer vision method, combining traditional image processing algorithms and a self-calibration technique was implemented. This method was used to identify the coordinates of control-points viewed on a scaled-model riser submitted to a periodic force applied to its fairlead attachment point. To study the observed motion, the riser was represented as a pseudo-rigid body model (PRBM) and the hypotheses of compliant mechanisms theory were assumed in order to cope with its elastic behavior. The derived Lagrangian equations of motion were linearized and expressed as a state-space model in which the state variables include the generalized coordinates and the unknown generalized forces. The state-vector thus assembled is estimated through a Kalman Filter. The estimation procedure allows the determination of both the generalized forces and the tension along the cable, with statistically proven convergence.

  16. Hessian-LoG filtering for enhancement and detection of photoreceptor cells in adaptive optics retinal images.

    PubMed

    Lazareva, Anfisa; Liatsis, Panos; Rauscher, Franziska G

    2016-01-01

    Automated analysis of retinal images plays a vital role in the examination, diagnosis, and prognosis of healthy and pathological retinas. Retinal disorders and the associated visual loss can be interpreted via quantitative correlations, based on measurements of photoreceptor loss. Therefore, it is important to develop reliable tools for identification of photoreceptor cells. In this paper, an automated algorithm is proposed, based on the use of the Hessian-Laplacian of Gaussian filter, which allows enhancement and detection of photoreceptor cells. The performance of the proposed technique is evaluated on both synthetic and high-resolution retinal images, in terms of packing density. The results on the synthetic data were compared against ground truth as well as cone counts obtained by the Li and Roorda algorithm. For the synthetic datasets, our method showed an average detection accuracy of 98.8%, compared to 93.9% for the Li and Roorda approach. The packing density estimates calculated on the retinal datasets were validated against manual counts and the results obtained by a proprietary software from Imagine Eyes and the Li and Roorda algorithm. Among the tested methods, the proposed approach showed the closest agreement with manual counting. PMID:26831589

  17. Remotely serviced filter and housing

    DOEpatents

    Ross, M.J.; Zaladonis, L.A.

    1987-07-22

    A filter system for a hot cell comprises a housing adapted for input of air or other gas to be filtered, flow of the air through a filter element, and exit of filtered air. The housing is tapered at the top to make it easy to insert a filter cartridge holds the filter element while the air or other gas is passed through the filter element. Captive bolts in trunnion nuts are readily operated by electromechanical manipulators operating power wrenches to secure and release the filter cartridge. The filter cartridge is adapted to make it easy to change a filter element by using a master-slave manipulator at a shielded window station. 6 figs.

  18. Digital tracking loops for a programmable digital modem

    NASA Technical Reports Server (NTRS)

    Poklemba, John J.

    1992-01-01

    In this paper, an analysis and hardware emulation of the tracking loops for a very flexible programmable digital modem (PDM) will be presented. The modem is capable of being programmed for 2, 4, 8, 16-PSK, 16-QAM, MSK, and Offset-QPSK modulation schemes over a range of data rates from 2.34 to 300 Mbps with programmable spectral occupancy from 1.2 to 1.8 times the symbol rate; these operational parameters are executable in burst or continuous mode. All of the critical processing in both the modulator and demodulator is done at baseband with very high-speed digital hardware and memory. Quadrature analog front-ends are used for translation between baseband and the IF center frequency. The modulator is based on a table lookup approach, where precomputed samples are stored in memory and clocked out according to the incoming data pattern. The sample values are predistorted to counteract the effects of the other filtering functions in the link as well as any transmission impairments. The demodulator architecture was adapted from a joint estimator-detector (JED) mathematical analysis. Its structure is applicable to most signalling formats that can be represented in a two-dimensional space. The JED realization uses interdependent, mutually aiding tracking loops with post-detection data feedback. To expedite and provide for more reliable synchronization, initial estimates for these loops are computed in a parallel acquisition processor. The cornerstone of the demodulator realization is the pre-averager received data filter which allows operation over a broad range of data rates without any hardware changes and greatly simplifies the implementation complexity. The emulation results confirmed tracking loop operation over the entire range of operational parameters listed above, as well as the capability of achieving and maintaining synchronization at BER's in excess of 10(exp -1). The emulation results also showed very close agreement with the tracking loop analysis, and

  19. Corrosion resistant filter unit

    SciTech Connect

    Gentry, J.M.

    1992-02-18

    This patent describes a fluid filter assembly adapted for the filtration of corrosive fluid to be injected into a well bore at pressure levels which may exceed 10,000 pounds per square. It comprises: a frame assembly for the mounting of a portion of the fluid filter assembly therein, the frame assembly; filter pods, the plurality of filter pods forming at least two banks of filter pods, each bank having at least two filter pods therein, each bank of the filter pods being supported by one or more the supports of the plurality of supports secured to selected struts of the frame assembly; an inlet manifold to direct the corrosive fluid to the plurality of filter pods, the inlet manifold being interconnected to the banks of filter pods formed by the filter pods whereby flow of the corrosive fluid can be directed to each bank of the filter pods; an outlet manifold to direct the corrosive fluid from the filter pods, the outlet manifold being interconnected to the banks of filter pods formed by the filter pods; a first valve means to control the flow of the corrosive fluid between banks of filter pods formed by the filter pods whereby the flow of the corrosive fluid can be selectively directed to each bank of the filter pods; a second valve means to selectively control the flow of the corrosive fluid between the inlet manifold and the outlet manifold; and union means for interconnecting the filter pods, inlet manifold and outlet manifold, each of the union means including mechanical connection means and internal seal means for isolating the corrosive fluids from the mechanical connection means.

  20. Filter vapor trap

    DOEpatents

    Guon, Jerold

    1976-04-13

    A sintered filter trap is adapted for insertion in a gas stream of sodium vapor to condense and deposit sodium thereon. The filter is heated and operated above the melting temperature of sodium, resulting in a more efficient means to remove sodium particulates from the effluent inert gas emanating from the surface of a liquid sodium pool. Preferably the filter leaves are precoated with a natrophobic coating such as tetracosane.

  1. Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter

    PubMed Central

    Han, Houzeng; Xu, Tianhe; Wang, Jian

    2016-01-01

    Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height

  2. Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter.

    PubMed

    Han, Houzeng; Xu, Tianhe; Wang, Jian

    2016-01-01

    Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height

  3. Nonlinear Attitude Filtering Methods

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis; Crassidis, John L.; Cheng, Yang

    2005-01-01

    This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

  4. Determination of the Earth's pole tide Love number k2 from observations of polar motion using an adaptive Kalman filter approach

    NASA Astrophysics Data System (ADS)

    Seitz, F.; Kirschner, S.; Neubersch, D.

    2012-09-01

    The geophysical interpretation of observed time series of Earth rotation parameters (ERP) is commonly based on numerical models that describe and balance variations of angular momentum in various subsystems of the Earth. Naturally, models are dependent on geometrical, rheological and physical parameters. Many of these are weakly determined from other models or observations. In our study we present an adaptive Kalman filter approach for the improvement of parameters of the dynamic Earth system model DyMEG which acts as a simulator of ERP. In particular we focus on the improvement of the pole tide Love number k2. In the frame of a sensitivity analysis k2 has been identified as one of the most crucial parameters of DyMEG since it directly influences the modeled Chandler oscillation. At the same time k2 is one of the most uncertain parameters in the model. Our simulations with DyMEG cover a period of 60 years after which a steady state of k2 is reached. The estimate for k2, accounting for the anelastic response of the Earth's mantle and the ocean, is 0.3531 + 0.0030i. We demonstrate that the application of the improved parameter k2 in DyMEG leads to significantly better results for polar motion than the original value taken from the Conventions of the International Earth Rotation and Reference Systems Service (IERS).

  5. Image-based ATR utilizing adaptive clutter filter detection, LLRT classification, and Volterra fusion with application to side-looking sonar

    NASA Astrophysics Data System (ADS)

    Aridgides, Tom; Fernández, Manuel

    2010-04-01

    An improved automatic target recognition (ATR) processing string has been developed. The overall processing string consists of pre-processing, subimage adaptive clutter filtering, detection, feature extraction, optimal subset feature selection, feature orthogonalization and classification processing blocks. The objects that are classified by three distinct ATR strings are fused using the classification confidence values and their expansions as features, and using "summing" or log-likelihood-ratio-test (LLRT) based fusion rules. These three ATR processing strings were individually developed and tuned by researchers from different companies. The utility of the overall processing strings and their fusion was demonstrated with an extensive side-looking sonar dataset. In this paper we describe a new processing improvement: six additional classification features are extracted, using primarily target shadow information and a feature extraction window whose length is now made variable as a function of range. This new ATR processing improvement resulted in a 3:1 reduction in false alarms. Two advanced fusion algorithms are subsequently applied: First, a nonlinear Volterra expansion (2nd order) feature-LLRT fusion algorithm is employed. Second, a repeated application of a subset Volterra feature selection / feature orthogonalization / LLRT fusion block is utilized. It is shown that cascaded Volterra feature- LLRT fusion of the ATR processing strings outperforms baseline "summing" and single-stage Volterra feature-LLRT fusion algorithms, yielding significant improvements over the best single ATR processing string results, and providing the capability to correctly call the majority of targets while maintaining a very low false alarm rate.

  6. Polar motion as boundary condition in an adaptive Kalman filter approach for the determination of period and damping of the Chandler oscillation

    NASA Astrophysics Data System (ADS)

    Seitz, F.; Kirschner, S.; Neubersch, D.

    2012-12-01

    Earth rotation has been monitored using space geodetic techniques since many decades. The geophysical interpretation of observed time series of Earth rotation parameters (ERP) polar motion and length-of-day is commonly based on numerical models that describe and balance variations of angular momentum in various subsystems of the Earth. Naturally, models are dependent on geometrical, rheological and physical parameters. Many of these are weakly determined from other models or observations. In our study we present an adaptive Kalman filter approach for the improvement of parameters of the dynamic Earth system model DyMEG which acts as a simulator of ERP. In particular we focus on the improvement of the pole tide Love number k2. In the frame of a sensitivity analysis k2 has been identified as one of the most crucial parameters of DyMEG since it directly influences the modeled Chandler oscillation. At the same time k2 is one of the most uncertain parameters in the model. Our simulations with DyMEG cover a period of 60 years after which a steady state of k2 is reached. The estimate for k2, accounting for the anelastic response of the Earth's mantle and the ocean, is 0.3531 + 0.0030i. We demonstrate that the application of the improved parameter k2 in DyMEG leads to significantly better results for polar motion than the original value taken from the Conventions of the International Earth Rotation and Reference Systems Service (IERS).

  7. Damage localization for multi-story buildings focusing on shift in the center of rigidity using an adaptive extended Kalman filter

    NASA Astrophysics Data System (ADS)

    Takeuchi, Tsubasa; Mita, Akira

    2015-04-01

    Recently damage detection methods based on measured vibration data for structural health monitoring (SHM) have been intensively studied. In order to decrease the number of required sensors, however, most of their methods focus only on single dimensional systems, in spite that there are some cases that torsional vibration greatly affect for structural damage. Although some studies consider multiple dimensional systems using frame structures, usually they need lots of sensors and calculation is time-consuming. Therefore, the balance between the cost and the particularity is very important for SHM system. In this paper, a method to localize the damaged area of multi-story buildings considering torsional components is proposed to detect the damage simply and particularly. This method focuses on shift in the center of rigidity caused by induced damage. The damaged quadrant of a certain story is identified comparing story eccentric distances of before and after damage-inducing seismic events. An adaptive extended Kalman filter (AEKF) is utilized to identify unknown structural parameters. Using a model which has four columns in each floor, several cases are considered in the verification study to disclose the capability of our proposed method.

  8. Observer performance for adaptive, image-based denoising and filtered back projection compared to scanner-based iterative reconstruction for lower dose CT enterography

    PubMed Central

    Fletcher, Joel G.; Hara, Amy K.; Fidler, Jeff L.; Silva, Alvin C.; Barlow, John M.; Carter, Rickey E.; Bartley, Adam; Shiung, Maria; Holmes, David R.; Weber, Nicolas K.; Bruining, David H.; Yu, Lifeng; McCollough, Cynthia H.

    2015-01-01

    Purpose The purpose of this study was to compare observer performance for detection of intestinal inflammation for low-dose CT enterography (LD-CTE) using scanner-based iterative reconstruction (IR) vs. vendor-independent, adaptive image-based noise reduction (ANLM) or filtered back projection (FBP). Methods Sixty-two LD-CTE exams were performed. LD-CTE images were reconstructed using IR, ANLM, and FBP. Three readers, blinded to image type, marked intestinal inflammation directly on patient images using a specialized workstation over three sessions, interpreting one image type/patient/session. Reference standard was created by a gastroenterologist and radiologist, who reviewed all available data including dismissal Gastroenterology records, and who marked all inflamed bowel segments on the same workstation. Reader and reference localizations were then compared. Non-inferiority was tested using Jackknife free-response ROC (JAFROC) figures of merit (FOM) for ANLM and FBP compared to IR. Patient-level analyses for the presence or absence of inflammation were also conducted. Results There were 46 inflamed bowel segments in 24/62 patients (CTDIvol interquartile range 6.9–10.1 mGy). JAFROC FOM for ANLM and FBP were 0.84 (95% CI 0.75–0.92) and 0.84 (95% CI 0.75–0.92), and were statistically non-inferior to IR (FOM 0.84; 95% CI 0.76–0.93). Patient-level pooled confidence intervals for sensitivity widely overlapped, as did specificities. Image quality was rated as better with IR and AMLM compared to FBP (p < 0.0001), with no difference in reading times (p = 0.89). Conclusions Vendor-independent adaptive image-based noise reduction and FBP provided observer performance that was non-inferior to scanner-based IR methods. Adaptive image-based noise reduction maintained or improved upon image quality ratings compared to FBP when performing CTE at lower dose levels. PMID:25725794

  9. RCD+: Fast loop modeling server

    PubMed Central

    López-Blanco, José Ramón; Canosa-Valls, Alejandro Jesús; Li, Yaohang; Chacón, Pablo

    2016-01-01

    Modeling loops is a critical and challenging step in protein modeling and prediction. We have developed a quick online service (http://rcd.chaconlab.org) for ab initio loop modeling combining a coarse-grained conformational search with a full-atom refinement. Our original Random Coordinate Descent (RCD) loop closure algorithm has been greatly improved to enrich the sampling distribution towards near-native conformations. These improvements include a new workflow optimization, MPI-parallelization and fast backbone angle sampling based on neighbor-dependent Ramachandran probability distributions. The server starts by efficiently searching the vast conformational space from only the loop sequence information and the environment atomic coordinates. The generated closed loop models are subsequently ranked using a fast distance-orientation dependent energy filter. Top ranked loops are refined with the Rosetta energy function to obtain accurate all-atom predictions that can be interactively inspected in an user-friendly web interface. Using standard benchmarks, the average root mean squared deviation (RMSD) is 0.8 and 1.4 Å for 8 and 12 residues loops, respectively, in the challenging modeling scenario in where the side chains of the loop environment are fully remodeled. These results are not only very competitive compared to those obtained with public state of the art methods, but also they are obtained ∼10-fold faster. PMID:27151199

  10. RCD+: Fast loop modeling server.

    PubMed

    López-Blanco, José Ramón; Canosa-Valls, Alejandro Jesús; Li, Yaohang; Chacón, Pablo

    2016-07-01

    Modeling loops is a critical and challenging step in protein modeling and prediction. We have developed a quick online service (http://rcd.chaconlab.org) for ab initio loop modeling combining a coarse-grained conformational search with a full-atom refinement. Our original Random Coordinate Descent (RCD) loop closure algorithm has been greatly improved to enrich the sampling distribution towards near-native conformations. These improvements include a new workflow optimization, MPI-parallelization and fast backbone angle sampling based on neighbor-dependent Ramachandran probability distributions. The server starts by efficiently searching the vast conformational space from only the loop sequence information and the environment atomic coordinates. The generated closed loop models are subsequently ranked using a fast distance-orientation dependent energy filter. Top ranked loops are refined with the Rosetta energy function to obtain accurate all-atom predictions that can be interactively inspected in an user-friendly web interface. Using standard benchmarks, the average root mean squared deviation (RMSD) is 0.8 and 1.4 Å for 8 and 12 residues loops, respectively, in the challenging modeling scenario in where the side chains of the loop environment are fully remodeled. These results are not only very competitive compared to those obtained with public state of the art methods, but also they are obtained ∼10-fold faster. PMID:27151199

  11. Adaptive iterative reconstruction

    NASA Astrophysics Data System (ADS)

    Bruder, H.; Raupach, R.; Sunnegardh, J.; Sedlmair, M.; Stierstorfer, K.; Flohr, T.

    2011-03-01

    It is well known that, in CT reconstruction, Maximum A Posteriori (MAP) reconstruction based on a Poisson noise model can be well approximated by Penalized Weighted Least Square (PWLS) minimization based on a data dependent Gaussian noise model. We study minimization of the PWLS objective function using the Gradient Descent (GD) method, and show that if an exact inverse of the forward projector exists, the PWLS GD update equation can be translated into an update equation which entirely operates in the image domain. In case of non-linear regularization and arbitrary noise model this means that a non-linear image filter must exist which solves the optimization problem. In the general case of non-linear regularization and arbitrary noise model, the analytical computation is not trivial and might lead to image filters which are computationally very expensive. We introduce a new iteration scheme in image space, based on a regularization filter with an anisotropic noise model. Basically, this approximates the statistical data weighting and regularization in PWLS reconstruction. If needed, e.g. for compensation of the non-exactness of backprojector, the image-based regularization loop can be preceded by a raw data based loop without regularization and statistical data weighting. We call this combined iterative reconstruction scheme Adaptive Iterative Reconstruction (AIR). It will be shown that in terms of low-contrast visibility, sharpness-to-noise and contrast-to-noise ratio, PWLS and AIR reconstruction are similar to a high degree of accuracy. In clinical images the noise texture of AIR is also superior to the more artificial texture of PWLS.

  12. Development and Analysis of a Waffle Constrained Reconstructor (WCR) for Fried Geometry Adaptive Optics Systems

    NASA Astrophysics Data System (ADS)

    Praus, R.

    2014-09-01

    A common difficulty of Fried geometry-based adaptive optics is the build-up of the unsensed spatial wavefront mode called waffle. This paper presents a Fried geometry wavefront reconstructor matrix which ameliorates the impact the waffle mode in closed-loop adaptive optics systems. Typical waffle suppression algorithms employ spatial filters that can adversely affect the adaptive optics system's ability to correct the highest spatial frequencies. Because it is not based on spatial filtering techniques, but on algebraic constraints in the development of the reconstructor matrix itself, the waffle constrained reconstructor does not sacrifice correction of high spatial frequencies in order to reduce waffle. This paper will provide the mathematical development of the waffle constrained reconstructor and provide analysis of its closed-loop performance as compared to other recontructors utilizing high-fidelity wave-optics simulations.

  13. Input filter compensation for switching regulators

    NASA Technical Reports Server (NTRS)

    Lee, F. C.

    1984-01-01

    Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.

  14. Continuous control of phase-locked-loop bandwidth

    NASA Technical Reports Server (NTRS)

    Motal, G. W.; Vanelli, J. C.

    1980-01-01

    Tracking loop filter with continuous bandwidth control smooths transition from wide to narrow band. Circuit was designed for Space Shuttle where bandwidth varied between 320 Hz for acquisition and 20 Hz for tracking. Field-effect transitor (FET) acts as voltage controlled variable resistance, changing time constant of filter between phase detector and voltage-controlled oscillator in phase-locked loop.

  15. Stack filters

    NASA Astrophysics Data System (ADS)

    Wendt, P. D.; Coyle, E. J.; Gallagher, N. C., Jr.

    1986-08-01

    A large class of easily implemented nonlinear filters called stack filters are discussed which includes the rank order operators in addition to the compositions of morphological operators. Techniques similar to those used to determine the root signal behavior of median filters are employed to study the convergence properties of the filters, and necessary conditions for a stack filter to preserve monotone regions or edges in signals, and the output distribution of the filters, are obtained. Among the stack filters of window width three are found asymmetric median filters in which one removes only positive going edges, the other removes only negative going edges, while the median filter removes impulses of both signs.

  16. False lock performance of Shuttle Costas loop receivers

    NASA Technical Reports Server (NTRS)

    Woo, K. T.; Holmes, J. K.; Huth, G. K.; Lindsey, W. C.

    1978-01-01

    The false (sideband) lock problem in Shuttle Costas loop receivers, in the presence of noise, is assessed. False lock margin is defined depending on symbol signal-to-noise ratio rather than in the absence of noise. Closed-form results are given for the case where the arm filters of the Costas loop are one-pole Butterworth filters as used in the Shuttle receivers. However, the approach taken is also general enough to cover filters of arbitrary characteristics. As part of the development of the false lock margin, it is shown that the false lock phenomenon of the squaring loop is identical to that of the Costas loop.

  17. Loop-to-loop coupling.

    SciTech Connect

    Warne, Larry Kevin; Lucero, Larry Martin; Langston, William L.; Salazar, Robert Austin; Coleman, Phillip Dale; Basilio, Lorena I.; Bacon, Larry Donald

    2012-05-01

    This report estimates inductively-coupled energy to a low-impedance load in a loop-to-loop arrangement. Both analytical models and full-wave numerical simulations are used and the resulting fields, coupled powers and energies are compared. The energies are simply estimated from the coupled powers through approximations to the energy theorem. The transmitter loop is taken to be either a circular geometry or a rectangular-loop (stripline-type) geometry that was used in an experimental setup. Simple magnetic field models are constructed and used to estimate the mutual inductance to the receiving loop, which is taken to be circular with one or several turns. Circuit elements are estimated and used to determine the coupled current and power (an equivalent antenna picture is also given). These results are compared to an electromagnetic simulation of the transmitter geometry. Simple approximate relations are also given to estimate coupled energy from the power. The effect of additional loads in the form of attached leads, forming transmission lines, are considered. The results are summarized in a set of susceptibility-type curves. Finally, we also consider drives to the cables themselves and the resulting common-to-differential mode currents in the load.

  18. Optimum performance of suppressed carrier receivers with Costas loop tracking

    NASA Technical Reports Server (NTRS)

    Simon, M. K.; Lindsey, W. C.

    1977-01-01

    The performance of suppressed carrier receivers with Costas loop tracking is optimized by proper choice of loop arm filter bandwidth. In particular, it is shown that for a variety of passive arm filter types, there exists, for a given data rate and data signal-to-noise ratio, an optimum filter bandwidth in the sense of minimizing the loop's squaring loss. For the linear theory case, this is equivalent to minimizing the loop's tracking jitter. When symbol synchronization is known, it is shown that by replacing the passive arm filters with active filters, i.e., integrate-and-dump circuits, one can achieve an improvement in carrier-to-noise ratio of as much as 4 to 6 dB depending on the passive arm filter type used for comparison and the value of data signal-to-noise ratio.

  19. Experimental assessment of the matched filter for laser guide star wavefront sensing.

    PubMed

    Conan, Rodolphe; Lardière, Olivier; Herriot, Glen; Bradley, Colin; Jackson, Kate

    2009-02-20

    Laser guide star wavefront sensing comes with several limitations. When imaged with a Shack-Hartmann wavefront sensor, the laser guide star is seen as extended sources elongated in the directions given by the lenslet locations and the laser axis. A test bed has been built in the Adaptive Optics Laboratory of the University of Victoria that reproduces this effect as seen on extremely large telescopes. A new wavefront sensing algorithm, the matched filter, has been implemented and its performance assessed with the test bed. Its ability to mitigate laser guide star aberrations by tracking the sodium layer fluctuations in a closed loop adaptive optics system is shown. PMID:23567582

  20. Image quality of CT angiography with model-based iterative reconstruction in young children with congenital heart disease: comparison with filtered back projection and adaptive statistical iterative reconstruction.

    PubMed

    Son, Sung Sil; Choo, Ki Seok; Jeon, Ung Bae; Jeon, Gye Rok; Nam, Kyung Jin; Kim, Tae Un; Yeom, Jeong A; Hwang, Jae Yeon; Jeong, Dong Wook; Lim, Soo Jin

    2015-06-01

    To retrospectively evaluate the image quality of CT angiography (CTA) reconstructed by model-based iterative reconstruction (MBIR) and to compare this with images obtained by filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) in newborns and infants with congenital heart disease (CHD). Thirty-seven children (age 4.8 ± 3.7 months; weight 4.79 ± 0.47 kg) with suspected CHD underwent CTA on a 64detector MDCT without ECG gating (80 kVp, 40 mA using tube current modulation). Total dose length product was recorded in all patients. Images were reconstructed using FBP, ASIR, and MBIR. Objective image qualities (density, noise) were measured in the great vessels and heart chambers. The contrast-to-noise ratio (CNR) was calculated by measuring the density and noise of myocardial walls. Two radiologists evaluated images for subjective noise, diagnostic confidence, and sharpness at the level prior to the first branch of the main pulmonary artery. Images were compared with respect to reconstruction method, and reconstruction times were measured. Images from all patients were diagnostic, and the effective dose was 0.22 mSv. The objective image noise of MBIR was significantly lower than those of FBP and ASIR in the great vessels and heart chambers (P < 0.05); however, with respect to attenuations in the four chambers, ascending aorta, descending aorta, and pulmonary trunk, no statistically significant difference was observed among the three methods (P > 0.05). Mean CNR values were 8.73 for FBP, 14.54 for ASIR, and 22.95 for MBIR. In addition, the subjective image noise of MBIR was significantly lower than those of the others (P < 0.01). Furthermore, while FBP had the highest score for image sharpness, ASIR had the highest score for diagnostic confidence (P < 0.05), and mean reconstruction times were 5.1 ± 2.3 s for FBP and ASIR and 15.1 ± 2.4 min for MBIR. While CTA with MBIR in newborns and infants with CHD can reduce image noise and

  1. Disk filter

    DOEpatents

    Bergman, Werner

    1986-01-01

    An electric disk filter provides a high efficiency at high temperature. A hollow outer filter of fibrous stainless steel forms the ground electrode. A refractory filter material is placed between the outer electrode and the inner electrically isolated high voltage electrode. Air flows through the outer filter surfaces through the electrified refractory filter media and between the high voltage electrodes and is removed from a space in the high voltage electrode.

  2. Disk filter

    DOEpatents

    Bergman, W.

    1985-01-09

    An electric disk filter provides a high efficiency at high temperature. A hollow outer filter of fibrous stainless steel forms the ground electrode. A refractory filter material is placed between the outer electrode and the inner electrically isolated high voltage electrode. Air flows through the outer filter surfaces through the electrified refractory filter media and between the high voltage electrodes and is removed from a space in the high voltage electrode.

  3. Water Filters

    NASA Technical Reports Server (NTRS)

    1993-01-01

    The Aquaspace H2OME Guardian Water Filter, available through Western Water International, Inc., reduces lead in water supplies. The filter is mounted on the faucet and the filter cartridge is placed in the "dead space" between sink and wall. This filter is one of several new filtration devices using the Aquaspace compound filter media, which combines company developed and NASA technology. Aquaspace filters are used in industrial, commercial, residential, and recreational environments as well as by developing nations where water is highly contaminated.

  4. On interference suppression using complementary filters in DS-SSS

    NASA Astrophysics Data System (ADS)

    Lee, Bong Woon; Essman, Joseph E.

    An alternate interference suppression method used in conjunction with direct-sequence spread-spectrum systems (DS-SSS) is proposed. It consists of a complementary filter and reference loop using a scalar filter in the Walsh-Hadamard domain. Analytical expressions for chip-error probability (Pe) in the reference loop are given, and the performance of the complementary filter is compared with that of the other suppression filters via a simulation. The results show that the complementary filter is superior to the other filters when Pe is less than 0.25.

  5. Electronic filters, hearing aids and methods

    NASA Technical Reports Server (NTRS)

    Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor); Zheng, Baohua (Inventor)

    1991-01-01

    An electronic filter for an electroacoustic system. The system has a microphone for generating an electrical output from external sounds and an electrically driven transducer for emitting sound. Some of the sound emitted by the transducer returns to the microphone means to add a feedback contribution to its electical output. The electronic filter includes a first circuit for electronic processing of the electrical output of the microphone to produce a filtered signal. An adaptive filter, interconnected with the first circuit, performs electronic processing of the filtered signal to produce an adaptive output to the first circuit to substantially offset the feedback contribution in the electrical output of the microphone, and the adaptive filter includes means for adapting only in response to polarities of signals supplied to and from the first circuit. Other electronic filters for hearing aids, public address systems and other electroacoustic systems, as well as such systems, and methods of operating them are also disclosed.

  6. Biological Filters.

    ERIC Educational Resources Information Center

    Klemetson, S. L.

    1978-01-01

    Presents the 1978 literature review of wastewater treatment. The review is concerned with biological filters, and it covers: (1) trickling filters; (2) rotating biological contractors; and (3) miscellaneous reactors. A list of 14 references is also presented. (HM)

  7. Acquisition and Tracking Behavior of Phase-Locked Loops

    NASA Technical Reports Server (NTRS)

    Viterbi, A. J.

    1958-01-01

    Phase-locked or APC loops have found increasing applications in recent years as tracking filters, synchronizing devices, and narrowband FM discriminators. Considerable work has been performed to determine the noise-squelching properties of the loop when it is operating in or near phase lock and is functioning as a linear coherent detector. However, insufficient consideration has been devoted to the non-linear behavior of the loop when it is out of lock and in the process of pulling in. Experimental evidence has indicated that there is a strong tendency for phase-locked loops to achieve lock under most circumstances. However, the analysis which has appeared in the literature iis limited to the acquisition of a constant frequency reference signal with only one phase-locked loop filter configuration. This work represents an investigation of frequency acquisition properties of phase-locked loops for a variety of reference-signal behavior and loop configurations

  8. Metallic Filters

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Filtration technology originated in a mid 1960's NASA study. The results were distributed to the filter industry, an HR Textron responded, using the study as a departure for the development of 421 Filter Media. The HR system is composed of ultrafine steel fibers metallurgically bonded and compressed so that the pore structure is locked in place. The filters are used to filter polyesters, plastics, to remove hydrocarbon streams, etc. Several major companies use the product in chemical applications, pollution control, etc.

  9. Water Filters

    NASA Technical Reports Server (NTRS)

    1987-01-01

    A compact, lightweight electrolytic water filter generates silver ions in concentrations of 50 to 100 parts per billion in the water flow system. Silver ions serve as effective bactericide/deodorizers. Ray Ward requested and received from NASA a technical information package on the Shuttle filter, and used it as basis for his own initial development, a home use filter.

  10. FILTER TREATMENT

    DOEpatents

    Sutton, J.B.; Torrey, J.V.P.

    1958-08-26

    A process is described for reconditioning fused alumina filters which have become clogged by the accretion of bismuth phosphate in the filter pores, The method consists in contacting such filters with faming sulfuric acid, and maintaining such contact for a substantial period of time.

  11. Adaptive control and noise suppression by a variable-gain gradient algorithm

    NASA Technical Reports Server (NTRS)

    Merhav, S. J.; Mehta, R. S.

    1987-01-01

    An adaptive control system based on normalized LMS filters is investigated. The finite impulse response of the nonparametric controller is adaptively estimated using a given reference model. Specifically, the following issues are addressed: The stability of the closed loop system is analyzed and heuristically established. Next, the adaptation process is studied for piecewise constant plant parameters. It is shown that by introducing a variable-gain in the gradient algorithm, a substantial reduction in the LMS adaptation rate can be achieved. Finally, process noise at the plant output generally causes a biased estimate of the controller. By introducing a noise suppression scheme, this bias can be substantially reduced and the response of the adapted system becomes very close to that of the reference model. Extensive computer simulations validate these and demonstrate assertions that the system can rapidly adapt to random jumps in plant parameters.

  12. A Self-Adaptive Missile Guidance System for Statistical Inputs

    NASA Technical Reports Server (NTRS)

    Peery, H. Rodney

    1960-01-01

    A method of designing a self-adaptive missile guidance system is presented. The system inputs are assumed to be known in a statistical sense only. Newton's modified Wiener theory is utilized in the design of the system and to establish the performance criterion. The missile is assumed to be a beam rider, to have a g limiter, and to operate over a flight envelope where the open-loop gain varies by a factor of 20. It is shown that the percent of time that missile acceleration limiting occurs can be used effectively to adjust the coefficients of the Wiener filter. The result is a guidance system which adapts itself to a changing environment and gives essentially optimum filtering and minimum miss distance.

  13. Quick-change filter cartridge

    DOEpatents

    Rodgers, John C.; McFarland, Andrew R.; Ortiz, Carlos A.

    1995-01-01

    A quick-change filter cartridge. In sampling systems for measurement of airborne materials, a filter element is introduced into the sampled airstream such that the aerosol constituents are removed and deposited on the filter. Fragile sampling media often require support in order to prevent rupture during sampling, and careful mounting and sealing to prevent misalignment, tearing, or creasing which would allow the sampled air to bypass the filter. Additionally, handling of filter elements may introduce cross-contamination or exposure of operators to toxic materials. Moreover, it is desirable to enable the preloading of filter media into quick-change cartridges in clean laboratory environments, thereby simplifying and expediting the filter-changing process in the field. The quick-change filter cartridge of the present invention permits the application of a variety of filter media in many types of instruments and may also be used in automated systems. The cartridge includes a base through which a vacuum can be applied to draw air through the filter medium which is located on a porous filter support and held there by means of a cap which forms an airtight seal with the base. The base is also adapted for receiving absorbing media so that both particulates and gas-phase samples may be trapped for investigation, the latter downstream of the aerosol filter.

  14. An optimization of the FPGA/NIOS adaptive FIR filter using linear prediction to reduce narrow band RFI for the next generation ground-based ultra-high energy cosmic-ray experiment

    NASA Astrophysics Data System (ADS)

    Szadkowski, Zbigniew; Fraenkel, E. D.; Glas, Dariusz; Legumina, Remigiusz

    2013-12-01

    The electromagnetic part of an extensive air shower developing in the atmosphere provides significant information complementary to that obtained by water Cherenkov detectors which are predominantly sensitive to the muonic content of an air shower at ground. The emissions can be observed in the frequency band between 10 and 100 MHz. However, this frequency range is significantly contaminated by narrow-band RFI and other human-made distortions. The Auger Engineering Radio Array currently suppresses the RFI by multiple time-to-frequency domain conversions using an FFT procedure as well as by a set of manually chosen IIR notch filters in the time-domain. An alternative approach developed in this paper is an adaptive FIR filter based on linear prediction (LP). The coefficients for the linear predictor are dynamically refreshed and calculated in the virtual NIOS processor. The radio detector is an autonomous system installed on the Argentinean pampas and supplied from a solar panel. Powerful calculation capacity inside the FPGA is a factor. Power consumption versus the degree of effectiveness of the calculation inside the FPGA is a figure of merit to be minimized. Results show that the RFI contamination can be significantly suppressed by the LP FIR filter for 64 or less stages.

  15. Kalman Orbit Optimized Loop Tracking

    NASA Technical Reports Server (NTRS)

    Young, Lawrence E.; Meehan, Thomas K.

    2011-01-01

    Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

  16. Rollercoaster Loop Shapes

    ERIC Educational Resources Information Center

    Pendrill, Ann-Marie

    2005-01-01

    Many modern rollercoasters feature loops. Although textbook loops are often circular, real rollercoaster loops are not. In this paper, we look into the mathematical description of various possible loop shapes, as well as their riding properties. We also discuss how a study of loop shapes can be used in physics education.

  17. Rollercoaster loop shapes

    NASA Astrophysics Data System (ADS)

    Pendrill, Ann-Marie

    2005-11-01

    Many modern rollercoasters feature loops. Although textbook loops are often circular, real rollercoaster loops are not. In this paper, we look into the mathematical description of various possible loop shapes, as well as their riding properties. We also discuss how a study of loop shapes can be used in physics education.

  18. Multi-instrument observations of coronal loops

    NASA Astrophysics Data System (ADS)

    Scott, Jason Terrence

    This document exhibits results of analysis from data collected with multiple EUV satellites (SOHO, TRACE, STEREO, Hinode, and SDO). The focus is the detailed observation of coronal loops using multiple instruments, i.e. filter imagers and spectrometers. Techniques for comparing the different instruments and deriving loop parameters are demonstrated. Attention is given to the effects the different instruments may introduce into the data and their interpretation. The assembled loop parameters are compared to basic energy balance equations and scaling laws. Discussion of the blue-shifted, asymmetric, and line broadened spectral line profiles near the footpoints of coronal loops is made. The first quantitative analysis of the anti-correlation between intensity and spectral line broadening for isolated regions along loops and their footpoints is presented. A magnetic model of an active region shows where the separatrices meet the photospheric boundary. At the boundary, the spectral data reveal concentrated regions of increased blue-shifted outflows, blue wing asymmetry, and line broadening. This is found just outside the footpoints of bright loops. The intensity and line broadening in this region are anti-correlated. A comparison of the similarities in the spectroscopic structure near the footpoints of the arcade loops and more isolated loops suggests the notion of consistent structuring for the bright loops forming an apparent edge of an active region core.

  19. Water Stream "Loop-the-Loop"

    ERIC Educational Resources Information Center

    Jefimenko, Oleg

    1974-01-01

    Discusses the design of a modified loop-the-loop apparatus in which a water stream is used to illustrate centripetal forces and phenomena of high-velocity hydrodynamics. Included are some procedures of carrying out lecture demonstrations. (CC)

  20. Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

    NASA Technical Reports Server (NTRS)

    VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

    2014-01-01

    Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a

  1. A Computer Model of a Phase Lock Loop

    NASA Technical Reports Server (NTRS)

    Shelton, Ralph Paul

    1973-01-01

    A computer model is reported of a PLL (phase-lock loop), preceded by a bandpass filter, which is valid when the bandwidth of the bandpass filter is of the same order of magnitude as the natural frequency of the PLL. New results for the PLL natural frequency equal to the bandpass filter bandwidth are presented for a second order PLL operating with carrier plus noise as the input. However, it is shown that extensions to higher order loops, and to the case of a modulated carrier are straightforward. The new results presented give the cycle skipping rate of the PLL as a function of the input carrier to noise ratio when the PLL natural frequency is equal to the bandpass filter bandwidth. Preliminary results showing the variation of the output noise power and cycle skipping rates of the PLL as a function of the loop damping ratio for the PLL natural frequency equal to the bandpass filter bandwidth are also included.

  2. Filtering apparatus

    DOEpatents

    Haldipur, Gaurang B.; Dilmore, William J.

    1992-01-01

    A vertical vessel having a lower inlet and an upper outlet enclosure separated by a main horizontal tube sheet. The inlet enclosure receives the flue gas from a boiler of a power system and the outlet enclosure supplies cleaned gas to the turbines. The inlet enclosure contains a plurality of particulate-removing clusters, each having a plurality of filter units. Each filter unit includes a filter clean-gas chamber defined by a plate and a perforated auxiliary tube sheet with filter tubes suspended from each tube sheet and a tube connected to each chamber for passing cleaned gas to the outlet enclosure. The clusters are suspended from the main tube sheet with their filter units extending vertically and the filter tubes passing through the tube sheet and opening in the outlet enclosure. The flue gas is circulated about the outside surfaces of the filter tubes and the particulate is absorbed in the pores of the filter tubes. Pulses to clean the filter tubes are passed through their inner holes through tubes free of bends which are aligned with the tubes that pass the clean gas.

  3. Filtering apparatus

    DOEpatents

    Haldipur, G.B.; Dilmore, W.J.

    1992-09-01

    A vertical vessel is described having a lower inlet and an upper outlet enclosure separated by a main horizontal tube sheet. The inlet enclosure receives the flue gas from a boiler of a power system and the outlet enclosure supplies cleaned gas to the turbines. The inlet enclosure contains a plurality of particulate-removing clusters, each having a plurality of filter units. Each filter unit includes a filter clean-gas chamber defined by a plate and a perforated auxiliary tube sheet with filter tubes suspended from each tube sheet and a tube connected to each chamber for passing cleaned gas to the outlet enclosure. The clusters are suspended from the main tube sheet with their filter units extending vertically and the filter tubes passing through the tube sheet and opening in the outlet enclosure. The flue gas is circulated about the outside surfaces of the filter tubes and the particulate is absorbed in the pores of the filter tubes. Pulses to clean the filter tubes are passed through their inner holes through tubes free of bends which are aligned with the tubes that pass the clean gas. 18 figs.

  4. Iterative LQG Controller Design Through Closed-Loop Identification

    NASA Technical Reports Server (NTRS)

    Hsiao, Min-Hung; Huang, Jen-Kuang; Cox, David E.

    1996-01-01

    This paper presents an iterative Linear Quadratic Gaussian (LQG) controller design approach for a linear stochastic system with an uncertain open-loop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQC controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

  5. Extrasensitive phase-locked-loop circuit

    NASA Technical Reports Server (NTRS)

    Nyiri, E. J.

    1977-01-01

    Modified phase-locked loop (PLL) generates clock from incoming data signal. To minimize effects of threshold phase-detector gain variations, the PLL uses a dither oscillator, a dither band-pass filter, and correlator instead of coherent amplitude detector.

  6. Neuron-like dynamics of a phase-locked loop

    NASA Astrophysics Data System (ADS)

    Matrosov, Valery V.; Mishchenko, Mikhail A.; Shalfeev, Vladimir D.

    2013-10-01

    Dynamics of two coupled phase-controlled generators based on phase-locked loop systems with a high frequency filter in the control loop was studied. It was found that beating modes are synchronized in the systems and shown that different synchronization states form an overlapping structure in parameters space of the coupled systems. Usage of the phase-locked loop as a neuron-like element is proposed.

  7. Adaptive sampler

    DOEpatents

    Watson, Bobby L.; Aeby, Ian

    1982-01-01

    An adaptive data compression device for compressing data having variable frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.

  8. Adaptive sampler

    DOEpatents

    Watson, B.L.; Aeby, I.

    1980-08-26

    An adaptive data compression device for compressing data is described. The device has a frequency content, including a plurality of digital filters for analyzing the content of the data over a plurality of frequency regions, a memory, and a control logic circuit for generating a variable rate memory clock corresponding to the analyzed frequency content of the data in the frequency region and for clocking the data into the memory in response to the variable rate memory clock.

  9. Phase-locked loop FM demodulator

    NASA Technical Reports Server (NTRS)

    Kirkham, Harold (Inventor); Jackson, Shannon P. (Inventor)

    1992-01-01

    A conventional phase-locked loop is improved by replacing its phase detector with one comprising a linear ramp generator and a sample-and-hold circuit, thus eliminating the need for a lowpass loop filter, although the output of the sample-and-hold circuit may be filtered in the case of a very low level modulating signal on the incoming FM signal, but then filtering is not a difficult problem as in a conventional phase-locked loop. The result is FM demodulation by zero-order estimation. For FM demodulation by first-order estimation, the arithmetic difference between adjacent samples is formed, and using a second sample-and-hold circuit an arithmetic difference signal is produced as an input to a second ramp generator that is reset after each sampling cycle to generate a ramp the slope of which is a function of the arithmetic difference signal stored in the second sample-and-hold circuit. The ramp thus generated by the second ramp generator is arithmetically summed with the zero-estimation signal from the first sample-and-hold circuit to form a first-order estimation signal. Filtering such a first-order estimation signal is less of a problem than filtering a zero-order estimation signal.

  10. Flare Half-Loops: What Are They?

    NASA Astrophysics Data System (ADS)

    McKenzie, David Eugene; Guidoni, S. E.; Longcope, D. W.; Yoshimura, K.

    2012-05-01

    The M1.4 flare of 28 January 2011 has a remarkable resemblance to the famous "Tsuneta candle-flame" flare of 1992. It was observed with Hinode/XRT, SDO/AIA, and STEREO (A)/EUVI, resulting in higher resolution, greater temperature coverage, and stereoscopic views of this iconic structure. The high temperature images reveal a brightening that grows in size to form a tower-like structure at the top of the arcade. They also show that loops which are successively connected to this tower develop a density increase in one of their legs that can exceed twice the density of the other leg, giving the appearance of "half loops". These jumps in density last for an extended period of time. On the other hand, XRT filter ratios suggest that temperature is approximately uniform along the entire loop. XRT filter-ratio density maps corroborate that the brighter legs have higher density than the fainter halves. The tower is associated with a localized density increase, with even higher densities than either leg of the loop. This spatial variation of density may correspond to a shock at the top of the loops. We use STEREO images to show that the half loop brightening is not a line-of-sight projection effect of the type suggested by Forbes & Acton. This work is supported under contract SP02H3901R from Lockheed-Martin to MSU, and under contract NNM07AB07C with the Harvard-Smithsonian Astrophysical Observatory.

  11. An Extension to the Kalman Filter for an Improved Detection of Unknown Behavior

    NASA Technical Reports Server (NTRS)

    Benazera, Emmanuel; Narasimhan, Sriram

    2005-01-01

    The use of Kalman filter (KF) interferes with fault detection algorithms based on the residual between estimated and measured variables, since the measured values are used to update the estimates. This feedback results in the estimates being pulled closer to the measured values, influencing the residuals in the process. Here we present a fault detection scheme for systems that are being tracked by a KF. Our approach combines an open-loop prediction over an adaptive window and an information-based measure of the deviation of the Kalman estimate from the prediction to improve fault detection.

  12. Passband switchable microwave photonic multiband filter.

    PubMed

    Ge, Jia; Fok, Mable P

    2015-01-01

    A reconfigurable microwave photonic (MWP) multiband filter with selectable and switchable passbands is proposed and experimentally demonstrated, with a maximum of 12 simultaneous passbands evenly distributed from 0 to 10 GHz. The scheme is based on the generation of tunable optical comb lines using a two-stage Lyot loop filter, such that various filter tap spacings and spectral combinations are obtained for the configuration of the MWP filter. Through polarization state adjustment inside the Lyot loop filter, an optical frequency comb with 12 different comb spacings is achieved, which corresponds to a MWP filter with 12 selectable passbands. Center frequencies of the filter passbands are switchable, while the number of simultaneous passbands is tunable from 1 to 12. Furthermore, the MWP multiband filter can either work as an all-block, single-band or multiband filter with various passband combinations, which provide exceptional operation flexibility. All the passbands have over 30 dB sidelobe suppression and 3-dB bandwidth of 200 MHz, providing good filter selectivity. PMID:26521693

  13. Passband switchable microwave photonic multiband filter

    NASA Astrophysics Data System (ADS)

    Ge, Jia; Fok, Mable P.

    2015-11-01

    A reconfigurable microwave photonic (MWP) multiband filter with selectable and switchable passbands is proposed and experimentally demonstrated, with a maximum of 12 simultaneous passbands evenly distributed from 0 to 10 GHz. The scheme is based on the generation of tunable optical comb lines using a two-stage Lyot loop filter, such that various filter tap spacings and spectral combinations are obtained for the configuration of the MWP filter. Through polarization state adjustment inside the Lyot loop filter, an optical frequency comb with 12 different comb spacings is achieved, which corresponds to a MWP filter with 12 selectable passbands. Center frequencies of the filter passbands are switchable, while the number of simultaneous passbands is tunable from 1 to 12. Furthermore, the MWP multiband filter can either work as an all-block, single-band or multiband filter with various passband combinations, which provide exceptional operation flexibility. All the passbands have over 30 dB sidelobe suppression and 3-dB bandwidth of 200 MHz, providing good filter selectivity.

  14. Passband switchable microwave photonic multiband filter

    PubMed Central

    Ge, Jia; Fok, Mable P.

    2015-01-01

    A reconfigurable microwave photonic (MWP) multiband filter with selectable and switchable passbands is proposed and experimentally demonstrated, with a maximum of 12 simultaneous passbands evenly distributed from 0 to 10 GHz. The scheme is based on the generation of tunable optical comb lines using a two-stage Lyot loop filter, such that various filter tap spacings and spectral combinations are obtained for the configuration of the MWP filter. Through polarization state adjustment inside the Lyot loop filter, an optical frequency comb with 12 different comb spacings is achieved, which corresponds to a MWP filter with 12 selectable passbands. Center frequencies of the filter passbands are switchable, while the number of simultaneous passbands is tunable from 1 to 12. Furthermore, the MWP multiband filter can either work as an all-block, single-band or multiband filter with various passband combinations, which provide exceptional operation flexibility. All the passbands have over 30 dB sidelobe suppression and 3-dB bandwidth of 200 MHz, providing good filter selectivity. PMID:26521693

  15. Can Chemical Looping Combustion Use CFB Technology?

    SciTech Connect

    Gamwo, I.K.

    2006-11-01

    Circulating Fluidized Bed (CFB) technology has demonstrated an unparalleled ability to achieve low SO2 and NOx emissions for coal-fired power plants without CO2 capture. Chemical Looping combustion (CLC) is a novel fuel combustion technology which appears as a leading candidate in terms of competitiveness for CO2 removal from flue gas. This presentaion deals with the adaptation of circulating fluidized bed technology to Chemical looping combustion

  16. OPE for super loops

    NASA Astrophysics Data System (ADS)

    Sever, Amit; Vieira, Pedro; Wang, Tianheng

    2011-11-01

    We extend the Operator Product Expansion for Null Polygon Wilson loops to the Mason-Skinner-Caron-Huot super loop dual to non MHV gluon amplitudes. We explain how the known tree level amplitudes can be promoted into an infinite amount of data at any loop order in the OPE picture. As an application, we re-derive all one loop NMHV six gluon amplitudes by promoting their tree level expressions. We also present some new all loops predictions for these amplitudes.

  17. The preprocessed doacross loop

    NASA Technical Reports Server (NTRS)

    Saltz, Joel H.; Mirchandaney, Ravi

    1990-01-01

    Dependencies between loop iterations cannot always be characterized during program compilation. Doacross loops typically make use of a-priori knowledge of inter-iteration dependencies to carry out required synchronizations. A type of doacross loop is proposed that allows the scheduling of iterations of a loop among processors without advance knowledge of inter-iteration dependencies. The method proposed for loop iterations requires that parallelizable preprocessing and postprocessing steps be carried out during program execution.

  18. Fast flux locked loop

    DOEpatents

    Ganther, Jr., Kenneth R.; Snapp, Lowell D.

    2002-09-10

    A flux locked loop for providing an electrical feedback signal, the flux locked loop employing radio-frequency components and technology to extend the flux modulation frequency and tracking loop bandwidth. The flux locked loop of the present invention has particularly useful application in read-out electronics for DC SQUID magnetic measurement systems, in which case the electrical signal output by the flux locked loop represents an unknown magnetic flux applied to the DC SQUID.

  19. High-performance brain-machine interface enabled by an adaptive optimal feedback-controlled point process decoder.

    PubMed

    Shanechi, Maryam M; Orsborn, Amy; Moorman, Helene; Gowda, Suraj; Carmena, Jose M

    2014-01-01

    Brain-machine interface (BMI) performance has been improved using Kalman filters (KF) combined with closed-loop decoder adaptation (CLDA). CLDA fits the decoder parameters during closed-loop BMI operation based on the neural activity and inferred user velocity intention. These advances have resulted in the recent ReFIT-KF and SmoothBatch-KF decoders. Here we demonstrate high-performance and robust BMI control using a novel closed-loop BMI architecture termed adaptive optimal feedback-controlled (OFC) point process filter (PPF). Adaptive OFC-PPF allows subjects to issue neural commands and receive feedback with every spike event and hence at a faster rate than the KF. Moreover, it adapts the decoder parameters with every spike event in contrast to current CLDA techniques that do so on the time-scale of minutes. Finally, unlike current methods that rotate the decoded velocity vector, adaptive OFC-PPF constructs an infinite-horizon OFC model of the brain to infer velocity intention during adaptation. Preliminary data collected in a monkey suggests that adaptive OFC-PPF improves BMI control. OFC-PPF outperformed SmoothBatch-KF in a self-paced center-out movement task with 8 targets. This improvement was due to both the PPF's increased rate of control and feedback compared with the KF, and to the OFC model suggesting that the OFC better approximates the user's strategy. Also, the spike-by-spike adaptation resulted in faster performance convergence compared to current techniques. Thus adaptive OFC-PPF enabled proficient BMI control in this monkey. PMID:25571483

  20. Nonlinear filtering for robust signal processing

    SciTech Connect

    Palmieri, F.

    1987-01-01

    A generalized framework for the description and design of a large class of nonlinear filters is proposed. Such a family includes, among others, the newly defined Ll-estimators, that generalize the order statistic filters (L-filters) and the nonrecursive linear filters (FIR). Such estimators are particularly efficient in filtering signals that do not follow gaussian distributions. They can be designed to restore signals and images corrupted by noise of impulsive type. Such filters are very appealing since they are suitable for being made robust against perturbations on the assumed model, or insensitive to the presence of spurious outliers in the data. The linear part of the filter is used to characterize their essential spectral behavior. It can be constrained to a given shape to obtain nonlinear filters that combine given frequency characteristics and noise immunity. The generalized nonlinear filters can also be used adaptively with the coefficients computed dynamically via LMS or RLS algorithms.