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Sample records for adaptive digital filtering

  1. Weighted adaptive spatial filtering in digital holographic microscopy

    NASA Astrophysics Data System (ADS)

    Hong, Yuan; Shi, Tielin; Wang, Xiao; Zhang, Yichun; Chen, Kepeng; Liao, Guanglan

    2017-01-01

    Spatial filtering, a key point to realize real-time measurement, is used commonly in digital off-axis holography to extract desired terms. In this paper, we propose a weighted adaptive spatial filtering method by weighting the adaptive filtering window (obtained from image segmentation) based on signal to noise ratio. The advantages of this method are evaluated by simulations and further verified by recorded digital image plane holograms. The results demonstrate that our method is effective in suppressing noise and retaining the sharp edges in the reconstructed 3D profiles.

  2. Selected annotated bibliographies for adaptive filtering of digital image data

    USGS Publications Warehouse

    Mayers, Margaret; Wood, Lynnette

    1988-01-01

    Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity.Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze.Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. Survey of digital filtering

    NASA Technical Reports Server (NTRS)

    Nagle, H. T., Jr.

    1972-01-01

    A three part survey is made of the state-of-the-art in digital filtering. Part one presents background material including sampled data transformations and the discrete Fourier transform. Part two, digital filter theory, gives an in-depth coverage of filter categories, transfer function synthesis, quantization and other nonlinear errors, filter structures and computer aided design. Part three presents hardware mechanization techniques. Implementations by general purpose, mini-, and special-purpose computers are presented.

  8. 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.

  9. A model for radar images and its application to adaptive digital filtering of multiplicative noise

    NASA Technical Reports Server (NTRS)

    Frost, V. S.; Stiles, J. A.; Shanmugan, K. S.; Holtzman, J. C.

    1982-01-01

    Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

  10. Digital transversal filter architecture

    NASA Astrophysics Data System (ADS)

    Greenberger, A. J.

    1985-01-01

    A fast and efficient architecture is described for the realization of a pipelined, fully parallel digital transversal filter in VLSI. The order of summation is changed such that no explicit multiplication is seen, gated accumulators are used, and the coefficients are circulated. Estimates for the number of transistors needed for a CMOS implementation are given.

  11. Rocket noise filtering system using digital filters

    NASA Technical Reports Server (NTRS)

    Mauritzen, David

    1990-01-01

    A set of digital filters is designed to filter rocket noise to various bandwidths. The filters are designed to have constant group delay and are implemented in software on a general purpose computer. The Parks-McClellan algorithm is used. Preliminary tests are performed to verify the design and implementation. An analog filter which was previously employed is also simulated.

  12. Digital hum filtering

    USGS Publications Warehouse

    Knapp, R.W.; Anderson, N.L.

    1994-01-01

    Data may be overprinted by a steady-state cyclical noise (hum). Steady-state indicates that the noise is invariant with time; its attributes, frequency, amplitude, and phase, do not change with time. Hum recorded on seismic data usually is powerline noise and associated higher harmonics; leakage from full-waveform rectified cathodic protection devices that contain the odd higher harmonics of powerline frequencies; or vibrational noise from mechanical devices. The fundamental frequency of powerline hum may be removed during data acquisition with the use of notch filters. Unfortunately, notch filters do not discriminate signal and noise, attenuating both. They also distort adjacent frequencies by phase shifting. Finally, they attenuate only the fundamental mode of the powerline noise; higher harmonics and frequencies other than that of powerlines are not removed. Digital notch filters, applied during processing, have many of the same problems as analog filters applied in the field. The method described here removes hum of a particular frequency. Hum attributes are measured by discrete Fourier analysis, and the hum is canceled from the data by subtraction. Errors are slight and the result of the presence of (random) noise in the window or asynchrony of the hum and data sampling. Error is minimized by increasing window size or by resampling to a finer interval. Errors affect the degree of hum attenuation, not the signal. The residual is steady-state hum of the same frequency. ?? 1994.

  13. Digital matched filter ASIC

    NASA Astrophysics Data System (ADS)

    Magill, D. T.; Edwards, G.

    The architecture of a digital matched filter (DMF) and the selected technology used is described. The characteristics of the DMF ASIC are summarized in tabular form. Three architectures are considered for the implementation of a DMF ASIC. First, there is the conventional trapped delay line architecture which requires a large adder tree. The second architecture is the systolic array DMF which consists of a number of identical stages cascaded together. The third architecture is the bank-of-correlators DMF, in which the reference code is recirculated around through the delay line. Since the objective is to maximize the length of the DMF, the tapped delay line architecture is selected. The tapped delay form is designed to support BPSK, QPSK, and OQPSK chip modulation. Matched filter lengths of up to 256 chips can be supported by cascading 4 ASICs. The DMF is designed as a gate array using an advanced double metal, 1.5 micron CMOS process. The regularity of FIR filter architecture allows the core of the device to be laid out very compactly, resulting in efficient usage of the gate array.

  14. Counting digital filter

    NASA Technical Reports Server (NTRS)

    Zohar, S.

    1977-01-01

    Overall design of filter combines radix converter with ADC in single functional unit that directly converts analog input to its negative binary representation. Four basic elements of filter are fixed register, shift register, counter, and accumulator.

  15. Digital filtering: background and tutorial for psychophysiologists.

    PubMed

    Cook, E W; Miller, G A

    1992-05-01

    Digital filtering offers more to psychophysiologists than is commonly appreciated. An introduction is offered here to foster the explicit design and use of digital filters. Because of considerable confusion in the literature about terminology important to both analog and digital filtering, basic concepts are reviewed and clarified. Because some time series concepts are fundamental to digital filtering, these are also presented. Examples of filters commonly used in psychophysiology are given, and procedures are presented for the design and use of one type of digital filter. Properties of some types of digital filters are described, and the relative advantages of simple analog and digital filters are discussed.

  16. Advanced simulation of digital filters

    NASA Astrophysics Data System (ADS)

    Doyle, G. S.

    1980-09-01

    An Advanced Simulation of Digital Filters has been implemented on the IBM 360/67 computer utilizing Tektronix hardware and software. The program package is appropriate for use by persons beginning their study of digital signal processing or for filter analysis. The ASDF programs provide the user with an interactive method by which filter pole and zero locations can be manipulated. Graphical output on both the Tektronix graphics screen and the Versatec plotter are provided to observe the effects of pole-zero movement.

  17. Digital Filter Design Techniques.

    DTIC Science & Technology

    1988-03-01

    McClellan, and the Minimum p - Error IIR Filter Design Method of Deczky. Acceso Fo S CRA&!I DIC TAd [8 13v i . , . a.- II **’. . ’uaJI r -TABLE OF ,CONTENT...NFILT-- FILTE LENGTH C dUYPE-- TYPE OF FILIP C I MULTIPLE PASSbAND/STOPHASZ P11151 C =DIYFEZlNTIATCP C 3 HILBEET DANSFCRZ PELTE2 C NiANDS-- NUEBEi Of

  18. Digital frequency tracking filter design

    NASA Astrophysics Data System (ADS)

    Yeh, Hen-Geul

    In this paper, three design approaches of the digital frequency tracking filter are presented. The common structure of these approaches are: (1) to have a bank of filters to process the received signals (signals are separated into a few sections as the excitation frequency sweeps from low to high) from the test specimen, (2) to use the Welsh method to compute the spectral density via the FFT (Fast Fourier Transform) algorithm. The bandpass filter bank is employed in the 1st approach to remove the noise which is contained in all sections of received signals. The decimation and interpolation schemes are used in the 2nd approach to reduce the unnecessary computations which exist in the over sampled sections of received signals. The modulation and demodulation schemes (for high-frequency sections only) combined with decimation and interpolation schemes (for over sampled section only) are employed in the 3rd approach. The modulation and demodulation schemes are used to shift the spectrum from high-frequency to low-frequency for simplying the filtering process via LPFs (Low Pass Filters).

  19. Adaptive filters: stable but divergent

    NASA Astrophysics Data System (ADS)

    Rupp, Markus

    2015-12-01

    The pros and cons of a quadratic error measure in the context of various applications have often been discussed. In this tutorial, we argue that it is not only a suboptimal but definitely the wrong choice when describing the stability behavior of adaptive filters. We take a walk through the past and recent history of adaptive filters and present 14 canonical forms of adaptive algorithms and even more variants thereof contrasting their mean-square with their l 2-stability conditions. In particular, in safety critical applications, the convergence in the mean-square sense turns out to provide wrong results, often not leading to stability at all. Only the robustness concept with its l 2-stability conditions ensures the absence of divergence.

  20. Speed adaptation as Kalman filtering.

    PubMed

    Barraza, Jose F; Grzywacz, Norberto M

    2008-10-01

    If the purpose of adaptation is to fit sensory systems to different environments, it may implement an optimization of the system. What the optimum is depends on the statistics of these environments. Therefore, the system should update its parameters as the environment changes. A Kalman-filtering strategy performs such an update optimally by combining current estimations of the environment with those from the past. We investigate whether the visual system uses such a strategy for speed adaptation. We performed a matching-speed experiment to evaluate the time course of adaptation to an abrupt velocity change. Experimental results are in agreement with Kalman-modeling predictions for speed adaptation. When subjects adapt to a low speed and it suddenly increases, the time course of adaptation presents two phases, namely, a rapid decrease of perceived speed followed by a slower phase. In contrast, when speed changes from fast to slow, adaptation presents a single phase. In the Kalman-model simulations, this asymmetry is due to the prevalence of low speeds in natural images. However, this asymmetry disappears both experimentally and in simulations when the adapting stimulus is noisy. In both transitions, adaptation now occurs in a single phase. Finally, the model also predicts the change in sensitivity to speed discrimination produced by the adaptation.

  1. Adaptive spatial filtering for off-axis digital holographic microscopy based on region recognition approach with iterative thresholding

    NASA Astrophysics Data System (ADS)

    He, Xuefei; Nguyen, Chuong Vinh; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R.; Rug, Melanie; Maier, Alexander G.; Lee, Woei Ming

    2016-12-01

    Here we propose a region-recognition approach with iterative thresholding, which is adaptively tailored to extract the appropriate region or shape of spatial frequency. In order to justify the method, we tested it with different samples and imaging conditions (different objectives). We demonstrate that our method provides a useful method for rapid imaging of cellular dynamics in microfluidic and cell cultures.

  2. Real time microcontroller implementation of an adaptive myoelectric filter.

    PubMed

    Bagwell, P J; Chappell, P H

    1995-03-01

    This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

  3. 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.

  4. DDP-116 general digital filtering

    NASA Technical Reports Server (NTRS)

    Jones, J. A.; Graham, R. J.

    1972-01-01

    The methods are described for calibrating, selecting filter weights, filtering, and computing filter response functions. These methods are computed on a statistical analyzer (STAN) system with a Honeywell DDP-116 central processor. The following filter types are computed: all pass, low pass, high pass, band pass, band rejection, and derivative.

  5. FORTRAN IV Digital Filter Design Programs. Digital Systems Education Project.

    ERIC Educational Resources Information Center

    Reuss, E.; And Others

    The goals of the Digital Systems Education Project (DISE) include the development and distribution of educational/instructional materials in the digital systems area. Toward that end, this document contains three reports: (1) A FORTRAN IV Design Program for Low-Pass Butterworth and Chebychev Digital Filters; (2) A FORTRAN IV Design Program for…

  6. Moment calculations by digital filters

    NASA Astrophysics Data System (ADS)

    Budrikis, Z. L.; Hatamian, M.

    1984-02-01

    A simple recursive algorithm is presented for computing moments of two-dimensional integer arrays. It uses only additions, and can be implemented for high speed and real time computation at video rates. The Complementary Metal-Oxide Semiconductor (CMOS), Very Large-Scale Integrated (VLSI) implementation of the algorithm in a single chip that can calculate the 16 moments on a 512 x 512 array of 8-bit integers in real time (at video rate) is described. Such a chip can have potential applications in image processing, graphics, and robotics. The basic building block of the system is a single-pole digital filter that is implemented by recursive addition. The complexities involved in designing the chip, as well as its area, are significantly reduced by taking advantage of the fact that the column samples of the data array can be processed at a much slower rate than the row samples. An estimate of the chip area obtained from the layout design of the individual cells is given.

  7. A structure for digital notch filters

    NASA Technical Reports Server (NTRS)

    Abu-El-haija, A. I.; Peterson, A. M.

    1979-01-01

    Narrow-band digital notch filters have their poles near the unit circle. As the sampling rate is increased, the poles move towards Z = +1. Implementing such filters requires long registers to overcome the sensitivity and roundoff errors. A filter structure based on digital incremental computers is proposed which has low sensitivity and round-off errors, and simple hardware implementation. The filter structure can be directly used on differentially pulse-code modulated signals. Hardware multipliers are not required as the poles approach z = +1, and excellent results can be obtained using multipliers with very short word lengths, or with small size read-only memories.

  8. Speckle reduction in optical coherence tomography images using digital filtering

    PubMed Central

    Ozcan, Aydogan; Bilenca, Alberto; Desjardins, Adrien E.; Bouma, Brett E.; Tearney, Guillermo J.

    2009-01-01

    Speckle noise is a ubiquitous artifact that limits the interpretation of optical coherence tomography images. Here we apply various speckle-reduction digital filters to optical coherence tomography images and compare their performance. Our results indicate that shift-invariant, nonorthogonal wavelet-transform-based filters together with enhanced Lee and adaptive Wiener filters can significantly reduce speckle and increase the signal-to-noise ratio, while preserving strong edges. The speckle reduction capabilities of these filters are also compared with speckle reduction from incoherent angular compounding. Our results suggest that by using these digital filters, the number of individual angles required to attain a certain level of speckle reduction can be decreased. PMID:17728812

  9. Adaptive filtering with correlated state noise

    NASA Technical Reports Server (NTRS)

    Argentiero, P.

    1972-01-01

    An adaptive filter which uses a minimum variance criteria to estimate state noise covariance is presented. It is not necessary to assume white state noise in order to implement the filter. Simulation results are given which demonstrate that the filter tracks a satellite in the presence of modeling errors better than a conventional minimum variance filter with state noise. It is also shown that the propagated convariance matrix of the filter is an accurate indicator of the filter's performance.

  10. Coordinated adaptive filters for motion simulators.

    NASA Technical Reports Server (NTRS)

    Parrish, R. V.; Dieudonne, J. E.; Bowles, R. L.; Martin, D. J.

    1973-01-01

    A new approach to providing motion drive signals to a flight simulator utilizing coordinated adaptive filters is presented. Some motivation for the use of coordinated washout is discussed, along with conditions that determine the burden of coordination. The coordinated adaptive filters are derived, based on continuous steepest descent, and the application of the filters to simulated flight data is demonstrated.

  11. AN OPTICAL CATALOG OF GALAXY CLUSTERS OBTAINED FROM AN ADAPTIVE MATCHED FILTER FINDER APPLIED TO SLOAN DIGITAL SKY SURVEY DATA RELEASE 6

    SciTech Connect

    Szabo, T.; Pierpaoli, E.; Pipino, A.; Dong, F.; Gunn, J. E-mail: pierpaol@usc.edu

    2011-07-20

    We present a new cluster catalog extracted from the Sloan Digital Sky Survey Data Release 6 (SDSS DR6) using an adaptive matched filter (AMF) cluster finder. We identify 69,173 galaxy clusters in the redshift range 0.045 {<=} z < 0.78 in 8420 deg{sup 2} of the sky. We provide angular position, redshift, richness, core, and virial radii estimates for these clusters, as well as an error analysis for each of these quantities. We also provide a catalog of more than 205,000 galaxies representing the three brightest galaxies in the r band which are possible brightest cluster galaxy (BCG) candidates. We show basic properties of the BCG candidates and study how their luminosity scales in redshift and cluster richness. We compare our catalog with the maxBCG and GMBCG catalogs, as well as with that of Wen et al. We match between 30% and 50% of clusters between catalogs over all overlapping redshift ranges. We find that the percentage of matches increases with the richness for all catalogs. We cross match the AMF catalog with available X-ray data in the same area of the sky and find 539 matches, 119 of which with temperature measurements. We present scaling relations between optical and X-ray properties and cluster center comparison. We find that both {Lambda}{sub 200} and R{sub 200} correlate well with both L{sub X} and T{sub X} , with no significant difference in trend if we restrict the matches to flux-limited X-ray samples.

  12. Tree-structured nonlinear filters in digital mammography

    SciTech Connect

    Qian, W.; Clarke, L.P.; Kallergi, M.; Clark, R.A. )

    1994-03-01

    A new class of nonlinear filters with more robust characteristics for noise suppression and detail preservation is proposed for processing digital mammographic images. The new algorithm consists of two major filtering blocks: (a) a multistage tree-structured filter for image enhancement that uses central weighted median filters as basic sub-filtering blocks and (b) a dispersion edge detector. The design of the algorithm also included the use of linear and curved windows to determine whether variable shape windowing could improve detail preservation. First, the noise-suppressing properties of the tree-structured filter were compared to single filters, namely the median and the central weighted median with conventional square and variable shape adaptive windows; simulated images were used for this purpose. Second, the edge detection properties of the tree-structured filter cascaded with the dispersion edge detector were compared to the performance of the dispersion edge detector alone, the Sobel operator, and the single median filter cascaded with the dispersion edge detector. Selected mammographic images with representative biopsy-proven malignancies were processed with all methods and the results were visually evaluated by an expert mammographer. In all applications, the proposed filter suggested better detail preservation, noise suppression, and edge detection than all other approaches and it may prove to be a useful tool for computer-assisted diagnosis in digital mammography.

  13. Tree-structured nonlinear filters in digital mammography.

    PubMed

    Qian, W; Clarke, L P; Kallergi, M; Clark, R A

    1994-01-01

    A new class of nonlinear filters with more robust characteristics for noise suppression and detail preservation is proposed for processing digital mammographic images. The new algorithm consists of two major filtering blocks: (a) a multistage tree-structured filter for image enhancement that uses central weighted median filters as basic sub-filtering blocks and (b) a dispersion edge detector. The design of the algorithm also included the use of linear and curved windows to determine whether variable shape windowing could improve detail preservation. First, the noise-suppressing properties of the tree-structured filter were compared to single filters, namely the median and the central weighted median with conventional square and variable shape adaptive windows; simulated images were used for this purpose. Second, the edge detection properties of the tree-structured filter cascaded with the dispersion edge detector were compared to the performance of the dispersion edge detector alone, the Sobel operator, and the single median filter cascaded with the dispersion edge detector. Selected mammographic images with representative biopsy-proven malignancies were processed with all methods and the results were visually evaluated by an expert mammographer. In all applications, the proposed filter suggested better detail preservation, noise suppression, and edge detection than all other approaches and it may prove to be a useful tool for computer-assisted diagnosis in digital mammography.

  14. CMOS analog switches for adaptive filters

    NASA Technical Reports Server (NTRS)

    Dixon, C. E.

    1980-01-01

    Adaptive active low-pass filters incorporate CMOS (Complimentary Metal-Oxide Semiconductor) analog switches (such as 4066 switch) that reduce variation in switch resistance when filter is switched to any selected transfer function.

  15. Digital Filters for Digital Phase-locked Loops

    NASA Technical Reports Server (NTRS)

    Simon, M.; Mileant, A.

    1985-01-01

    An s/z hybrid model for a general phase locked loop is proposed. The impact of the loop filter on the stability, gain margin, noise equivalent bandwidth, steady state error and time response is investigated. A specific digital filter is selected which maximizes the overall gain margin of the loop. This filter can have any desired number of integrators. Three integrators are sufficient in order to track a phase jerk with zero steady state error at loop update instants. This filter has one zero near z = 1.0 for each integrator. The total number of poles of the filter is equal to the number of integrators plus two.

  16. Smartphone adapters for digital photomicrography

    PubMed Central

    Roy, Somak; Pantanowitz, Liron; Amin, Milon; Seethala, Raja R.; Ishtiaque, Ahmed; Yousem, Samuel A.; Parwani, Anil V.; Cucoranu, Ioan; Hartman, Douglas J.

    2014-01-01

    Background: Photomicrographs in Anatomic Pathology provide a means of quickly sharing information from a glass slide for consultation, education, documentation and publication. While static image acquisition historically involved the use of a permanently mounted camera unit on a microscope, such cameras may be expensive, need to be connected to a computer, and often require proprietary software to acquire and process images. Another novel approach for capturing digital microscopic images is to use smartphones coupled with the eyepiece of a microscope. Recently, several smartphone adapters have emerged that allow users to attach mobile phones to the microscope. The aim of this study was to test the utility of these various smartphone adapters. Materials and Methods: We surveyed the market for adapters to attach smartphones to the ocular lens of a conventional light microscope. Three adapters (Magnifi, Skylight and Snapzoom) were tested. We assessed the designs of these adapters and their effectiveness at acquiring static microscopic digital images. Results: All adapters facilitated the acquisition of digital microscopic images with a smartphone. The optimal adapter was dependent on the type of phone used. The Magnifi adapters for iPhone were incompatible when using a protective case. The Snapzoom adapter was easiest to use with iPhones and other smartphones even with protective cases. Conclusions: Smartphone adapters are inexpensive and easy to use for acquiring digital microscopic images. However, they require some adjustment by the user in order to optimize focus and obtain good quality images. Smartphone microscope adapters provide an economically feasible method of acquiring and sharing digital pathology photomicrographs. PMID:25191623

  17. Digital filters in radio detectors of the Pierre Auger Observatory

    NASA Astrophysics Data System (ADS)

    Szadkowski, Zbigniew; Głas, Dariusz

    2016-09-01

    Ultra-high energy cosmic rays (UHECR) are the most energetic observable particles in Universe. The main challenge in detecting such energetic particles is very small flux. Most experiments focus on detecting Extensive Air Showers (EAS), initiated by primary UHECR particle in interaction with particles of the atmosphere. One of the observation method is detecting the radio emission from the EAS. This emission was theoretically suggested in 1960's, but technological development allow successful detection only in the last several years. This detection technique is used by Auger Engineering Radio Array (AERA). Most of the emission can be observed in frequency band 30 - 80 MHz, however this range is contaminated by radio frequency interferences (RFI). These contaminations must be reduced to decrease false trigger rate. Currently, there are two kind of digital filters used in AERA. One of them is median filter, based on Fast Fourier Transform. Second one is the notch filter, which is a composition of four infinite impulse response filters. Those filters have properly work in AERA radio detectors for many years. Dynamic progress in electronics allows to use more sophisticated algorithms of RFI reduction. Planned modernization of the AERA radio detectors' electronic allows to use finte impulse response (FIR) filters, which can fast adapt to environment conditions. These filters are: Least Mean Squares (LMS) filter and filter based on linear prediction (LP). Tests of new kind of filters are promising and show that FIR filters can be used in next generation radio detectors in AERA experiment.

  18. 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.

  19. Performance of an Adaptive Matched Filter Using the Griffiths Algorithm

    DTIC Science & Technology

    1988-12-01

    Simon. Introduction to Adaptive Filters. New York: Macmillan Publishing Company, 1984. 11. Sklar , Bernard . Digital Communications Fundamentals and...York: Harper and Row, 1986. 8. Widrow, Bernard and Samuel D. Stearns. Adaptive Signal Processing. Englewood Cliffs, N.J.: Prentice-Hall, 1985. 9...Fourier Transforms. and Optics. New York: John Wiley and Sons, 1978. 15. Widrow, Bernard and others. "The Complex LMS Algorithm," Proceedings of the IEEE

  20. 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.

  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. 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

  3. Adaptive marginal median filter for colour images.

    PubMed

    Morillas, Samuel; Gregori, Valentín; Sapena, Almanzor

    2011-01-01

    This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.

  4. 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.

  5. Suppression of Biodynamic Interference by Adaptive Filtering

    NASA Technical Reports Server (NTRS)

    Velger, M.; Merhav, S. J.; Grunwald, A. J.

    1984-01-01

    Preliminary experimental results obtained in moving base simulator tests are presented. Both for pursuit and compensatory tracking tasks, a strong deterioration in tracking performance due to biodynamic interference is found. The use of adaptive filtering is shown to substantially alleviate these effects, resulting in a markedly improved tracking performance and reduction in task difficulty. The effect of simulator motion and of adaptive filtering on human operator describing functions is investigated. Adaptive filtering is found to substantially increase pilot gain and cross-over frequency, implying a more tight tracking behavior. The adaptive filter is found to be effective in particular for high-gain proportional dynamics, low display forcing function power and for pursuit tracking task configurations.

  6. 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…

  7. Integrated-Circuit Active Digital Filter

    NASA Technical Reports Server (NTRS)

    Nathan, R.

    1986-01-01

    Pipeline architecture with parallel multipliers and adders speeds calculation of weighted sums. Picture-element values and partial sums flow through delay-adder modules. After each cycle or time unit of calculation, each value in filter moves one position right. Digital integrated-circuit chips with pipeline architecture rapidly move 35 X 35 two-dimensional convolutions. Need for such circuits in image enhancement, data filtering, correlation, pattern extraction, and synthetic-aperture-radar image processing: all require repeated calculations of weighted sums of values from images or two-dimensional arrays of data.

  8. Coherent Digital Holographic Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Liu, Changgeng

    A new type of adaptive optics (AO) based on the principles of digital holography (DH) is proposed and developed for the use in wide-field and confocal retinal imaging. Digital holographic adaptive optics (DHAO) dispenses with the wavefront sensor and wavefront corrector of the conventional AO system. DH is an emergent imaging technology that gives direct numerical access to the phase of the optical field, thus allowing precise control and manipulation of the optical field. Incorporation of DH in an ophthalmic imaging system can lead to versatile imaging capabilities at substantially reduced complexity and cost of the instrument. A typical conventional AO system includes several critical hardware pieces: spatial light modulator, lenslet array, and a second CCD camera in addition to the camera for imaging. The proposed DHAO system replaces these hardware components with numerical processing for wavefront measurement and compensation of aberration through the principles of DH. (Abstract shortened by UMI.).

  9. Digital filter design approach for SQUID gradiometers

    SciTech Connect

    Bruno, A.C.; Ribeiro, P.C.

    1988-04-15

    A review of the traditional method for designing gradiometers is made. A nonrecursive digital filter model for the gradiometer is presented, giving a new set of parameters for the gradiometer identification. Some designs are analyzed using the proposed set. As an example, a true differentiator is designed to be used as the SQUID input coil. It is shown that the differentiator has the same noise rejection as the conventional gradiometer but provides more signal sensitivity.

  10. Digitally Programmable Active Switched Capacitor Filters.

    DTIC Science & Technology

    1987-03-01

    POSTGRADUATE SCHOOL Monterey, California n FILE WRY In THESIS DIGITALLY PROGRAMMABLE ACTIVE SWITCHED CAPACITOR FILTERS by Yalkin, Cengiz March 1987 Thesis ...COVERED 14 DATE OF REPORT (Year. Month. Day) 15 PAGE (OkNTMaster’s Thesis FROM ’O 1987 March 89 𔄀 SLP-ILENIENTARY NOTATION COSArI CODES 18 SUBJECT...Sheri chael, Thesis Advisor Roberto Cristi, Second Reader "harriet Rigas, Clirman, Department of Electrical and Computer En’ ineering Gordon E

  11. Building block for an orthonormal-lattice-filter adaptive network

    NASA Astrophysics Data System (ADS)

    Gabriel, W. F.

    1980-07-01

    The recent algorithm for a multistage multichannel orthonormal lattice filter proposed by M. Aftab Alam is a welcome addition to the library of adaptive-processing algorithms and provides a flexible alternative to the conventional approach of an optimum Weiner filter. This algorithm is based on a Gram-Schmidt orthonormalization procedure which is similar to cascade adaptive processing techniques described in earlier works. One of the most desirable features of this type of processing network is that it can be implemented with simple one-stage orthogonal-filter building blocks which directly filter the input data samples. These building blocks are the major subject of this report, and a particular configuration is developed based on a modified version of the familiar Howells-Applebaum algorithm. It can be implemented in either analog or digital form, data storage is not required, it is unconditionally stable, speed of convergence is no longer a problem, and the design is simple. The performance characteristics of a complete orthogonal-lattice-filter network operating in the spacial domain were simulated for example cases of one, two, and three strong incoherent signal sources spaced within a beamwidth for a eight-element linear-array antenna. The adaptive spacial filter patterns and the transient responses demonstrate that the building block has sufficient transient-response speed and control to permit full use of the processing capabilities inherent in a Gram-Schmidt cascade network.

  12. Adaptive Embedded Digital System for Plasma Diagnostics

    NASA Astrophysics Data System (ADS)

    González, Angel; Rodríguez, Othoniel; Mangual, Osvaldo; Ponce, Eduardo; Vélez, Xavier

    2014-05-01

    An Adaptive Embedded Digital System to perform plasma diagnostics using electrostatic probes was developed at the Plasma Engineering Laboratory at Polytechnic University of Puerto Rico. The system will replace the existing instrumentation at the Laboratory, using reconfigurable hardware to minimize the equipment and software needed to perform diagnostics. The adaptability of the design resides on the possibility of replacing the computational algorithm on the fly, allowing to use the same hardware for different probes. The system was prototyped using Very High Speed Integrated Circuits Hardware Description Language (VHDL) into an Field Programmable Gate Array (FPGA) board. The design of the Embedded Digital System includes a Zero Phase Digital Filter, a Derivative Unit, and a Computational Unit designed using the VHDL-2008 Support Library. The prototype is able to compute the Plasma Electron Temperature and Density from a Single Langmuir probe. The system was tested using real data previously acquired from a single Langmuir probe. The plasma parameters obtained from the embedded system were compared with results computed using matlab yielding excellent matching. The new embedded system operates on 4096 samples versus 500 on the previous system, and completes its computations in 26 milliseconds compared with about 15 seconds on the previous system.

  13. Local image registration by adaptive filtering.

    PubMed

    Caner, Gulcin; Tekalp, A Murat; Sharma, Gaurav; Heinzelman, Wendi

    2006-10-01

    We propose a new adaptive filtering framework for local image registration, which compensates for the effect of local distortions/displacements without explicitly estimating a distortion/displacement field. To this effect, we formulate local image registration as a two-dimensional (2-D) system identification problem with spatially varying system parameters. We utilize a 2-D adaptive filtering framework to identify the locally varying system parameters, where a new block adaptive filtering scheme is introduced. We discuss the conditions under which the adaptive filter coefficients conform to a local displacement vector at each pixel. Experimental results demonstrate that the proposed 2-D adaptive filtering framework is very successful in modeling and compensation of both local distortions, such as Stirmark attacks, and local motion, such as in the presence of a parallax field. In particular, we show that the proposed method can provide image registration to: a) enable reliable detection of watermarks following a Stirmark attack in nonblind detection scenarios, b) compensate for lens distortions, and c) align multiview images with nonparametric local motion.

  14. Adaptive filtering for the lattice Boltzmann method

    NASA Astrophysics Data System (ADS)

    Marié, Simon; Gloerfelt, Xavier

    2017-03-01

    In this study, a new selective filtering technique is proposed for the Lattice Boltzmann Method. This technique is based on an adaptive implementation of the selective filter coefficient σ. The proposed model makes the latter coefficient dependent on the shear stress in order to restrict the use of the spatial filtering technique in sheared stress region where numerical instabilities may occur. Different parameters are tested on 2D test-cases sensitive to numerical stability and on a 3D decaying Taylor-Green vortex. The results are compared to the classical static filtering technique and to the use of a standard subgrid-scale model and give significant improvements in particular for low-order filter consistent with the LBM stencil.

  15. Matched filter based iterative adaptive approach

    NASA Astrophysics Data System (ADS)

    Nepal, Ramesh; Zhang, Yan Rockee; Li, Zhengzheng; Blake, William

    2016-05-01

    Matched Filter sidelobes from diversified LPI waveform design and sensor resolution are two important considerations in radars and active sensors in general. Matched Filter sidelobes can potentially mask weaker targets, and low sensor resolution not only causes a high margin of error but also limits sensing in target-rich environment/ sector. The improvement in those factors, in part, concern with the transmitted waveform and consequently pulse compression techniques. An adaptive pulse compression algorithm is hence desired that can mitigate the aforementioned limitations. A new Matched Filter based Iterative Adaptive Approach, MF-IAA, as an extension to traditional Iterative Adaptive Approach, IAA, has been developed. MF-IAA takes its input as the Matched Filter output. The motivation here is to facilitate implementation of Iterative Adaptive Approach without disrupting the processing chain of traditional Matched Filter. Similar to IAA, MF-IAA is a user parameter free, iterative, weighted least square based spectral identification algorithm. This work focuses on the implementation of MF-IAA. The feasibility of MF-IAA is studied using a realistic airborne radar simulator as well as actual measured airborne radar data. The performance of MF-IAA is measured with different test waveforms, and different Signal-to-Noise (SNR) levels. In addition, Range-Doppler super-resolution using MF-IAA is investigated. Sidelobe reduction as well as super-resolution enhancement is validated. The robustness of MF-IAA with respect to different LPI waveforms and SNR levels is also demonstrated.

  16. Digital adaptive flight controller development

    NASA Technical Reports Server (NTRS)

    Kaufman, H.; Alag, G.; Berry, P.; Kotob, S.

    1974-01-01

    A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Two designs are described for an example aircraft. Each of these designs uses a weighted least squares procedure to identify parameters defining the dynamics of the aircraft. The two designs differ in the way in which control law parameters are determined. One uses the solution of an optimal linear regulator problem to determine these parameters while the other uses a procedure called single stage optimization. Extensive simulation results and analysis leading to the designs are presented.

  17. Fast digital noise filter capable of locating spectral peaks and shoulders

    NASA Technical Reports Server (NTRS)

    Edwards, T. R.; Knight, R. D.

    1972-01-01

    Experimental data frequently have a poor signal-to-noise ratio which one would like to enhance before analysis. With the data in digital form, this may be accomplished by means of a digital filter. A fast digital filter based upon the principle of least squares and using the techniques of convoluting integers is described. In addition to smoothing, this filter also is capable of accurately and simultaneously locating spectral peaks and shoulders. This technique has been adapted into a computer subroutine, and results of several test cases are shown, including mass spectral data and data from a proportional counter for the High Energy Astronomy Observatory.

  18. Color image diffusion using adaptive bilateral filter.

    PubMed

    Xie, Jun; Ann Heng, Pheng

    2005-01-01

    In this paper, we propose an approach to diffuse color images based on the bilateral filter. Real image data has a level of uncertainty that is manifested in the variability of measures assigned to pixels. This uncertainty is usually interpreted as noise and considered an undesirable component of the image data. Image diffusion can smooth away small-scale structures and noise while retaining important features, thus improving the performances for many image processing algorithms such as image compression, segmentation and recognition. The bilateral filter is noniterative, simple and fast. It has been shown to give similar and possibly better filtering results than iterative approaches. However, the performance of this filter is greatly affected by the choose of the parameters of filtering kernels. In order to remove noise and maintain the significant features on images, we extend the bilateral filter by introducing an adaptive domain spread into the nonlinear diffusion scheme. For color images, we employ the CIE-Lab color system to describe input images and the filtering process is operated using three channels together. Our analysis shows that the proposed method is more suitable for preserving strong edges on noisy images than the original bilateral filter. Empirical results on both nature images and color medical images confirm the novel method's advantages, and show it can diffuse various kinds of color images correctly and efficiently.

  19. Digital filtering of plume emission spectra

    NASA Technical Reports Server (NTRS)

    Madzsar, George C.

    1990-01-01

    Fourier transformation and digital filtering techniques were used to separate the superpositioned spectral phenomena observed in the exhaust plumes of liquid propellant rocket engines. Space shuttle main engine (SSME) spectral data were used to show that extraction of spectral lines in the spatial frequency domain does not introduce error, and extraction of the background continuum introduces only minimal error. Error introduced during band extraction could not be quantified due to poor spectrometer resolution. Based on the atomic and molecular species found in the SSME plume, it was determined that spectrometer resolution must be 0.03 nm for SSME plume spectral monitoring.

  20. Spectral analysis and filtering techniques in digital spatial data processing

    USGS Publications Warehouse

    Pan, Jeng-Jong

    1989-01-01

    A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

  1. Digital Integrate-And-Dump Filter With Offset Sampling

    NASA Technical Reports Server (NTRS)

    Sadr, R.; Hurd, W. J.

    1989-01-01

    Detection of weak signals improved slightly. Digital integrate-and-dump filter proposed for detection of weak rectangular-pulse signals corrupted by additive white Gaussian noise. Theory of filter takes account of degradation of performance caused by offset sampling.

  2. Image Restoration on Copper Inscription Using Nonlinear Filtering and Adaptive Threshold

    NASA Astrophysics Data System (ADS)

    Chairy, A.; Suprapto, Y. K.; Yuniarno, E. M.

    2017-01-01

    Inscription is an important document inherited by history of kingdom. Inscription made on hard stuff such as stone and copper. Therefore it is necessary digitizing documents, to keep the authenticity of the document. But the document of the historical heritage have disruption on inscription plate which be called noise. So that, it is necessary to reduce the noise in the image of the inscription, to ease the documentation of historical digital. Then, separation between the background and the writing object carved on inscription is conducted so easy to read. This research is using nonlinear filtering method to reduce the noise and adaptive threshold to separate between the background and letter inscription. Nonlinear filtering method used is median filter, harmonic mean filter and contra harmonic mean filter, whereas in the adaptive threshold using adaptive mean and adaptive median threshold. The results of this research is using measurement methods MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio) and SNR (Signal to Noise Ratio).

  3. 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.

  4. Gearbox Fault Diagnosis Using Adaptive Wavelet Filter

    NASA Astrophysics Data System (ADS)

    LIN, J.; ZUO, M. J.

    2003-11-01

    Vibration signals from a gearbox are usually noisy. As a result, it is difficult to find early symptoms of a potential failure in a gearbox. Wavelet transform is a powerful tool to disclose transient information in signals. An adaptive wavelet filter based on Morlet wavelet is introduced in this paper. The parameters in the Morlet wavelet function are optimised based on the kurtosis maximisation principle. The wavelet used is adaptive because the parameters are not fixed. The adaptive wavelet filter is found to be very effective in detection of symptoms from vibration signals of a gearbox with early fatigue tooth crack. Two types of discrete wavelet transform (DWT), the decimated with DB4 wavelet and the undecimated with harmonic wavelet, are also used to analyse the same signals for comparison. No periodic impulses appear on any scale in either DWT decomposition.

  5. Kalman filter based control for Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Petit, Cyril; Quiros-Pacheco, Fernando; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

    2004-12-01

    Classical Adaptive Optics suffer from a limitation of the corrected Field Of View. This drawback has lead to the development of MultiConjugated Adaptive Optics. While the first MCAO experimental set-ups are presently under construction, little attention has been paid to the control loop. This is however a key element in the optimization process especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications : simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering which seems a very promising solution. Following the work of Brice Leroux, we focus on a frequential characterization of kalman filters, computing a transfer matrix. The result brings much information about their behaviour and allows comparisons with classical controllers. It also appears that straightforward improvements of the system models can lead to static aberrations and vibrations filtering. Simulation results are proposed and analysed thanks to our frequential characterization. Related problems such as model errors, aliasing effect reduction or experimental implementation and testing of Kalman filter control loop on a simplified MCAO experimental set-up could be then discussed.

  6. Tunable photonic filters: a digital signal processing design approach.

    PubMed

    Binh, Le Nguyen

    2009-05-20

    Digital signal processing techniques are used for synthesizing tunable optical filters with variable bandwidth and centered reference frequency including the tunability of the low-pass, high-pass, bandpass, and bandstop optical filters. Potential applications of such filters are discussed, and the design techniques and properties of recursive digital filters are outlined. The basic filter structures, namely, the first-order all-pole optical filter (FOAPOF) and the first-order all-zero optical filter (FOAZOF), are described, and finally the design process of tunable optical filters and the designs of the second-order Butterworth low-pass, high-pass, bandpass, and bandstop tunable optical filters are presented. Indeed, we identify that the all-zero and all-pole networks are equivalent with well known principles of optics of interference and resonance, respectively. It is thus very straightforward to implement tunable optical filters, which is a unique feature.

  7. 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.

  8. Parallel digital modem using multirate digital filter banks

    NASA Technical Reports Server (NTRS)

    Sadr, Ramin; Vaidyanathan, P. P.; Raphaeli, Dan; Hinedi, Sami

    1994-01-01

    A new class of architectures for an all-digital modem is presented in this report. This architecture, referred to as the parallel receiver (PRX), is based on employing multirate digital filter banks (DFB's) to demodulate, track, and detect the received symbol stream. The resulting architecture is derived, and specifications are outlined for designing the DFB for the PRX. The key feature of this approach is a lower processing rate then either the Nyquist rate or the symbol rate, without any degradation in the symbol error rate. Due to the freedom in choosing the processing rate, the designer is able to arbitrarily select and use digital components, independent of the speed of the integrated circuit technology. PRX architecture is particularly suited for high data rate applications, and due to the modular structure of the parallel signal path, expansion to even higher data rates is accommodated with each. Applications of the PRX would include gigabit satellite channels, multiple spacecraft, optical links, interactive cable-TV, telemedicine, code division multiple access (CDMA) communications, and others.

  9. 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.

  10. A practical sub-space adaptive filter.

    PubMed

    Zaknich, A

    2003-01-01

    A Sub-Space Adaptive Filter (SSAF) model is developed using, as a basis, the Modified Probabilistic Neural Network (MPNN) and its extension the Tuneable Approximate Piecewise Linear Regression (TAPLR) model. The TAPLR model can be adjusted by a single smoothing parameter continuously from the best piecewise linear model in each sub-space to the best approximately piecewise linear model over the whole data space. A suitable value in between ensures that all neighbouring piecewise linear models merge together smoothly at their boundaries. This model was developed by altering the form of the MPNN, a network used for general nonlinear regression. The MPNNs special structure allows it to be easily used to model a process by appropriately weighting piecewise linear models associated with each of the network's radial basis functions. The model has now been further extended to allow each piecewise linear model section to be adapted separately as new data flows through it. By doing this, the proposed SSAF model represents a learning/filtering method for nonlinear processes that provides one solution to the stability/plasticity dilemma associated with standard adaptive filters.

  11. 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.

  12. Low Power Systolic Array Based Digital Filter for DSP Applications

    PubMed Central

    Karthick, S.; Valarmathy, S.; Prabhu, E.

    2015-01-01

    Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP) based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures. PMID:25922854

  13. Low Power Systolic Array Based Digital Filter for DSP Applications.

    PubMed

    Karthick, S; Valarmathy, S; Prabhu, E

    2015-01-01

    Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP) based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.

  14. ROUND-OFF ERROR OF FLOATING-POINT DIGITAL FILTERS,

    DTIC Science & Technology

    the filter, the problem has been studied extensively. The only result available for floating - point arithmetic realization of digital filters is an...paper, a statistic approach is adopted to treat the round-off error problem for floating - point computer realization of filters. (Author)

  15. Nonlinear adaptive filtering of stimulus artifact.

    PubMed

    Grieve, R; Parker, P A; Hudgins, B; Englehart, K

    2000-03-01

    Noninvasive measurements of somatosensory evoked potentials have both clinical and research applications. The electrical artifact which results from the stimulus is an interference which can distort the evoked signal, and introduce errors in response onset timing estimation. Given that this interference is synchronous with the evoked signal, it cannot be reduced by the conventional technique of ensemble averaging. The technique of adaptive noise cancelling has potential in this regard however, and has been used effectively in other similar problems. An adaptive noise cancelling filter which uses a neural network as the adaptive element is investigated in this application. The filter is implemented and performance determined in the cancelling of artifact for in vivo measurements on the median nerve. A technique of segmented neural network training is proposed in which the network is trained on that segment of the record time window which does not contain the evoked signal. The neural network is found to generalize well from this training to include the segment of the window containing the evoked signal. Both quantitative and qualitative measures show that significant stimulus artifact reduction is achieved.

  16. Statistical properties of filtered pseudo-random digital sequences

    NASA Technical Reports Server (NTRS)

    Weathers, G. D.

    1972-01-01

    A tutorial presentation of pseudo-random digital sequences, their generation and properties is given. The results of a study of filtered pseudo-random sequences, and their statistical properties are reported. The generator, to be used in a telemetry communications system test unit, must generate its pseudo-random signals by filtering a long digital sequence. Desired signal properties include: (1) approximately Gaussian amplitude probability density function; and (2) signal spectral envelope approximately that of the filter being used in the generator. Filtered maximum-length sequences have been used for this, and similar applications in the past. The results were good for low-pass filtered sequences when the ratio of digital clock frequency to filter cutoff frequency was between fifteen and twenty. However, for higher values of this ratio, a definite skewing of the amplitude density function was observed.

  17. Improved adaptive complex diffusion despeckling filter.

    PubMed

    Bernardes, Rui; Maduro, Cristina; Serranho, Pedro; Araújo, Adérito; Barbeiro, Sílvia; Cunha-Vaz, José

    2010-11-08

    Despeckling optical coherence tomograms from the human retina is a fundamental step to a better diagnosis or as a preprocessing stage for retinal layer segmentation. Both of these applications are particularly important in monitoring the progression of retinal disorders. In this study we propose a new formulation for a well-known nonlinear complex diffusion filter. A regularization factor is now made to be dependent on data, and the process itself is now an adaptive one. Experimental results making use of synthetic data show the good performance of the proposed formulation by achieving better quantitative results and increasing computation speed.

  18. Microcomputer program for the design of digital filters.

    PubMed

    Johnson, A T

    1985-12-01

    The program presented here is intended to be a design device and learning tool for digital filters. Digital filters designed with the program can be implemented by incorporation within the data analysis programs of the user. The program is written in BASIC for use with the IBM-PC, is intended to be user-friendly, and includes a great deal of filter assistance not found in other programs. An example of program use shows how one filter can be used to remove noise from respiratory waveform data.

  19. Research in digital adaptive flight controllers

    NASA Technical Reports Server (NTRS)

    Kaufman, H.

    1976-01-01

    A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Both explicit controllers which directly utilize parameter identification and implicit controllers which do not require identification were considered. Extensive analytical and simulation efforts resulted in the recommendation of two explicit digital adaptive flight controllers. Interface weighted least squares estimation procedures with control logic were developed using either optimal regulator theory or with control logic based upon single stage performance indices.

  20. Bayesian adaptive estimation of the auditory filter.

    PubMed

    Shen, Yi; Richards, Virginia M

    2013-08-01

    A Bayesian adaptive procedure for estimating the auditory-filter shape was proposed and evaluated using young, normal-hearing listeners at moderate stimulus levels. The resulting quick-auditory-filter (qAF) procedure assumed the power spectrum model of masking with the auditory-filter shape being modeled using a spectrally symmetric, two-parameter rounded-exponential (roex) function. During data collection using the qAF procedure, listeners detected the presence of a pure-tone signal presented in the spectral notch of a noise masker. Dependent on the listener's response on each trial, the posterior probability distributions of the model parameters were updated, and the resulting parameter estimates were then used to optimize the choice of stimulus parameters for the subsequent trials. Results showed that the qAF procedure gave similar parameter estimates to the traditional threshold-based procedure in many cases and was able to reasonably predict the masked signal thresholds. Additional measurements suggested that occasional failures of the qAF procedure to reliably converge could be a consequence of incorrect responses early in a qAF track. The addition of a parameter describing lapses of attention reduced the likelihood of such failures.

  1. Development and applications of an interactive digital filter design program.

    PubMed

    Woo, H W; Kim, Y M; Tompkins, W J

    1985-10-01

    We have implemented an interactive digital filter design program in the HP 1000 computer at the Department of Electrical Engineering of the University of Washington. This program allows users to design different types of filters interactively with both amplitude and phase responses displayed on graphic devices. The performance of each designed filter can be evaluated conveniently before the best one is chosen and implemented for any particular application. This program can design recursive filters, e.g. Butterworth, Chebyshev and elliptic, or nonrecursive filters with one out of six different windows, i.e. rectangular, triangular, Hann, Hamming, Blackman and Kaiser. The main outputs from this program are coefficients of a transfer function of an analog filter, a digital filter, or both. Therefore, the design of both analog and digital filters is facilitated by using this program. The program is very simple to use and does not require background in analog or digital filter principles in order to run it. The program is written in standard FORTRAN and is about 30 kbytes in size excluding the graphics display routines. Since it uses standard FORTRAN, it can be easily transported to minicomputer and microcomputer systems that have a FORTRAN compiler and minimal graphics capabilities. This program is available for distribution to interested institutions and laboratories.

  2. BLOCK-FLOATING-POINT REALIZATION OF DIGITAL FILTERS

    DTIC Science & Technology

    A realization for digital filters using block- floating - point arithmetic is proposed. A statistical model for roundoff noise is presented and used to compare block- floating - point with fixed-point and floating - point realizations.

  3. Digital high-pass filter deconvolution by means of an infinite impulse response filter

    NASA Astrophysics Data System (ADS)

    Födisch, P.; Wohsmann, J.; Lange, B.; Schönherr, J.; Enghardt, W.; Kaever, P.

    2016-09-01

    In the application of semiconductor detectors, the charge-sensitive amplifier is widely used in front-end electronics. The output signal is shaped by a typical exponential decay. Depending on the feedback network, this type of front-end electronics suffers from the ballistic deficit problem, or an increased rate of pulse pile-ups. Moreover, spectroscopy applications require a correction of the pulse-height, while a shortened pulse-width is desirable for high-throughput applications. For both objectives, digital deconvolution of the exponential decay is convenient. With a general method and the signals of our custom charge-sensitive amplifier for cadmium zinc telluride detectors, we show how the transfer function of an amplifier is adapted to an infinite impulse response (IIR) filter. This paper investigates different design methods for an IIR filter in the discrete-time domain and verifies the obtained filter coefficients with respect to the equivalent continuous-time frequency response. Finally, the exponential decay is shaped to a step-like output signal that is exploited by a forward-looking pulse processing.

  4. Image texture classification with digital filter banks and transforms

    NASA Astrophysics Data System (ADS)

    Husoy, John H.; Randen, Trygve; Gulsrud, Thor O.

    1993-10-01

    Several frequency domain or joint spatial/frequency domain techniques for image texture classification have been published. We formulate these techniques within a common signal processing framework based on digital filter banks. The usefulness of computationally efficient IIR filter banks as channel filters in texture classifiers is demonstrated. Using estimates of local energy in the frequency channels we also propose a technique for selecting optimum filter banks by maximizing a between class distance measure. This optimization is particularly simple when using the IIR based filter banks.

  5. A study of digital holographic filter generation

    NASA Technical Reports Server (NTRS)

    Calhoun, M.; Ingels, F.

    1976-01-01

    Problems associated with digital computer generation of holograms are discussed along with a criteria for producing optimum digital holograms. This criteria revolves around amplitude resolution and spatial frequency limitations induced by the computer and plotter process.

  6. 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.

  7. 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.

  8. 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.

  9. Digital adaptive control laws for VTOL aircraft

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.

    1979-01-01

    Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.

  10. Design of suboptimal adaptive filter for stochastic systems

    NASA Astrophysics Data System (ADS)

    Ahn, Jun Il; Shin, Vladimir

    2005-12-01

    In this paper, the problem of estimating the system state in for linear discrete-time systems with uncertainties is considered. In [1], [2], we have proposed the fusion formula (FF) for an arbitrary number of correlated and uncorrelated estimates. The FF is applied to detection and filtering problem. The new suboptimal adaptive filter with parallel structure is herein proposed. In consequence of parallel structure of the proposed filter, parallel computers can be used for their design. A lower computational complexity and lower memory demand are achieved with the proposed filter than in the optimal adaptive Lainiotis-Kalman filter. Example demonstrates the accuracy of the new filter.

  11. Performance analysis of digital integrate-and-dump filters

    NASA Technical Reports Server (NTRS)

    Chie, C. M.

    1982-01-01

    Key design parameters associated with the operation of a digital integrate-and-dump filter are identified in this paper. Performance degradation effects associated with the selection of these parameters such as analog-to-digital converter (ADC) gain loading factor, number of bits used, predetection bandwidth, sampling rate, and accumulator length are considered. Numerical results of practical interest are also provided.

  12. [Evaluation of an adaptive filter for CT under low-CNR condition: comparison with linear filter].

    PubMed

    Mori, Issei; Uchida, Miho; Sato, Ami; Sato, Shingo; Tamura, Hajime; Takai, Yoshihiro; Ishibashi, Tadashi; Saito, Haruo; Hosokai, Yoshiyuki; Ogura, Takahide; Chida, Koichi; Machida, Yoshio

    2009-01-20

    The use of an adaptive filter for CT images is becoming a common procedure and is said to reduce image noise while preserving sharpness and helping to reduce the required X-ray dose. Although many reports support this view, the validity of such evaluations is arguable. When the linearity of a system is in question, physical performance indexes should be measured under conditions similar to those of clinical use. Evaluations of diagnosis using clinical images may be fallible because the non-filtered image used as the reference might not have been optimally reconstructed. We have chosen simple, but commonly used, adaptive filters for our evaluation. As a reference for comparing performance, we designed linear filters that best approximate the noise characteristics of the adaptive filters. MTF is measured through observation of the edge-spread function. Clinical abdominal images are used to compare the performance of adaptive filters and linear filters. We conclude that the performance of the type of adaptive filter we have chosen is virtually the same as that of the linear filter, as long as the image quality of soft tissues is our interest. Both the noise SD and MTF are virtually the same if the contrast of the object is not substantially higher than 150 HU. Images of soft tissues obtained with the use of adaptive filters are also virtually the same as those obtained by linear filters. The edge-preservation characteristic of this adaptive filter is not observable for soft tissues.

  13. Low Power Adder Based Digital Filter for QRS Detector

    PubMed Central

    Murali, L.; Chitra, D.; Manigandan, T.

    2014-01-01

    Most of the Biomedical applications use dedicated processors for the implementation of complex signal processing. Among them, sensor network is also a type, which has the constraint of low power consumption. Since the processing elements are the most copiously used operations in the signal processors, the power consumption of this has the major impact on the system level application. In this paper, we introduce low power concept of transistor stacking to reduce leakage power; and new architectures based on stacking to implement the full adder and its significance at the digital filter level for QRS detector are implemented. The proposed concept has lesser leakage power at the adder as well as filter level with trade-off in other quality metrics of the design. This enabled the design to be dealt with as the low-power corner and can be made adaptable to any level of hierarchical abstractions as per the requirement of the application. The proposed architectures are designed, modeled at RTL level using the Verilog-HDL, and synthesized in Synopsys Design Compiler by mapping the design to 65 nm technology library standard cells. PMID:24895649

  14. Low power adder based digital filter for QRS detector.

    PubMed

    Murali, L; Chitra, D; Manigandan, T

    2014-01-01

    Most of the Biomedical applications use dedicated processors for the implementation of complex signal processing. Among them, sensor network is also a type, which has the constraint of low power consumption. Since the processing elements are the most copiously used operations in the signal processors, the power consumption of this has the major impact on the system level application. In this paper, we introduce low power concept of transistor stacking to reduce leakage power; and new architectures based on stacking to implement the full adder and its significance at the digital filter level for QRS detector are implemented. The proposed concept has lesser leakage power at the adder as well as filter level with trade-off in other quality metrics of the design. This enabled the design to be dealt with as the low-power corner and can be made adaptable to any level of hierarchical abstractions as per the requirement of the application. The proposed architectures are designed, modeled at RTL level using the Verilog-HDL, and synthesized in Synopsys Design Compiler by mapping the design to 65 nm technology library standard cells.

  15. Simplification of digital filtering algorithms using multirate concepts (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Mitra, Sanjit K.

    1992-02-01

    The polyphase decomposition of a sequence is a useful tool in multirate signal processing such as in the design of computationally efficient decimators and interpolators, the design of analysis/synthesis filter banks, and the development of fast discrete transform algorithms. This paper reviews a recently introduced generalization of the polyphase decomposition concept and outlines some of its applications in the simplification of digital filtering algorithms such as the design and implementation of finite-impulse-response (FIR) digital filters, the design of decimators and interpolators, and discrete Fourier transform computations.

  16. FIR digital filter-based ZCDPLL for carrier recovery

    NASA Astrophysics Data System (ADS)

    Nasir, Qassim

    2016-04-01

    The objective of this work is to analyse the performance of the newly proposed two-tap FIR digital filter-based first-order zero-crossing digital phase-locked loop (ZCDPLL) in the absence or presence of additive white Gaussian noise (AWGN). The introduction of the two-tap FIR digital filter widens the lock range of a ZCDPLL and improves the loop's operation in the presence of AWGN. The FIR digital filter tap coefficients affect the loop convergence behaviour and appropriate selection of those gains should be taken into consideration. The new proposed loop has wider locking range and faster acquisition time and reduces the phase error variations in the presence of noise.

  17. Adaptive filter design using recurrent cerebellar model articulation controller.

    PubMed

    Lin, Chih-Min; Chen, Li-Yang; Yeung, Daniel S

    2010-07-01

    A novel adaptive filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so the stability of the filtering error can be guaranteed. To demonstrate the performance of the proposed adaptive RCMAC filter, it is applied to a nonlinear channel equalization system and an adaptive noise cancelation system. The advantages of the proposed filter over other adaptive filters are verified through simulations.

  18. Adapting Digital Libraries to Continual Evolution

    NASA Technical Reports Server (NTRS)

    Barkstrom, Bruce R.; Finch, Melinda; Ferebee, Michelle; Mackey, Calvin

    2002-01-01

    In this paper, we describe five investment streams (data storage infrastructure, knowledge management, data production control, data transport and security, and personnel skill mix) that need to be balanced against short-term operating demands in order to maximize the probability of long-term viability of a digital library. Because of the rapid pace of information technology change, a digital library cannot be a static institution. Rather, it has to become a flexible organization adapted to continuous evolution of its infrastructure.

  19. An adaptive filter for smoothing noisy radar images

    NASA Technical Reports Server (NTRS)

    Frost, V. S.; Stiles, J. A.; Shanmugam, K. S.; Holtzman, J. C.; Smith, S. A.

    1981-01-01

    A spatial domain adaptive Wiener filter for smoothing radar images corrupted by multiplicative noise is presented. The filter is optimum in a minimum mean squared error sense, computationally efficient, and preserves edges in the image better than other filters. The proposed algorithm can also be used for processing optical images with illumination variations that have a multiplicative effect.

  20. Adjustment of adaptive sum comb filter for PPG signals.

    PubMed

    Pilt, Kristjan; Meigas, Kalju; Ferenets, Rain; Kaik, Juri

    2009-01-01

    AC component of photoplethysmography signal carries important information for diagnostics. Registered signal may be affected by noises, which are sharing the same bandwidth. Adaptive comb filter is used for the AC component extraction. Due to filter averaging behavior it decreases the signal shape difference between consecutive beats. Comb filter needs to be adjusted for PPG signal. Comb filter new weight values are determined through numerical computation. Experiments with generated photoplethysmographic signals were carried out to compare adjusted and non-adjusted adaptive sum comb filter.

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

    PubMed

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

    2014-09-19

    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.

  2. 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.

  3. Comparison between digital Doppler filtering processes applied to radar signals

    NASA Astrophysics Data System (ADS)

    Desodt, G.

    1983-10-01

    Two families of Doppler processes based on FFT and FIR filters, respectively, are compared in terms of hardware complexity and performance. It is shown that FIR filter banks are characterized by better performance than FFT filter banks. For the same number of pulses, the FIR processor permits a better clutter rejection and greater bandwidth than the FFT one. Also, an FIR-based bank has a much simpler and more adaptable architecture than an FFT-based bank.

  4. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Ormsby, John (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing (DSP) functions. Such capability also makes and FPGA a suitable platform for the digital implementation of closed loop controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance in a compact form-factor. Other researchers have presented the notion that a second order digital filter with proportional-integral-derivative (PID) control functionality can be implemented in an FPGA. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSF) devices. Our goal is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. Meeting our goals requires alternative compact implementation of such functionality to withstand the harsh environment encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching these goals.

  5. Adaptive Filtering in the Wavelet Transform Domain via Genetic Algorithms

    DTIC Science & Technology

    2004-08-06

    identification. Figure 1 shows a very basic example of this type of system . x(n) Figure 1. Basic system identification using adaptive filters block diagram...block diagram of adaptive wavelet filtering system . The main objective of the system shown in Figure 2 is to minimize the error signal, e(k), which is...in Table 1. Daub4 wavelets use filter banks (Vaidyanathan 1992) containing exactly four elements. 5 Figure 4. Time-Domain Representation of

  6. Progress in adaptive control of flexible spacecraft using lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Montgomery, R. C.

    1985-01-01

    This paper reviews the use of the least square lattice filter in adaptive control systems. Lattice filters have been used primarily in speech and signal processing, but they have utility in adaptive control because of their order-recursive nature. They are especially useful in dealing with structural dynamics systems wherein the order of a controller required to damp a vibration is variable depending on the number of modes significantly excited. Applications are presented for adaptive control of a flexible beam. Also, difficulties in the practical implementation of the lattice filter in adaptive control are discussed.

  7. New demodulation filter in digital phase rotation beamforming.

    PubMed

    Schneider, Fabio Kurt; Yoo, Yang Mo; Agarwal, Anup; Koh, Liang Mong; Kim, Yongmin

    2006-07-01

    In this paper, we present a new quadrature demodulation filter to reduce hardware complexity in digital phase rotation beamforming. Due to its low sensitivity to phase delay errors, digital quadrature demodulation is commonly used in ultrasound machines. However, since it requires two lowpass filters for each channel to remove harmonics, the direct use of conventional finite impulse response (FIR) filters in ultrasound machines is computationally expensive and burdensome. In our new method, an efficient multi-stage uniform coefficient (MSUC) filter is utilized to remove harmonic components in phase rotation beamforming. In comparison with the directly implemented FIR (DI-FIR) and the previously-proposed signed-power-of-two FIR (SPOT-FIR) lowpass filters, the proposed MSUC filter reduces the necessary hardware resources by 93.9% and 83.9%, respectively. In simulation, the MSUC filter shows a negligible degradation in image quality. The proposed method resulted in comparable spatial and contrast resolution to the DI-FIR approach in the phantom study. These preliminary results indicate that the proposed quadrature demodulation filtering method could significantly reduce the hardware complexity in phase rotation beamforming while maintaining comparable image quality.

  8. Investigation of Adaptive Robust Kalman Filtering Algorithms for GPS/DR Navigation System Filters

    NASA Astrophysics Data System (ADS)

    Elzoghby, MOSTAFA; Arif, USMAN; Li, FU; Zhi Yu, XI

    2017-03-01

    The conventional Kalman filter (KF) algorithm is suitable if the characteristic noise covariance for states as well as measurements is readily known but in most cases these are unknown. Similarly robustness is required instead of smoothing if states are changing abruptly. Such an adaptive as well as robust Kalman filter is vital for many real time applications, like target tracking and navigating aerial vehicles. A number of adaptive as well as robust Kalman filtering methods are available in the literature. In order to investigate the performance of some of these methods, we have selected three different Kalman filters, namely Sage Husa KF, Modified Adaptive Robust KF and Adaptively Robust KF, which are easily simulate able as well as implementable for real time applications. These methods are simulated for land based vehicle and the results are compared with conventional Kalman filter. Results show that the Modified Adaptive Robust KF is best amongst the selected methods and can be used for Navigation applications.

  9. Digital item adaptation for color vision variations

    NASA Astrophysics Data System (ADS)

    Song, Jaeil; Yang, Seungji; Kim, Cheonseog; Nam, Jaeho; Hong, Jin-Woo; Ro, Yong Man

    2003-06-01

    As color is more widely used to carry visual information in the multimedia content, ability to perceive color plays a crucial role in getting visual information. Regardless of color vision variations, one should have visual information equally. This paper proposes the adaptation technique for color vision variations in the MPEG-21 Digital Item Adaptation (DIA). DIA is performed respectively for severe color vision deficiency (dichromats) and for mild color vision deficiency (anomalous trichromats), according to the description of user characteristics about color vision variations. Adapted images are tested by simulation program for color vision variations so as to recognize the appearance of the adapted images in the color deficient vision. Experimental result shows that proposed adaptation technique works well in the MPEG-21 framework.

  10. Optimal multiobjective design of digital filters using spiral optimization technique.

    PubMed

    Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid

    2013-01-01

    The multiobjective design of digital filters using spiral optimization technique is considered in this paper. This new optimization tool is a metaheuristic technique inspired by the dynamics of spirals. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the spiral optimization technique produced filters which fulfill the desired characteristics and are of practical use.

  11. Optimal Multiobjective Design of Digital Filters Using Taguchi Optimization Technique

    NASA Astrophysics Data System (ADS)

    Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid

    2014-01-01

    The multiobjective design of digital filters using the powerful Taguchi optimization technique is considered in this paper. This relatively new optimization tool has been recently introduced to the field of engineering and is based on orthogonal arrays. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the Taguchi optimization technique produced filters that fulfill the desired characteristics and are of practical use.

  12. 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).

  13. Improved digital filters for evaluating Fourier and Hankel transform integrals

    USGS Publications Warehouse

    Anderson, Walter L.

    1975-01-01

    New algorithms are described for evaluating Fourier (cosine, sine) and Hankel (J0,J1) transform integrals by means of digital filters. The filters have been designed with extended lengths so that a variable convolution operation can be applied to a large class of integral transforms having the same system transfer function. A f' lagged-convolution method is also presented to significantly decrease the computation time when computing a series of like-transforms over a parameter set spaced the same as the filters. Accuracy of the new filters is comparable to Gaussian integration, provided moderate parameter ranges and well-behaved kernel functions are used. A collection of Fortran IV subprograms is included for both real and complex functions for each filter type. The algorithms have been successfully used in geophysical applications containing a wide variety of integral transforms

  14. Decision-directed entropy-based adaptive filtering

    NASA Astrophysics Data System (ADS)

    Myler, Harley R.; Weeks, Arthur R.; Van Dyke-Lewis, Michelle

    1991-12-01

    A recurring problem in adaptive filtering is selection of control measures for parameter modification. A number of methods reported thus far have used localized order statistics to adaptively adjust filter parameters. The most effective techniques are based on edge detection as a decision mechanism to allow the preservation of edge information while noise is filtered. In general, decision-directed adaptive filters operate on a localized area within an image by using statistics of the area as a discrimination parameter. Typically, adaptive filters are based on pixel to pixel variations within a localized area that are due to either edges or additive noise. In homogeneous areas within the image where variances are due to additive noise, the filter should operate to reduce the noise. Using an edge detection technique, a decision directed adaptive filter can vary the filtering proportional to the amount of edge information detected. We show an approach using an entropy measure on edges to differentiate between variations in the image due to edge information as compared against noise. The method uses entropy calculated against the spatial contour variations of edges in the window.

  15. Digital filter suppresses effects of nonstatistical noise bursts on multichannel scaler digital averaging systems

    NASA Technical Reports Server (NTRS)

    Goodman, L. S.; Salter, F. O.

    1968-01-01

    Digital filter suppresses the effects of nonstatistical noise bursts on data averaged over multichannel scaler. Interposed between the sampled channels and the digital averaging system, it uses binary logic circuitry to compare the number of counts per channel with the average number of counts per channel.

  16. 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.

  17. Digital filtering for data compression in telemetry systems

    SciTech Connect

    Bell, R.M.

    1994-08-01

    There are many obstacles to using data compression in a telemetry system. Non-linear quantization is often too lossy, and the data is too highly structured to make variable-length entropy codes practical. This paper describes a lossless telemetry data compression system that was built using digital FIR filters. The method of compression takes advantage of the fact that the optimal Nyquist sampling rate is rarely achievable due to two factors: (1) Sensor/transducers are not bandlimited to the frequencies of interest, and (2) Accurate, high-order analog filters are not available to perform effective band limiting and prevent aliasing. Real-time digital filtering can enhance the performance of a typical sampling system so that it approaches Nyquist sampling rates, effectively compressing the amount of data and reducing transmission bandwidth. The system that was built reduced the sampling rate of 14 high-frequency vibration channels by a factor of two, and reduced the bandwidth of the-data link from 1.8 Mbps to 1.28 Mbps. The entire circuit uses seven function-specific, digital-filter DSP`s operating in parallel (two 128-tap FIR filters can be implemented on each Motorola DSP56200), one EPROM and a Programmable Logic Device as the controller.

  18. Digitally Controlled ’Programmable’ Active Filters.

    DTIC Science & Technology

    1985-12-01

    Mitra, S. K., Analysis and Synthesis of Linear Active .. Networks, Wiley, New York, 1969. * 6. Sedra , A. S. and Smith , K. C., "A Second-Generation...Current Conveyor and its Applications," IEEE Trans. Circuit Theory, Vol. CT-17, pp. 132-134, 1970. 7. Sedra , A. S., "A New Approach to Active Network...CT-18, pp. 358-361, May 1971. 27. Hamilton, T. A., and Sedra , A. S., "Some New IJ Configurations for Active Filters," IEEE Trans. Circuit Tehory, Vol

  19. An adaptive Kalman filter for ECG signal enhancement.

    PubMed

    Vullings, Rik; de Vries, Bert; Bergmans, Jan W M

    2011-04-01

    The ongoing trend of ECG monitoring techniques to become more ambulatory and less obtrusive generally comes at the expense of decreased signal quality. To enhance this quality, consecutive ECG complexes can be averaged triggered on the heartbeat, exploiting the quasi-periodicity of the ECG. However, this averaging constitutes a tradeoff between improvement of the SNR and loss of clinically relevant physiological signal dynamics. Using a bayesian framework, in this paper, a sequential averaging filter is developed that, in essence, adaptively varies the number of complexes included in the averaging based on the characteristics of the ECG signal. The filter has the form of an adaptive Kalman filter. The adaptive estimation of the process and measurement noise covariances is performed by maximizing the bayesian evidence function of the sequential ECG estimation and by exploiting the spatial correlation between several simultaneously recorded ECG signals, respectively. The noise covariance estimates thus obtained render the filter capable of ascribing more weight to newly arriving data when these data contain morphological variability, and of reducing this weight in cases of no morphological variability. The filter is evaluated by applying it to a variety of ECG signals. To gauge the relevance of the adaptive noise-covariance estimation, the performance of the filter is compared to that of a Kalman filter with fixed, (a posteriori) optimized noise covariance. This comparison demonstrates that, without using a priori knowledge on signal characteristics, the filter with adaptive noise estimation performs similar to the filter with optimized fixed noise covariance, favoring the adaptive filter in cases where no a priori information is available or where signal characteristics are expected to fluctuate.

  20. Digital Filter Design with Harmonics Estimation for Power Supplies

    NASA Astrophysics Data System (ADS)

    Shah, P. J.; Saxena, R.; Chawla, M. P. S.

    2012-06-01

    The quality of voltage waveforms is nowadays an issue of the utmost importance for power utilities and electronic equipment. Modern frequency power converters generate a wide spectrum of harmonic components, which deteriorate the quality of the delivered energy, increase the energy losses as well as decrease their liability of a power supplies. In large converters systems not only harmonics, but also considerable interharmonics strongly deteriorate the quality of the power supply voltage. The estimation of the components parameters is very important for control and protection tasks. Digital low pass filter overcome the voltage drift, temperature drift and time drift problems and can be used for harmonic detection for better utilization in real-time. Real-time detection of harmonics can be implemented using MATLAB software and developing simulation circuit set up. With the appropriate cutoff frequency f c and nth order of filter, low pass filter and band-pass filter for real-time harmonic detection can be analyzed. In this paper the aim is to design filters using different methods including Prony analysis. The monitoring of power system harmonics an important issue in the frame of modern power system management and control can be achieved easily using digital filters.

  1. The cerebellum as an adaptive filter: a general model?

    PubMed

    Dean, Paul; Porrill, John

    2010-01-01

    Many functional models of the cerebellar microcircuit are based on the adaptive-filter model first proposed by Fujita. The adaptive filter has powerful signal processing capacities that are suitable for both sensory and motor tasks, and uses a simple and intuitively plausible decorrelation learning rule that offers and account of the evolution of the inferior olive. Moreover, in those cases where the input-output transformations of cerebellar microzones have been sufficiently characterised, they appear to conform to those predicted by the adaptive-filter model. However, these cases are few in number, and comparing the model with the internal operations of the microcircuit itself has not proved straightforward. Whereas some microcircuit features appear compatible with adaptive-filter function, others such as simple granular-layer processing or Purkinje cell bistability, do not. How far these seeming incompatibilities indicate additional computational roles for the cerebellar microcircuit remains to be determined.

  2. 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.…

  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. Enhanced adaptive loop filter for motion compensated frame.

    PubMed

    Yoo, Young-Joe; Seo, Chan-Won; Han, Jong-Ki; Nguyen, Truong Q

    2011-08-01

    We propose an adaptive loop filter to remove the redundancy between current and motion compensated frames so that the residual signal is minimized, thus coding efficiency increases. The loop filter coefficients and offset are optimized for each frame or a set of blocks to minimize the total energy of the residual signal resulting from motion estimation and compensation. The optimized loop filter with offset is applied for the set of blocks where the filtering process gives coding gain based upon rate-distortion cost. The proposed loop filter is used for the motion compensated frame whereas the conventional adaptive interpolation filter (AIF) is applied to the reference frames to interpolate the subpixel values. Another conventional scheme adaptive loop filter (ALF), is used after deblocking filtering to enhance quality of reconstructed frames, not to minimize energy of residual signal. The proposed loop filter can be used in combination with the AIF and ALF. Experimental results show that proposed algorithm provides the averaged bit reduction of 8% compared to conventional H.264/AVC scheme. When the proposed scheme is combined with AIF and ALF, the coding gain increases even further.

  5. 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…

  6. 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.

  7. 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.

  8. 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.

  9. Optimal Recursive Digital Filters for Active Bending Stabilization

    NASA Technical Reports Server (NTRS)

    Orr, Jeb S.

    2013-01-01

    In the design of flight control systems for large flexible boosters, it is common practice to utilize active feedback control of the first lateral structural bending mode so as to suppress transients and reduce gust loading. Typically, active stabilization or phase stabilization is achieved by carefully shaping the loop transfer function in the frequency domain via the use of compensating filters combined with the frequency response characteristics of the nozzle/actuator system. In this paper we present a new approach for parameterizing and determining optimal low-order recursive linear digital filters so as to satisfy phase shaping constraints for bending and sloshing dynamics while simultaneously maximizing attenuation in other frequency bands of interest, e.g. near higher frequency parasitic structural modes. By parameterizing the filter directly in the z-plane with certain restrictions, the search space of candidate filter designs that satisfy the constraints is restricted to stable, minimum phase recursive low-pass filters with well-conditioned coefficients. Combined with optimal output feedback blending from multiple rate gyros, the present approach enables rapid and robust parametrization of autopilot bending filters to attain flight control performance objectives. Numerical results are presented that illustrate the application of the present technique to the development of rate gyro filters for an exploration-class multi-engined space launch vehicle.

  10. Noise Shaping Filter Compensating PWM Distortion for Fully Digital Amplifier

    NASA Astrophysics Data System (ADS)

    Yoneya, Akihiko

    The full-digital audio amplifiers have several merits such as a high power enabling a small size of the amplifier and digital implementation of the signal processing which allows desired precision of the processing except for the final stage switching amplifiers. Unfortunately, the pulse width modulation (PWM) causes signal distortions because of the non-linearity of the modulation from the viewpoint of the transient response. This paper proposes a compensation method of the PWM distortion with feedback approach. In the noise-shaping filter of the delta-sigma modulator to calculate the pulse codes for the PWM, the distortion caused by the PWM is evaluated and fed it back to compensate the distortion. Eventually the filter is implemented as a state-variable filter with non-linear feedback from the quantizer. The calculation of the filter elements is also described. By using proposed filters, PWM signals with small distortions and small floor noise can be obtained to realize high-fidelity audio amplifiers.

  11. 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.

  12. Fast HDR image upscaling using locally adapted linear filters

    NASA Astrophysics Data System (ADS)

    Talebi, Hossein; Su, Guan-Ming; Yin, Peng

    2015-02-01

    A new method for upscaling high dynamic range (HDR) images is introduced in this paper. Overshooting artifact is the common problem when using linear filters such as bicubic interpolation. This problem is visually more noticeable while working on HDR images where there exist more transitions from dark to bright. Our proposed method is capable of handling these artifacts by computing a simple gradient map which enables the filter to be locally adapted to the image content. This adaptation consists of first, clustering pixels into regions with similar edge structures and second, learning the shape and length of our symmetric linear filter for each of these pixel groups. This new filter can be implemented in a separable fashion which perfectly fits hardware implementations. Our experimental results show that training our filter with HDR images can effectively reduce the overshooting artifacts and improve upon the visual quality of the existing linear upscaling approaches.

  13. A digital filtering scheme for SQUID based magnetocardiography

    NASA Astrophysics Data System (ADS)

    Zhu, Xue-Min; Ren, Yu-Feng; Yu, Hong-Wei; Zhao, Shi-Ping; Chen, Geng-Hua; Zhang, Li-Hua; Yang, Qian-Sheng

    2006-01-01

    Considering the properties of slow change and quasi-periodicity of magnetocardiography (MCG) signal, we use an integrated technique of adaptive and low-pass filtering in dealing with two-channel MCG data measured by high Tc SQUIDs. The adaptive filter in the time domain is based on a noise feedback normalized least-mean-square (NLMS) algorithm and the low-pass filter with a cutoff at 100Hz in the frequency domain characterized by Gaussian functions is combined with a notch at the power line frequency. In this way, both relevant and irrelevant noises in original MCG data are largely eliminated. The method may also be useful for other slowly varying quasi-periodical signals.

  14. 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.

  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. 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.

  17. Modifying real convolutional codes for protecting digital filtering systems

    NASA Technical Reports Server (NTRS)

    Redinbo, G. R.; Zagar, Bernhard

    1993-01-01

    A novel method is proposed for protecting digital filters from temporary and permanent failures that are not easily detected by conventional fault-tolerant computer design principles, on the basis of the error-detecting properties of real convolutional codes. Erroneous behavior is detected by externally comparing the calculated and regenerated parity samples. Great simplifications are obtainable by modifying the code structure to yield simplified parity channels with finite impulse response structures. A matrix equation involving the original parity values of the code and the polynomial of the digital filter's transfer function is formed, and row manipulations separate this equation into a set of homogeneous equations constraining the modifying scaling coefficients and another set which defines the code parity values' implementation.

  18. Image fusion using DFT-based digital filter banks

    NASA Astrophysics Data System (ADS)

    Sezgin, Murat; Erer, Isin; Ersoy, Okan K.

    2005-08-01

    In this paper, we present a new fusion algorithm based on a multidecomposition approach with the DFT based symmetric, zero-phase, nonoverlapping digital filter bank representation. The DFT of the signal is separated into two parts leading to the low and high -pass components then decimated by two to obtain subband signals. The original signal may be recovered by interpolating the subband signals, computing their inverse DFT and summing the results. In the proposed image fusion algorithm, two or more source images are decomposed into subbands by DFT based digital filters. The detail and approximation subband coefficients are modified according to their magnitudes and mean values, respectively. Then, the modified subbands are combined in the subband domain. Finally, the fused image is obtained by the inverse transform.

  19. Design of adaptive filter amplifier in UV communication based on DSP

    NASA Astrophysics Data System (ADS)

    Lv, Zhaoshun; Wu, Hanping; Li, Junyu

    2016-10-01

    According to the problem of the weak signal at receiving end in UV communication, we design a high gain, continuously adjustable adaptive filter amplifier. Based on proposing overall technical indicators and analyzing its working principle of the signal amplifier, we use chip LMH6629MF and two chips of AD797BN to achieve three-level cascade amplification. And apply hardware of DSP TMS320VC5509A to implement digital filtering. Design and verification by Multisim, Protel 99SE and CCS, the results show that: the amplifier can realize continuously adjustable amplification from 1000 to 10000 times without distortion. Magnification error is <=%4@1000 10000. And equivalent input noise voltage of amplification circuit is <=6 nV/ √Hz @30KHz 45KHz, and realizing function of adaptive filtering. The design provides theoretical reference and technical support for the UV weak signal processing.

  20. Adaptive comb filtering for motion artifact reduction from PPG with a structure of adaptive lattice IIR notch filter.

    PubMed

    Lee, Boreom; Kee, Youngwook; Han, Jonghee; Yi, Won Jin

    2011-01-01

    Photoplethysmographic (PPG) signal can provide important information about cardiovascular and respiratory conditions of individuals in a hospital or daily life. However, PPG can be distorted by motion artifacts significantly. Therefore, the reduction of the effects of motion artifacts is very important procedure for monitoring cardio-respiratory system by PPG. There have been many adaptive techniques to reduce motion artifacts from PPG signal including normalized least mean squares (NLMS) method, recursive least squares (RLS) filter, and Kalman filter. In the present study, we propose the adaptive comb filter (ACF) for reducing the effects of motion artifacts from PPG signal. ACF with adaptive lattice infinite impulse response (IIR) notch filter (ALNF) successfully reduced the motion artifacts from the quasi-periodic PPG signal.

  1. Convergence Analysis of LMS based Adaptive filter

    NASA Astrophysics Data System (ADS)

    Rai, Amrita; Kohli, Amit Kumar

    2010-11-01

    A standard algorithm for LMS-filter simulation, tested with several convergence criteria is presented in this paper. We analyze the steady-state mean square error (MSE) convergence of the LMS algorithm when random functions are used as reference inputs. In this paper, we make a more precise analysis using the deterministic nature of the reference inputs and their time-variant correlation matrix. Simulations performed under MATLAB show remarkable differences between convergence criteria with various value of the step size.

  2. The influence of software filtering in digital mammography image quality

    NASA Astrophysics Data System (ADS)

    Michail, C.; Spyropoulou, V.; Kalyvas, N.; Valais, I.; Dimitropoulos, N.; Fountos, G.; Kandarakis, I.; Panayiotakis, G.

    2009-05-01

    Breast cancer is one of the most frequently diagnosed cancers among women. Several techniques have been developed to help in the early detection of breast cancer such as conventional and digital x-ray mammography, positron and single-photon emission mammography, etc. A key advantage in digital mammography is that images can be manipulated as simple computer image files. Thus non-dedicated commercially available image manipulation software can be employed to process and store the images. The image processing tools of the Photoshop (CS 2) software usually incorporate digital filters which may be used to reduce image noise, enhance contrast and increase spatial resolution. However, improving an image quality parameter may result in degradation of another. The aim of this work was to investigate the influence of three sharpening filters, named hereafter sharpen, sharpen more and sharpen edges on image resolution and noise. Image resolution was assessed by means of the Modulation Transfer Function (MTF).In conclusion it was found that the correct use of commercial non-dedicated software on digital mammograms may improve some aspects of image quality.

  3. 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.

  4. 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.

  5. 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

  6. Numerical filtering techniques for the reduction of noise in digital telemetry data

    NASA Astrophysics Data System (ADS)

    Helfrich-Stone, Thomas M.

    Telemetry data noise is due to the marginal or complete loss of telemetry carrier signal, leading to errors in the PCM data received. Attention is presently given to several postflight numerical filtering techniques for the reduction and/or removal of noise in digital telemetry data, prior to use in automated computer data analysis. The techniques encompass manual filtering, upper/lower bound filtering, mean-plus/minus standard deviation filtering, rate-of-change filtering, multiple-measurement filtering, and multiple filters.

  7. 3-D adaptive nonlinear complex-diffusion despeckling filter.

    PubMed

    Rodrigues, Pedro; Bernardes, Rui

    2012-12-01

    This work aims to improve the process of speckle noise reduction while preserving edges and other relevant features through filter expansion from 2-D to 3-D. Despeckling is very important for data visual inspection and as a preprocessing step for other algorithms, as they are usually notably influenced by speckle noise. To that intent, a 3-D approach is proposed for the adaptive complex-diffusion filter. This 3-D iterative filter was applied to spectral-domain optical coherence tomography medical imaging volumes of the human retina and a quantitative evaluation of the results was performed to allow a demonstration of the better performance of the 3-D over the 2-D filtering and to choose the best total diffusion time. In addition, we propose a fast graphical processing unit parallel implementation so that the filter can be used in a clinical setting.

  8. A reduced bias delay lock loop for adaptive filters

    NASA Astrophysics Data System (ADS)

    Fan, Guangteng; Huang, Yangbo; Su, Yingxue; Li, Jingyuan; Sun, Guangfu

    2017-01-01

    Narrowband interferences (NBIs) severely degrade the quality of a received signal and can hinder the operation of GPS receivers, and therefore, they are commonly excised using an adaptive transversal filter. This filter does not cause code tracking bias in the case of an ideal analog receiver channel when its magnitude and phase response are constant; however, distortion is induced by RF cables, amplifiers, and mixers that results in an asymmetric correlation function. This correlation function is further deformed by the adaptive transversal filter, resulting in a nonzero bias. Given the adaptive nature of this transversal filter, the bias varies based on the jamming pattern. For precision navigation applications, this bias must be mitigated. With this problem in mind, a new technique called amplitude estimating delay lock loop (AEDLL) is presented. By using data related to a known structure of the adaptive transversal filter, the proposed method only needs to estimate the amplitude of the correlation function and revise the correlation function for code tracking. Simulations show that the AEDLL method is capable of reducing the RMSE of code tracking bias to less than 0.12 ns, which is significantly smaller than that achieved using existing methods.

  9. The effect of filtering and inter-digit interval on the recognition of dichotic digits.

    PubMed

    Carter, A S; Wilson, R H

    2000-01-01

    The new compact disc from the Department of Veterans Affairs, Tonal and Speech Materials for Auditory, Perceptual Assessment, Disc 2.0 (1998), contains two lists of randomly interleaved 1-, 2-, and 3-pair dichotic digits. Two experiments are reported, in which the effects of low-pass filtering and inter-digit interval on dichotic digit recognition were investigated in adult listeners with normal hearing and with mild-to-moderate cochlear hearing loss. Results demonstrated that in the filtered condition, as the low-pass cutoff was increased, there was an increase in recognition performance for 1-, 2-, and 3-pair dichotic digits. When compared to normative data for the materials, findings indicate that the interleaved 1-, 2-, and 3-pair dichotic digit materials were essentially resistant to the effects of hearing loss. There was no significant change in recognition performance as a function of inter-digit interval. The studied 625-ms range of inter-digit intervals studied produced consistent recognition performance with both groups of listeners.

  10. The design of digital filters for biomedical signal processing. Part 3: The design of Butterworth and Chebychev filters.

    PubMed

    Challis, R E; Kitney, R I

    1983-04-01

    The first two papers in this series reviewed the basic concepts which apply to digital filter theory and presented design techniques based on the z plane pole-zero plot. In this paper these methods are used to develop digital versions of Butterworth and Chebychev filters. The basic theory of both filter types is reviewed and the bilinear transformation is used to derive the z-transforms of the filters from their s-plane continuous time descriptions. Recurrence relationships which may be used to implement filters of various orders are developed. The impulse and frequency responses of the elements are illustrated and examples are given of their application to ECG data.

  11. 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.

  12. An Adaptive Kalman Filter Excisor for Suppressing Narrowband Interference

    DTIC Science & Technology

    1993-11-01

    interferences in- connues. Le filtre de Kalman doit alors "apprendre" ý ajuster un de ses param~tres pour effectuer le meilleur traitement. L’erreur est...4"L l B"• -- -- - - -.- ,_, . An~. A)7cQ 0 -QGOP II liii 111111 IIa( Naional 06fenso I ’ I Deence nitonals I "It AN ADAPTIVE KALMAN FILTER EXCISOR...Ottawa 0 A o~ oO Best Available COpy 4INational Defense Defence nationals AN ADAPTIVE KALMAN FILTER EXCISOR FOR SUPPRESSING NARROWBAND INTERFERENCE by

  13. 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.

  14. An adaptive neural fuzzy filter and its applications.

    PubMed

    Lin, C T; Juang, C F

    1997-01-01

    A new kind of nonlinear adaptive filter, the adaptive neural fuzzy filter (ANFF), based upon a neural network's learning ability and fuzzy if-then rule structure, is proposed in this paper. The ANFF is inherently a feedforward multilayered connectionist network which can learn by itself according to numerical training data or expert knowledge represented by fuzzy if-then rules. The adaptation here includes the construction of fuzzy if-then rules (structure learning), and the tuning of the free parameters of membership functions (parameter learning). In the structure learning phase, fuzzy rules are found based on the matching of input-output clusters. In the parameter learning phase, a backpropagation-like adaptation algorithm is developed to minimize the output error. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially, and both the structure learning and parameter learning are performed concurrently as the adaptation proceeds. However, if some linguistic information about the design of the filter is available, such knowledge can be put into the ANFF to form an initial structure with hidden nodes. Two major advantages of the ANFF can thus be seen: 1) a priori knowledge can be incorporated into the ANFF which makes the fusion of numerical data and linguistic information in the filter possible; and 2) no predetermination, like the number of hidden nodes, must be given, since the ANFF can find its optimal structure and parameters automatically.

  15. Optimization of an adaptive nonlinear filter for the analysis of nystagmus.

    PubMed

    Engelken, E J; Stevens, K W; Enderle, J D

    1991-01-01

    An adaptive nonlinear digital filter has been designed for the analysis of an eye-movement signal called nystagmus. Nystagmus is a bi-phasic signal consisting of a sequence of tracking eye movements called "slow-phase" interspersed with brief, high-velocity refixation movements called "fast-phase." The objective of the analysis is to separate the nystagmus signal into its fast- and slow-phase components. Specifically, the goal is to produce an evenly sampled estimate of slow-phase velocity (SPV) and an estimate of the peak fast-phase velocity. Classically this has been done using pattern recognition methods that exploit the fact that the fast-phase is a relatively short duration, high-velocity movement compared to the slow-phase. Unfortunately, these velocity and duration differences do not reliably separate the slow- and fast-phases under all conditions, especially when the signal is noisy. We have designed and built an adaptive nonlinear digital filter that easily outperforms the more complex pattern recognition algorithms. This new filter, called an Adaptive Asymmetrically Trimmed-Mean (AATM) filter, works under the assumption that, on the average, the eyes spend more time in slow-phase than in fast-phase. Thus, in any given data segment, most of the data samples are slow-phase samples. By analyzing the amplitude distribution of the data samples in the segment we can determine which of these samples are slow-phase. We used computer generated nystagmus signals contaminated with 3 levels of noise to evaluate the filter. The filter parameters were then optimized using Monte Carlo procedures producing an extremely robust analysis method.

  16. Adaptive conductance filtering for spatially varying noise in PET images

    NASA Astrophysics Data System (ADS)

    Padfield, Dirk R.; Manjeshwar, Ravindra

    2006-03-01

    PET images that have been reconstructed with unregularized algorithms are commonly smoothed with linear Gaussian filters to control noise. Since these filters are spatially invariant, they degrade feature contrast in the image, compromising lesion detectability. Edge-preserving smoothing filters can differentially preserve edges and features while smoothing noise. These filters assume spatially uniform noise models. However, the noise in PET images is spatially variant, approximately following a Poisson behavior. Therefore, different regions of a PET image need smoothing by different amounts. In this work, we introduce an adaptive filter, based on anisotropic diffusion, designed specifically to overcome this problem. In this algorithm, the diffusion is varied according to a local estimate of the noise using either the local median or the grayscale image opening to weight the conductance parameter. The algorithm is thus tailored to the task of smoothing PET images, or any image with Poisson-like noise characteristics, by adapting itself to varying noise while preserving significant features in the image. This filter was compared with Gaussian smoothing and a representative anisotropic diffusion method using three quantitative task-relevant metrics calculated on simulated PET images with lesions in the lung and liver. The contrast gain and noise ratio metrics were used to measure the ability to do accurate quantitation; the Channelized Hotelling Observer lesion detectability index was used to quantify lesion detectability. The adaptive filter improved the signal-to-noise ratio by more than 45% and lesion detectability by more than 55% over the Gaussian filter while producing "natural" looking images and consistent image quality across different anatomical regions.

  17. Reversible wavelet filter banks with side informationless spatially adaptive low-pass filters

    NASA Astrophysics Data System (ADS)

    Abhayaratne, Charith

    2011-07-01

    Wavelet transforms that have an adaptive low-pass filter are useful in applications that require the signal singularities, sharp transitions, and image edges to be left intact in the low-pass signal. In scalable image coding, the spatial resolution scalability is achieved by reconstructing the low-pass signal subband, which corresponds to the desired resolution level, and discarding other high-frequency wavelet subbands. In such applications, it is vital to have low-pass subbands that are not affected by smoothing artifacts associated with low-pass filtering. We present the mathematical framework for achieving 1-D wavelet transforms that have a spatially adaptive low-pass filter (SALP) using the prediction-first lifting scheme. The adaptivity decisions are computed using the wavelet coefficients, and no bookkeeping is required for the perfect reconstruction. Then, 2-D wavelet transforms that have a spatially adaptive low-pass filter are designed by extending the 1-D SALP framework. Because the 2-D polyphase decompositions are used in this case, the 2-D adaptivity decisions are made nonseparable as opposed to the separable 2-D realization using 1-D transforms. We present examples using the 2-D 5/3 wavelet transform and their lossless image coding and scalable decoding performances in terms of quality and resolution scalability. The proposed 2-D-SALP scheme results in better performance compared to the existing adaptive update lifting schemes.

  18. Properties of digital 1/3-octave filters implemented according to ANSI S1.11

    NASA Astrophysics Data System (ADS)

    Geras, Antonina; Starecki, Tomasz

    The paper presents results of investigation into properties of digital filters implemented in compliance with ANSI S1.11 Standard: Octave-Band and Fractional-Octave Band Analog and Digital Filters. The discussed solutions are digital one-third-octave IIR filters with Direct Form I topology. Performed simulations showed that the filters exhibit strong problems with stability, especially in the case of low center frequency filters. Another problem clearly visible in all investigated structures was poor attenuation at the frequencies above the passband. Although the filters were implemented according to the ANSI standard, none of them met all of the requirements of the standard.

  19. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    PubMed

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance.

  20. 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...

  1. Robust visual tracking via adaptive kernelized correlation filter

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Wang, Desheng; Liao, Qingmin

    2016-10-01

    Correlation filter based trackers have proved to be very efficient and robust in object tracking with a notable performance competitive with state-of-art trackers. In this paper, we propose a novel object tracking method named Adaptive Kernelized Correlation Filter (AKCF) via incorporating Kernelized Correlation Filter (KCF) with Structured Output Support Vector Machines (SOSVM) learning method in a collaborative and adaptive way, which can effectively handle severe object appearance changes with low computational cost. AKCF works by dynamically adjusting the learning rate of KCF and reversely verifies the intermediate tracking result by adopting online SOSVM classifier. Meanwhile, we bring Color Names in this formulation to effectively boost the performance owing to its rich feature information encoded. Experimental results on several challenging benchmark datasets reveal that our approach outperforms numerous state-of-art trackers.

  2. Digital timing: sampling frequency, anti-aliasing filter and signal interpolation filter dependence on timing resolution

    NASA Astrophysics Data System (ADS)

    Cho, Sanghee; Grazioso, Ron; Zhang, Nan; Aykac, Mehmet; Schmand, Matthias

    2011-12-01

    The main focus of our study is to investigate how the performance of digital timing methods is affected by sampling rate, anti-aliasing and signal interpolation filters. We used the Nyquist sampling theorem to address some basic questions such as what will be the minimum sampling frequencies? How accurate will the signal interpolation be? How do we validate the timing measurements? The preferred sampling rate would be as low as possible, considering the high cost and power consumption of high-speed analog-to-digital converters. However, when the sampling rate is too low, due to the aliasing effect, some artifacts are produced in the timing resolution estimations; the shape of the timing profile is distorted and the FWHM values of the profile fluctuate as the source location changes. Anti-aliasing filters are required in this case to avoid the artifacts, but the timing is degraded as a result. When the sampling rate is marginally over the Nyquist rate, a proper signal interpolation is important. A sharp roll-off (higher order) filter is required to separate the baseband signal from its replicates to avoid the aliasing, but in return the computation will be higher. We demonstrated the analysis through a digital timing study using fast LSO scintillation crystals as used in time-of-flight PET scanners. From the study, we observed that there is no significant timing resolution degradation down to 1.3 Ghz sampling frequency, and the computation requirement for the signal interpolation is reasonably low. A so-called sliding test is proposed as a validation tool checking constant timing resolution behavior of a given timing pick-off method regardless of the source location change. Lastly, the performance comparison for several digital timing methods is also shown.

  3. 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.

  4. Time-domain technique for optimal design of digital-filter equalizers.

    NASA Technical Reports Server (NTRS)

    Burlage, D. W.; Houts, R. C.

    1972-01-01

    A technique is presented for the design of frequency-sampling and transversal digital filters from specified unit-impulse responses. The multiplier coefficients for the digital filter are specified by the use of a linear-programming algorithm. Examples include the design of digital filters to generate intersymbol-free pulses for data transmission over ideal bandlimited channels and to equalize data transmission channels that have known unit-impulse responses.

  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. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    PubMed

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

    2016-07-26

    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.

  7. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

    PubMed Central

    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

  8. 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

  9. 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

  10. 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.

  11. A comparison of filtering techniques on denoising terahertz coaxial digital holography image

    NASA Astrophysics Data System (ADS)

    Cui, Shan-shan; Li, Qi

    2016-10-01

    In the process of recording terahertz digital hologram, the hologram is easy to be contaminated by speckle noise, which leads to lower resolution in imaging system and affects the reconstruction results seriously. Thus, the study of filtering algorithms applicable for de-speckling terahertz digital holography image has important practical values. In this paper, non-local means filtering and guided bilateral filtering were brought to process the real image reconstructed from continuous-wave terahertz coaxial digital hologram. For comparison, median filtering, bilateral filtering, and robust bilateral filtering, were introduced as conventional methods to denoise the real image. Then, all the denoising results were evaluated. The comparison indicates that the guided bilateral filter manifests the optimal denoising effect for the terahertz digital holography image, both significantly suppressing speckle noise, and effectively preserving the useful information on the reconstructed image.

  12. Object tracking under nonuniform illumination with adaptive correlation filtering

    NASA Astrophysics Data System (ADS)

    Picos, Kenia; Díaz-Ramírez, Víctor H.; Kober, Vitaly

    2013-09-01

    A real-time system for illumination-invariant object tracking is proposed. The system is able to estimate at high-rate the position of a moving target in an input scene when is corrupted by the presence of a high cluttering background and nonuniform illumination. The position of the target is estimated with the help of a filter bank of space-variant correlation filters. The filters in the bank, adapt their parameters according to the local statistical parameters of the observed scene in a small region centered at coordinates of a predicted position for the target in each frame. The prediction is carried out by exploiting information of present and past frames, and by using a dynamic motion model of the target in a two-dimensional plane. Computer simulation results obtained with the proposed system are presented and discussed in terms of tracking accuracy, computational complexity, and tolerance to nonuniform illumination.

  13. Kalman filtering to suppress spurious signals in adaptive optics control.

    PubMed

    Poyneer, Lisa A; Véran, Jean-Pierre

    2010-11-01

    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.

  14. 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.

  15. 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.

  16. Adaptive two-pass rank order filter to remove impulse noise in highly corrupted images.

    PubMed

    Xu, Xiaoyin; Miller, Eric L; Chen, Dongbin; Sarhadi, Mansoor

    2004-02-01

    In this paper, we present an adaptive two-pass rank order filter to remove impulse noise in highly corrupted images. When the noise ratio is high, rank order filters, such as the median filter for example, can produce unsatisfactory results. Better results can be obtained by applying the filter twice, which we call two-pass filtering. To further improve the performance, we develop an adaptive two-pass rank order filter. Between the passes of filtering, an adaptive process is used to detect irregularities in the spatial distribution of the estimated impulse noise. The adaptive process then selectively replaces some pixels changed by the first pass of filtering with their original observed pixel values. These pixels are then kept unchanged during the second filtering. In combination, the adaptive process and the second filter eliminate more impulse noise and restore some pixels that are mistakenly altered by the first filtering. As a final result, the reconstructed image maintains a higher degree of fidelity and has a smaller amount of noise. The idea of adaptive two-pass processing can be applied to many rank order filters, such as a center-weighted median filter (CWMF), adaptive CWMF, lower-upper-middle filter, and soft-decision rank-order-mean filter. Results from computer simulations are used to demonstrate the performance of this type of adaptation using a number of basic rank order filters.

  17. Parameter testing for lattice filter based adaptive modal control systems

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

    For Large Space Structures (LSS), an adaptive control system is highly desirable. The present investigation is concerned with an 'indirect' adaptive control scheme wherein the system order, mode shapes, and modal amplitudes are estimated on-line using an identification scheme based on recursive, least-squares, lattice filters. Using the identified model parameters, a modal control law based on a pole-placement scheme with the objective of vibration suppression is employed. A method is presented for closed loop adaptive control of a flexible free-free beam. The adaptive control scheme consists of a two stage identification scheme working in series and a modal pole placement control scheme. The main conclusion from the current study is that the identified parameters cannot be directly used for controller design purposes.

  18. Digital watermarking for secure and adaptive teleconferencing

    NASA Astrophysics Data System (ADS)

    Vorbrueggen, Jan C.; Thorwirth, Niels

    2002-04-01

    The EC-sponsored project ANDROID aims to develop a management system for secure active networks. Active network means allowing the network's customers to execute code (Java-based so-called proxylets) on parts of the network infrastructure. Secure means that the network operator nonetheless retains full control over the network and its resources, and that proxylets use ANDROID-developed facilities to provide secure applications. Management is based on policies and allows autonomous, distributed decisions and actions to be taken. Proxylets interface with the system via policies; among actions they can take is controlling execution of other proxylets or redirection of network traffic. Secure teleconferencing is used as the application to demonstrate the approach's advantages. A way to control a teleconference's data streams is to use digital watermarking of the video, audio and/or shared-whiteboard streams, providing an imperceptible and inseparable side channel that delivers information from originating or intermediate stations to downstream stations. Depending on the information carried by the watermark, these stations can take many different actions. Examples are forwarding decisions based on security classifications (possibly time-varying) at security boundaries, set-up and tear-down of virtual private networks, intelligent and adaptive transcoding, recorder or playback control (e.g., speaking off the record), copyright protection, and sender authentication.

  19. Adaptive-filter models of the cerebellum: computational analysis.

    PubMed

    Dean, Paul; Porrill, John

    2008-01-01

    Many current models of the cerebellar cortical microcircuit are equivalent to an adaptive filter using the covariance learning rule. The adaptive filter is a development of the original Marr-Albus framework that deals naturally with continuous time-varying signals, thus addressing the issue of 'timing' in cerebellar function, and it can be connected in a variety of ways to other parts of the system, consistent with the microzonal organization of cerebellar cortex. However, its computational capacities are not well understood. Here we summarise the results of recent work that has focused on two of its intrinsic properties. First, an adaptive filter seeks to decorrelate its (mossy fibre) inputs from a (climbing fibre) teaching signal. This procedure can be used both for sensory processing, e.g. removal of interference from sensory signals, and for learning accurate motor commands, by decorrelating an efference copy of those commands from a sensory signal of inaccuracy. As a model of the cerebellum the adaptive filter thus forms a natural link between events at the cellular level, such as forms of synaptic plasticity and the learning rules they embody, and intelligent behaviour at the system level. Secondly, it has been shown that the covariance learning rule enables the filter to handle input and intrinsic noise optimally. Such optimality may underlie the recently described role of the cerebellum in producing accurate smooth pursuit eye movements in the face of sensory noise. Moreover, it has the consequence of driving most input weights to very small values, consistent with experimental data that many parallel-fibre synapses are normally silent. The effectiveness of silent synapses can only be altered by LTP, so learning tasks depending on a reduction of Purkinje cell firing require the synapses to be embedded in a second, inhibitory pathway from parallel fibre to Purkinje cell. This pathway and the appropriate climbing-fibre related plasticity have been described

  20. 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.

  1. A novel adaptive noise filtering method for SAR images

    NASA Astrophysics Data System (ADS)

    Li, Weibin; He, Mingyi

    2009-08-01

    In the most application situation, signal or image always is corrupted by additive noise. As a result there are mass methods to remove the additive noise while few approaches can work well for the multiplicative noise. The paper presents an improved MAP-based filter for multiplicative noise by adaptive window denoising technique. A Gamma noise models is discussed and a preprocessing technique to differential the matured and un-matured pixel is applied to get accurate estimate for Equivalent Number of Looks. Also the adaptive local window growth and 3 different denoise strategies are applied to smooth noise while keep its subtle information according to its local statistics feature. The simulation results show that the performance is better than existing filter. Several image experiments demonstrate its theoretical performance.

  2. 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.

  3. 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.

  4. Microseismic event denoising via adaptive directional vector median filters

    NASA Astrophysics Data System (ADS)

    Zheng, Jing; Lu, Ji-Ren; Jiang, Tian-Qi; Liang, Zhe

    2017-01-01

    We present a novel denoising scheme via Radon transform-based adaptive vector directional median filters named adaptive directional vector median filter (AD-VMF) to suppress noise for microseismic downhole dataset. AD-VMF contains three major steps for microseismic downhole data processing: (i) applying Radon transform on the microseismic data to obtain the parameters of the waves, (ii) performing S-transform to determine the parameters for filters, and (iii) applying the parameters for vector median filter (VMF) to denoise the data. The steps (i) and (ii) can realize the automatic direction detection. The proposed algorithm is tested with synthetic and field datasets that were recorded with a vertical array of receivers. The P-wave and S-wave direct arrivals are properly denoised for poor signal-to-noise ratio (SNR) records. In the simulation case, we also evaluate the performance with mean square error (MSE) in terms of signal-to-noise ratio (SNR). The result shows that the distortion of the proposed method is very low; the SNR is even less than 0 dB.

  5. A Kalman filter approach to adaptive estimation of multispectral signatures

    NASA Technical Reports Server (NTRS)

    Crane, R. B.

    1973-01-01

    The signatures of remote sensing data from agricultural crops exhibit significant non-stationarity, so that the performance of fixed parameter classifiers degenerates with time and distance from the initial training data. A class of adaptive decision-directed classifiers are being developed, based on Kalman filter theory. Limited results to date on two data sets indicate approximately a 25 to 40% reduction in rates of misclassification.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

    PubMed

    Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

    2016-12-19

    The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

  11. Adaptive probabilistic collocation based Kalman filter for unsaturated flow problem

    NASA Astrophysics Data System (ADS)

    Man, J.; Li, W.; Zeng, L.; Wu, L.

    2015-12-01

    The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively 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 to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so called "cure of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF is even more computationally expensive than EnKF. Motivated by recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problem. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to alleviate the inconsistency between model parameters and states. The performance of RAPCKF is tested by unsaturated flow numerical cases. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.

  12. Adaptive filtering of Echelle spectra of distant Quasars

    NASA Technical Reports Server (NTRS)

    Priebe, A.; Liebscher, D.-E.; Lorenz, H.; Richter, G.-M.

    1992-01-01

    The study of the Ly alpha - forest of distant (approximately greater than 3) Quasars is an important tool in obtaining a more detailed picture of the distribution of matter along the line of sight and thus of the general distribution of matter in the Universe and is therefore of important cosmological significance. Obviously, this is one of the tasks where spectral resolution plays an important role. The spectra used were obtained with the EFOSC at the ESO 3.6m telescope. Applying for the data reduction the standard Echelle procedure, as it is implemented for instance in the MIDAS-package, one uses stationary filters (e.g. median) for noise and cosmic particle event reduction in the 2-dimensional Echelle image. These filters are useful if the spatial spectrum of the noise reaches essentially higher frequencies then the highest resolution features in the image. Otherwise the resolution in the data will be degraded and the spectral lines smoothed. However, in the Echelle spectra the highest resolution is already in the range of one or a few pixels and therefore stationary filtering means always a loss of resolution. An Echelle reduction procedure on the basis of a space variable filter described which recognizes the local resolution in the presence of noise and adapts to it is developed. It was shown that this technique leads to an improvement in resolution by a factor of 2 with respect to standard procedures.

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

    NASA Technical Reports Server (NTRS)

    Sadr, Ramin; Shah, Biren; Hinedi, Sami

    1993-01-01

    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.

  14. 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.

  15. Image denoising using a directional adaptive diffusion filter

    NASA Astrophysics Data System (ADS)

    Zhao, Cuifang; Shi, Caicheng; He, Peikun

    2006-11-01

    Partial differential equations (PDEs) are well-known due to their good processing results which it can not only smooth the noise but also preserve the edges. But the shortcomings of these processes came to being noticed by people. In some sense, PDE filter is called "cartoon model" as it produces an approximation of the input image, use the same diffusion model and parameters to process noise and signal because it can not differentiate them, therefore, the image is naturally modified toward piecewise constant functions. A new method called a directional adaptive diffusion filter is proposed in the paper, which combines PDE mode with wavelet transform. The undecimated discrete wavelet transform (UDWT) is carried out to get different frequency bands which have obviously directional selectivity and more redundancy details. Experimental results show that the proposed method provides a performance better to preserve textures, small details and global information.

  16. 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.

  17. An Adaptive Multipath Mitigation Filter for GNSS Applications

    NASA Astrophysics Data System (ADS)

    Chang, Chung-Liang; Juang, Jyh-Ching

    2008-12-01

    Global navigation satellite system (GNSS) is designed to serve both civilian and military applications. However, the GNSS performance suffers from several errors, such as ionosphere delay, troposphere delay, ephemeris error, and receiver noise and multipath. Among these errors, the multipath is one of the most unpredictable error sources in high-accuracy navigation. This paper applies a modified adaptive filter to reduce code and carrier multipath errors in GPS. The filter employs a tap-delay line with an Adaline network to estimate the direction and the delayed-signal parameters. Then, the multipath effect is mitigated by subtracting the estimated multipath effects from the processed correlation function. The hardware complexity of the method is also compared with other existing methods. Simulation results show that the proposed method using field data has a significant reduction in multipath error especially in short-delay multipath scenarios.

  18. 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

  19. Noninvasive fetal ECG estimation using adaptive comb filter.

    PubMed

    Wei, Zheng; Xueyun, Wei; Jian jian, Zhong; Hongxing, Liu

    2013-10-01

    This paper describes a robust and simple algorithm for fetal electrocardiogram (FECG) estimation from abdominal signal using adaptive comb filter (ACF). The ACF can adjust itself to the temporal variations in fundamental frequency, which makes it qualified for the estimation of quasi-periodic component from physiologic signal, such as ECG. The validity and performance of the described method are confirmed through experiments on real fetal ECG data. A comparison with the well-known independent component analysis (ICA) method has also been presented.

  20. Adaptive SVD-Based Digital Image Watermarking

    NASA Astrophysics Data System (ADS)

    Shirvanian, Maliheh; Torkamani Azar, Farah

    Digital data utilization along with the increase popularity of the Internet has facilitated information sharing and distribution. However, such applications have also raised concern about copyright issues and unauthorized modification and distribution of digital data. Digital watermarking techniques which are proposed to solve these problems hide some information in digital media and extract it whenever needed to indicate the data owner. In this paper a new method of image watermarking based on singular value decomposition (SVD) of images is proposed which considers human visual system prior to embedding watermark by segmenting the original image into several blocks of different sizes, with more density in the edges of the image. In this way the original image quality is preserved in the watermarked image. Additional advantages of the proposed technique are large capacity of watermark embedding and robustness of the method against different types of image manipulation techniques.

  1. An innovations-based noise cancelling technique on inverse kepstrum whitening filter and adaptive FIR filter in beamforming structure.

    PubMed

    Jeong, Jinsoo

    2011-01-01

    This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure.

  2. 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.

  3. Improving the response of accelerometers for automotive applications by using LMS adaptive filters.

    PubMed

    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/s(2)) 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.

  4. Superconducting Magnetometry for Cardiovascular Studies and AN Application of Adaptive Filtering.

    NASA Astrophysics Data System (ADS)

    Leifer, Mark Curtis

    Sensitive magnetic detectors utilizing Superconducting Quantum Interference Devices (SQUID's) have been developed and used for studying the cardiovascular system. The theory of magnetic detection of cardiac currents is discussed, and new experimental data supporting the validity of the theory is presented. Measurements on both humans and dogs, in both healthy and diseased states, are presented using the new technique, which is termed vector magnetocardiography. In the next section, a new type of superconducting magnetometer with a room temperature pickup is analyzed, and techniques for optimizing its sensitivity to low-frequency sub-microamp currents are presented. Performance of the actual device displays significantly improved sensitivity in this frequency range, and the ability to measure currents in intact, in vivo biological fibers. The final section reviews the theoretical operation of a digital self-optimizing filter, and presents a four-channel software implementation of the system. The application of the adaptive filter to enhancement of geomagnetic signals for earthquake forecasting is discussed, and the adaptive filter is shown to outperform existing techniques in suppressing noise from geomagnetic records.

  5. 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.

  6. A Coarse Alignment Method Based on Digital Filters and Reconstructed Observation Vectors.

    PubMed

    Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Wang, Zhicheng

    2017-03-29

    In this paper, a coarse alignment method based on apparent gravitational motion is proposed. Due to the interference of the complex situations, the true observation vectors, which are calculated by the apparent gravity, are contaminated. The sources of the interference are analyzed in detail, and then a low-pass digital filter is designed in this paper for eliminating the high-frequency noise of the measurement observation vectors. To extract the effective observation vectors from the inertial sensors' outputs, a parameter recognition and vector reconstruction method are designed, where an adaptive Kalman filter is employed to estimate the unknown parameters. Furthermore, a robust filter, which is based on Huber's M-estimation theory, is developed for addressing the outliers of the measurement observation vectors due to the maneuver of the vehicle. A comprehensive experiment, which contains a simulation test and physical test, is designed to verify the performance of the proposed method, and the results show that the proposed method is equivalent to the popular apparent velocity method in swaying mode, but it is superior to the current methods while in moving mode when the strapdown inertial navigation system (SINS) is under entirely self-contained conditions.

  7. Digital DC-Reconstruction of AC-Coupled Electrophysiological Signals with a Single Inverting Filter.

    PubMed

    Abächerli, Roger; Isaksen, Jonas; Schmid, Ramun; Leber, Remo; Schmid, Hans-Jakob; Generali, Gianluca

    2016-01-01

    Since the introduction of digital electrocardiographs, high-pass filters have been necessary for successful analog-to-digital conversion with a reasonable amplitude resolution. On the other hand, such high-pass filters may distort the diagnostically significant ST-segment of the ECG, which can result in a misleading diagnosis. We present an inverting filter that successfully undoes the effects of a 0.05 Hz single pole high-pass filter. The inverting filter has been tested on more than 1600 clinical ECGs with one-minute durations and produces a negligible mean RMS-error of 3.1*10(-8) LSB. Alternative, less strong inverting filters have also been tested, as have different applications of the filters with respect to rounding of the signals after filtering. A design scheme for the alternative inverting filters has been suggested, based on the maximum strength of the filter. With the use of the suggested filters, it is possible to recover the original DC-coupled ECGs from AC-coupled ECGs, at least when a 0.05 Hz first order digital single pole high-pass filter is used for the AC-coupling.

  8. Automatic digital filtering for the accuracy improving of a digital holographic measurement system

    NASA Astrophysics Data System (ADS)

    Matrecano, Marcella; Miccio, Lisa; Persano, Anna; Quaranta, Fabio; Siciliano, Pietro; Ferraro, Pietro

    2014-05-01

    Digital holography (DH) is a well-established interferometric tool in optical metrology allowing the investigation of engineered surface shapes with microscale lateral resolution and nanoscale axial precision. With the advent of charged coupled devices (CCDs) with smaller pixel sizes, high speed computers and greater pixel numbers, DH became a very feasible technology which offers new possibilities for a large variety of applications. DH presents numerous advantages such as the direct access to the phase information, numerical correction of optical aberrations and the ability of a numerical refocusing from a single hologram. Furthermore, as an interferometric method, DH offers both a nodestructive and no-contact approach to very fragile objects combined with flexibility and a high sensitivity to geometric quantities such as thicknesses and displacements. These features recommend it for the solution of many imaging and measurements problems, such as microelectro-optomechanical systems (MEMS/MEOMS) inspection and characterization. In this work, we propose to improve the performance of a DH measurement on MEMS devices, through digital filters. We have developed an automatic procedure, inserted in the hologram reconstruction process, to selectively filter the hologram spectrum. The purpose is to provide very few noisy reconstructed images, thus increasing the accuracy of the conveyed information and measures performed on images. Furthermore, improving the image quality, we aim to make this technique application as simple and as accurate as possible.

  9. Adaptive de-blocking filter for low bit rate applications

    NASA Astrophysics Data System (ADS)

    Jin, Xin; Zhu, Guangxi

    2006-01-01

    In block-based video compression technology, blocking artifacts are obvious because of the luminance and chrominance discontinuities which are caused by block-based discrete cosine transform (DCT) and motion compensation. As a kind of solution, an in-loop filter has been successfully used in H.264 adapting to quantization parameter and video content. In this paper, blocking artifacts distribution properties are analyzed carefully to reflect the blocking effect more accurately in the low bit rate applications. Two important parameters, named blocking severity and pixel variation, are defined to describe the boundary strength and the gradient of the samples across the edge respectively. Through series of statistical data retrieval and analysis for these parameters using multiple representative video sequences, a novel blocking artifacts distribution model is concluded. Based on this distribution model, an improved filter is proposed to H.264 with novel strength determination rule and different alpha model. Comparing with H.264 anchor results, the proposed de-blocking filter shows better performance especially in subjective aspect, which could be widely used in low bit rate applications.

  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.

  11. 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.

  12. 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

  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. Evaluating the adaptive-filter model of the cerebellum.

    PubMed

    Dean, Paul; Porrill, John

    2011-07-15

    The adaptive-filter model of the cerebellar microcircuit is in widespread use, combining as it does an explanation of key microcircuit features with well-specified computational power. Here we consider two methods for its evaluation. One is to test its predictions concerning relations between cerebellar inputs and outputs. Where the relevant experimental data are available, e.g. for the floccular role in image stabilization, the predictions appear to be upheld. However, for the majority of cerebellar microzones these data have yet to be obtained. The second method is to test model predictions about details of the microcircuit. We focus on features apparently incompatible with the model, in particular non-linear patterns in Purkinje cell simple-spike firing. Analysis of these patterns suggests the following three conclusions. (i) It is important to establish whether they can be observed during task-related behaviour. (ii) Highly non-linear models based on these patterns are unlikely to be universal, because they would be incompatible with the (approximately) linear nature of floccular function. (iii) The control tasks for which these models are computationally suited need to be identified. At present, therefore, the adaptive filter remains a candidate model of at least some cerebellar microzones, and its evaluation suggests promising lines for future enquiry.

  15. Design and responses of Butterworth and critically damped digital filters.

    PubMed

    Robertson, D Gordon E; Dowling, James J

    2003-12-01

    For many years the Butterworth lowpass filter has been used to smooth many kinds of biomechanical data, despite the fact that it is underdamped and therefore overshoots and/or undershoots data during rapid transitions. A comparison of the conventional Butterworth filter with a critically damped filter shows that the critically damped filter not only removes the undershooting and overshooting, but has a superior rise time during rapid transitions. While analog filters always create phase distortion, both the critically damped and Butterworth filters can be modified to become zero-lag filters when the data are processed in both the forward and reverse directions. In such cases little improvement is realized by applying multiple passes. The Butterworth filter has superior 'roll-off' (attenuation of noise above the cutoff frequency) than the critically damped filter, but by increasing the number of passes of the critically damped filter the same 'roll-off' can be achieved. In summary, the critically damped filter was shown to have superior performance in the time domain than the Butterworth filter, but for data that need to be double differentiated (e.g. displacement data) the Butterworth filter may still be the better choice.

  16. 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.

  17. Suppression of impulse noise in medical images with the use of Fuzzy Adaptive Median Filter.

    PubMed

    Toprak, Abdullah; Güler, Inan

    2006-12-01

    A new rule based fuzzy filter for removal of highly impulse noise, called Rule Based Fuzzy Adaptive Median (RBFAM) Filter, is aimed to be discussed in this paper. The RBFAM filter is an improved version of Adaptive Median Filter (AMF) and is presented in the aim of noise reduction of images corrupted with additive impulse noise. The filter has three stages. Two of those stages are fuzzy rule based and last stage is based on standard median and adaptive median filter. The proposed filter can preserve image details better then AMF while suppressing additive salt & pepper or impulse type noise. In this paper, we placed our preference on bell-shaped membership function instead of triangular membership function in order to observe better results. Experimental results indicates that the proposed filter is improvable with increased fuzzy rules to reduce more noise corrupted images and to remove salt and pepper noise in a more effective way than what AMF filter does.

  18. 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.

  19. Digital adaptive control laws for the F-8

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Harvey, C. A.

    1976-01-01

    NASA is conducting a flight control research program in digital fly-by-wire technology using a modified F-8C aircraft. The first phase of this program used Apollo hardware to demonstrate the practicality of digital fly-by-wire in an actual test vehicle. For the second phase, conventional aircraft sensors and a large floating point digital computer are being utilized to test advanced control laws and redundancy concepts. As part of NASA's research in digital fly-by-wire technology, Honeywell developed digital adaptive flight control laws for flight test in the F-8C. Adaptation of the control laws was to be based on information sensed from conventional aircraft sensors excluding air data. The control laws were constrained to use only existing elevator, rudder, and ailerons as control effectors, each powered by existing actuators. Three adaptive control laws were successfully designed using maximum likelihood estimation, a Liapunov stable model tracker and a self-excited limit cycle concept. The maximum likelihood estimation design was selected as the most promising because of its capability to identify more than surface effectiveness parameters. The adaptive concepts, the control laws and comparisons of predicted performance are described.

  20. Adaptive Current Control Method for Hybrid Active Power Filter

    NASA Astrophysics Data System (ADS)

    Chau, Minh Thuyen

    2016-09-01

    This paper proposes an adaptive current control method for Hybrid Active Power Filter (HAPF). It consists of a fuzzy-neural controller, identification and prediction model and cost function. The fuzzy-neural controller parameters are adjusted according to the cost function minimum criteria. For this reason, the proposed control method has a capability on-line control clings to variation of the load harmonic currents. Compared to the single fuzzy logic control method, the proposed control method shows the advantages of better dynamic response, compensation error in steady-state is smaller, able to online control is better and harmonics cancelling is more effective. Simulation and experimental results have demonstrated the effectiveness of the proposed control method.

  1. Adaptive filtering for white-light LED visible light communication

    NASA Astrophysics Data System (ADS)

    Hsu, Chin-Wei; Chen, Guan-Hong; Wei, Liang-Yu; Chow, Chi-Wai; Lu, I.-Cheng; Liu, Yen-Liang; Chen, Hsing-Yu; Yeh, Chien-Hung; Liu, Yang

    2017-01-01

    White-light phosphor-based light-emitting diode (LED) can be used to provide lighting and visible light communication (VLC) simultaneously. However, the long relaxation time of phosphor can reduce the modulation bandwidth and limit the VLC data rate. Recent VLC works focus on improving the LED modulation bandwidths. Here, we propose and demonstrate the use of adaptive Volterra filtering (AVF) to increase the data rate of a white-light LED VLC system. The detailed algorithm and implementation of the AVF for the VLC system have been discussed. Using our proposed electrical frontend circuit and the proposed AVF, a significant data rate enhancement to 700.68 Mbit/s is achieved after 1-m free-space transmission using a single white-light phosphor-based LED.

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

    PubMed

    Alam, Mushfiqul; Rohac, Jan

    2015-02-02

    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.

  3. Hybrid vs Adaptive Ensemble Kalman Filtering for Storm Surge Forecasting

    NASA Astrophysics Data System (ADS)

    Altaf, M. U.; Raboudi, N.; Gharamti, M. E.; Dawson, C.; McCabe, M. F.; Hoteit, I.

    2014-12-01

    Recent storm surge events due to Hurricanes in the Gulf of Mexico have motivated the efforts to accurately forecast water levels. Toward this goal, a parallel architecture has been implemented based on a high resolution storm surge model, ADCIRC. However the accuracy of the model notably depends on the quality and the recentness of the input data (mainly winds and bathymetry), model parameters (e.g. wind and bottom drag coefficients), and the resolution of the model grid. Given all these uncertainties in the system, the challenge is to build an efficient prediction system capable of providing accurate forecasts enough ahead of time for the authorities to evacuate the areas at risk. We have developed an ensemble-based data assimilation system to frequently assimilate available data into the ADCIRC model in order to improve the accuracy of the model. In this contribution we study and analyze the performances of different ensemble Kalman filter methodologies for efficient short-range storm surge forecasting, the aim being to produce the most accurate forecasts at the lowest possible computing time. Using Hurricane Ike meteorological data to force the ADCIRC model over a domain including the Gulf of Mexico coastline, we implement and compare the forecasts of the standard EnKF, the hybrid EnKF and an adaptive EnKF. The last two schemes have been introduced as efficient tools for enhancing the behavior of the EnKF when implemented with small ensembles by exploiting information from a static background covariance matrix. Covariance inflation and localization are implemented in all these filters. Our results suggest that both the hybrid and the adaptive approach provide significantly better forecasts than those resulting from the standard EnKF, even when implemented with much smaller ensembles.

  4. 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

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

    PubMed

    Zhang, Zhen; Ma, Yaopeng

    2016-02-06

    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.

  6. Design of a digital adaptive control system for reentry vehicles.

    NASA Technical Reports Server (NTRS)

    Picon-Jimenez, J. L.; Montgomery, R. C.; Grigsby, L. L.

    1972-01-01

    The flying qualities of atmospheric reentry vehicles experience considerable variations due to the wide changes in flight conditions characteristic of reentry trajectories. A digital adaptive control system has been designed to modify the vehicle's dynamic characteristics and to provide desired flying qualities for all flight conditions. This adaptive control system consists of a finite-memory identifier which determines the vehicle's unknown parameters, and a gain computer which calculates feedback gains to satisfy flying quality requirements.

  7. Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy.

    PubMed

    He, Xuefei; Nguyen, Chuong Vinh; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R; Williams, Richard J; Rug, Melanie; Maier, Alexander G; Lee, Woei Ming

    2016-08-01

    Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding method to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here paves way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures.

  8. Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy

    PubMed Central

    He, Xuefei; Nguyen, Chuong Vinh; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R.; Williams, Richard J.; Rug, Melanie; Maier, Alexander G.; Lee, Woei Ming

    2016-01-01

    Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding method to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here paves way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures. PMID:27570702

  9. High-resolution image digitizing through 12x3-bit RGB-filtered CCD camera

    NASA Astrophysics Data System (ADS)

    Cheng, Andrew Y. S.; Pau, Michael C. Y.

    1996-09-01

    A high resolution computer-controlled CCD image capturing system is developed by using a 12 bits 1024 by 1024 pixels CCD camera and motorized RGB filters to grasp an image with color depth up to 36 bits. The filters distinguish the major components of color and collect them separately while the CCD camera maintains the spatial resolution and detector filling factor. The color separation can be done optically rather than electronically. The operation is simply by placing the capturing objects like color photos, slides and even x-ray transparencies under the camera system, the necessary parameters such as integration time, mixing level and light intensity are automatically adjusted by an on-line expert system. This greatly reduces the restrictions of the capturing species. This unique approach can save considerable time for adjusting the quality of image, give much more flexibility of manipulating captured object even if it is a 3D object with minimal setup fixers. In addition, cross sectional dimension of a 3D capturing object can be analyzed by adapting a fiber optic ring light source. It is particularly useful in non-contact metrology of a 3D structure. The digitized information can be stored in an easily transferable format. Users can also perform a special LUT mapping automatically or manually. Applications of the system include medical images archiving, printing quality control, 3D machine vision, and etc.

  10. Efficient design of two-dimensional recursive digital filters. Final report

    SciTech Connect

    Twogood, R.E.; Mitra, S.K.

    1980-01-01

    This report outlines the research progress during the period August 1978 to July 1979. This work can be divided into seven basic project areas. Project 1 deals with a comparative study of 2-D recursive and nonrecursive digital filters. The second project addresses a new design technique for 2-D half-plane recursive filters, and Projects 3 thru 5 deal with implementation issues. The sixth project presents our recent study of the applicability of array processors to 2-D digital signal processing. The final project involves our investigation into techniques for incorporating symmetry constraints on 2-D recursive filters in order to yield more efficient implementations.

  11. Digital adaptive optics line-scanning confocal imaging system.

    PubMed

    Liu, Changgeng; Kim, Myung K

    2015-01-01

    A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea.

  12. Digital adaptive optics line-scanning confocal imaging system

    PubMed Central

    Liu, Changgeng; Kim, Myung K.

    2015-01-01

    Abstract. A digital adaptive optics line-scanning confocal imaging (DAOLCI) system is proposed by applying digital holographic adaptive optics to a digital form of line-scanning confocal imaging system. In DAOLCI, each line scan is recorded by a digital hologram, which allows access to the complex optical field from one slice of the sample through digital holography. This complex optical field contains both the information of one slice of the sample and the optical aberration of the system, thus allowing us to compensate for the effect of the optical aberration, which can be sensed by a complex guide star hologram. After numerical aberration compensation, the corrected optical fields of a sequence of line scans are stitched into the final corrected confocal image. In DAOLCI, a numerical slit is applied to realize the confocality at the sensor end. The width of this slit can be adjusted to control the image contrast and speckle noise for scattering samples. DAOLCI dispenses with the hardware pieces, such as Shack–Hartmann wavefront sensor and deformable mirror, and the closed-loop feedbacks adopted in the conventional adaptive optics confocal imaging system, thus reducing the optomechanical complexity and cost. Numerical simulations and proof-of-principle experiments are presented that demonstrate the feasibility of this idea. PMID:26140334

  13. 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.

  14. Adapting to the Digital Age: A Narrative Approach

    ERIC Educational Resources Information Center

    Cousins, Sarah; Bissar, Dounia

    2012-01-01

    The article adopts a narrative inquiry approach to foreground informal learning and exposes a collection of stories from tutors about how they adapted comfortably to the digital age.We were concerned that despite substantial evidence that bringing about changes in pedagogic practices can be difficult, there is a gap in convincing approaches to…

  15. Holographic fluorescence microscopy with incoherent digital holographic adaptive optics.

    PubMed

    Jang, Changwon; Kim, Jonghyun; Clark, David C; Lee, Seungjae; Lee, Byoungho; Kim, Myung K

    2015-01-01

    Introduction of adaptive optics technology into astronomy and ophthalmology has made great contributions in these fields, allowing one to recover images blurred by atmospheric turbulence or aberrations of the eye. Similar adaptive optics improvement in microscopic imaging is also of interest to researchers using various techniques. Current technology of adaptive optics typically contains three key elements: a wavefront sensor, wavefront corrector, and controller. These hardware elements tend to be bulky, expensive, and limited in resolution, involving, for example, lenslet arrays for sensing or multiactuator deformable mirrors for correcting. We have previously introduced an alternate approach based on unique capabilities of digital holography, namely direct access to the phase profile of an optical field and the ability to numerically manipulate the phase profile. We have also demonstrated that direct access and compensation of the phase profile are possible not only with conventional coherent digital holography, but also with a new type of digital holography using incoherent light: selfinterference incoherent digital holography (SIDH). The SIDH generates a complex—i.e., amplitude plus phase—hologram from one or several interferograms acquired with incoherent light, such as LEDs, lamps, sunlight, or fluorescence. The complex point spread function can be measured using guide star illumination and it allows deterministic deconvolution of the full-field image. We present experimental demonstration of aberration compensation in holographic fluorescence microscopy using SIDH. Adaptive optics by SIDH provides new tools for improved cellular fluorescence microscopy through intact tissue layers or other types of aberrant media.

  16. Holographic fluorescence microscopy with incoherent digital holographic adaptive optics

    NASA Astrophysics Data System (ADS)

    Jang, Changwon; Kim, Jonghyun; Clark, David C.; Lee, Seungjae; Lee, Byoungho; Kim, Myung K.

    2015-11-01

    Introduction of adaptive optics technology into astronomy and ophthalmology has made great contributions in these fields, allowing one to recover images blurred by atmospheric turbulence or aberrations of the eye. Similar adaptive optics improvement in microscopic imaging is also of interest to researchers using various techniques. Current technology of adaptive optics typically contains three key elements: a wavefront sensor, wavefront corrector, and controller. These hardware elements tend to be bulky, expensive, and limited in resolution, involving, for example, lenslet arrays for sensing or multiactuator deformable mirrors for correcting. We have previously introduced an alternate approach based on unique capabilities of digital holography, namely direct access to the phase profile of an optical field and the ability to numerically manipulate the phase profile. We have also demonstrated that direct access and compensation of the phase profile are possible not only with conventional coherent digital holography, but also with a new type of digital holography using incoherent light: self­interference incoherent digital holography (SIDH). The SIDH generates a complex-i.e., amplitude plus phase-hologram from one or several interferograms acquired with incoherent light, such as LEDs, lamps, sunlight, or fluorescence. The complex point spread function can be measured using guide star illumination and it allows deterministic deconvolution of the full-field image. We present experimental demonstration of aberration compensation in holographic fluorescence microscopy using SIDH. Adaptive optics by SIDH provides new tools for improved cellular fluorescence microscopy through intact tissue layers or other types of aberrant media.

  17. Fast complex memory polynomial-based adaptive digital predistorter

    NASA Astrophysics Data System (ADS)

    Singh Sappal, Amandeep; Singh Patterh, Manjeet; Sharma, Sanjay

    2011-07-01

    Today's 3G wireless systems require both high linearity and high power amplifier (PA) efficiency. The high peak-to-average ratios of the digital modulation schemes used in 3G wireless systems require that the RF PA maintain high linearity over a large range while maintaining this high efficiency; these two requirements are often at odds with each other with many of the traditional amplifier architectures. In this article, a fast and easy-to-implement adaptive digital predistorter has been presented for Wideband Code Division Multiplexed signals using complex memory polynomial work function. The proposed algorithm has been implemented to test a Motorola LDMOSFET PA. The proposed technique also takes care of the memory effects of the PA, which have been ignored in many proposed techniques in the literature. The results show that the new complex memory polynomial-based adaptive digital predistorter has better linearisation performance than conventional predistortion techniques.

  18. Identification method for digital image forgery and filtering region through interpolation.

    PubMed

    Hwang, Min Gu; Har, Dong Hwan

    2014-09-01

    Because of the rapidly increasing use of digital composite images, recent studies have identified digital forgery and filtering regions. This research has shown that interpolation, which is used to edit digital images, is an effective way to analyze digital images for composite regions. Interpolation is widely used to adjust the size of the image of a composite target, making the composite image seem natural by rotating or deforming. As a result, many algorithms have been developed to identify composite regions by detecting a trace of interpolation. However, many limitations have been found in detection maps developed to identify composite regions. In this study, we analyze the pixel patterns of noninterpolation and interpolation regions. We propose a detection map algorithm to separate the two regions. To identify composite regions, we have developed an improved algorithm using minimum filer, Laplacian operation and maximum filters. Finally, filtering regions that used the interpolation operation are analyzed using the proposed algorithm.

  19. An implementable digital adaptive flight controller designed using stabilized single stage algorithms

    NASA Technical Reports Server (NTRS)

    Kaufman, H.; Alag, G.

    1975-01-01

    Simple mechanical linkages have not solved the many control problems associated with high performance aircraft maneuvering throughout a wide flight envelope. One procedure for retaining uniform handling qualities over such an envelope is to implement a digital adaptive controller. Towards such an implementation an explicit adaptive controller which makes direct use of on-line parameter identification, has been developed and applied to both linearized and nonlinear equations of motion for a typical fighter aircraft. This controller is composed of an on-line weighted least squares parameter identifier, a Kalman state filter, and a model following control law designed using single stage performance indices. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for on-board implementation.

  20. Removing tidal-period variations from time-series data using low-pass digital filters

    USGS Publications Warehouse

    Walters, Roy A.; Heston, Cynthia

    1982-01-01

    Several low-pass, digital filters are examined for their ability to remove tidal Period Variations from a time-series of water surface elevation for San Francisco Bay. The most efficient filter is the one which is applied to the Fourier coefficients of the transformed data, and the filtered data recovered through an inverse transform. The ability of the filters to remove the tidal components increased in the following order: 1) cosine-Lanczos filter, 2) cosine-Lanczos squared filter; 3) Godin filter; and 4) a transform fitter. The Godin fitter is not sufficiently sharp to prevent severe attenuation of 2–3 day variations in surface elevation resulting from weather events.

  1. Digital separation of diaminobenzidine-stained tissues via an automatic color-filtering for immunohistochemical quantification.

    PubMed

    Fu, Rong; Ma, Xiaomian; Bian, Zhaoying; Ma, Jianhua

    2015-02-01

    The digital separation of diaminobenzidine (DAB)-stained tissues from hematoxylin background is an important pre-processing step to analyze immunostains. In most stain separation methods, specific color channels (for example: RGB, HSI, CMYK) or color deconvolution matrices are used to obtain different tissue contrasts between DAB- and hematoxylin-stained areas. However, these methods could produce incomplete separation or color changes because the color spectra of stains and co-localized stains overlap in histological images. Therefore, we proposed an automatic color-filtering to separate hematoxylin- and DAB-stained tissues. In implantation, the RGB images of DAB-labeled immunostains are first converted to 8-bit BN images by a mathematical translation to produce the largest contrast between brown DAB-stained tissues and blue hematoxylin-stained tissues. The first valley in the histogram revised by nonuniform quantization is set as the cut-off point to obtain a brown filter. DAB-stained tissues are accurately delineated from the background counterstain, resulting in DAB-only-image and De-DAB-image. Subsequently, a blue filter is designed in the CIE-Lab color space to further delineate the hematoxylin-stained tissues from the De-DAB-image. Finally, the average values of the remaining pixels of the De-DAB-image are set as the background color of the DAB-only-image to manage uneven dyeing and provide DAB-stained-image for adaptive immunohistochemistry quantitation. Extensive experimental results demonstrated that the proposed method has significant advantages compared with existing methods in terms of complete stain separation without changing the color in DAB-stained areas.

  2. Design of efficient circularly symmetric two-dimensional variable digital FIR filters.

    PubMed

    Bindima, Thayyil; Elias, Elizabeth

    2016-05-01

    Circularly symmetric two-dimensional (2D) finite impulse response (FIR) filters find extensive use in image and medical applications, especially for isotropic filtering. Moreover, the design and implementation of 2D digital filters with variable fractional delay and variable magnitude responses without redesigning the filter has become a crucial topic of interest due to its significance in low-cost applications. Recently the design using fixed word length coefficients has gained importance due to the replacement of multipliers by shifters and adders, which reduces the hardware complexity. Among the various approaches to 2D design, transforming a one-dimensional (1D) filter to 2D by transformation, is reported to be an efficient technique. In this paper, 1D variable digital filters (VDFs) with tunable cut-off frequencies are designed using Farrow structure based interpolation approach, and the sub-filter coefficients in the Farrow structure are made multiplier-less using canonic signed digit (CSD) representation. The resulting performance degradation in the filters is overcome by using artificial bee colony (ABC) optimization. Finally, the optimized 1D VDFs are mapped to 2D using generalized McClellan transformation resulting in low complexity, circularly symmetric 2D VDFs with real-time tunability.

  3. Adaptive Noise Suppression Using Digital Signal Processing

    NASA Technical Reports Server (NTRS)

    Kozel, David; Nelson, Richard

    1996-01-01

    A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

  4. A Low Power Linear Phase Digital FIR Filter for Wearable ECG Devices.

    PubMed

    Lian, Yong; Yu, Jianghong

    2005-01-01

    In this paper we present a low power linear phase digital FIR filter which is a part of an ECG-on-Chip. The ECG-on-Chip can be embedded into clothing to acquire the electrocardiogram (ECG) signal and send a warning message to a mobile phone or PDA if an abnormal ECG is detected. The proposed new filter structure significantly reduces the arithmetic operations for each sample which in turn lowers the power consumption. The filter is developed based on the interpolated finite impulse filter technique and is very attractive for a low cost and low power VLSI implementation.

  5. Digital filter control of remotely operated flexible robotic structures

    SciTech Connect

    Feddema, J.T.

    1992-01-01

    This paper presents an infinite impulse response (IIR) filtering technique for reducing structural vibration in remotely operated robotic systems. The technique uses a discrete filter between the operator's joy stick and the robot controller to alter the inputs of the system so that residual vibration and swing are reduced. A linearized plant model of the system is analyzed in the discrete time domain, and the filter is designed using pole-zero placement in the z-plane. This technique has been successfully applied to a two link flexible arm and a gantry crane with a suspended payload.

  6. Digital filter control of remotely operated flexible robotic structures

    SciTech Connect

    Feddema, J.T.

    1992-12-31

    This paper presents an infinite impulse response (IIR) filtering technique for reducing structural vibration in remotely operated robotic systems. The technique uses a discrete filter between the operator`s joy stick and the robot controller to alter the inputs of the system so that residual vibration and swing are reduced. A linearized plant model of the system is analyzed in the discrete time domain, and the filter is designed using pole-zero placement in the z-plane. This technique has been successfully applied to a two link flexible arm and a gantry crane with a suspended payload.

  7. PLI cancellation in ECG signal based on adaptive filter by using Wiener-Hopf equation for providing initial condition.

    PubMed

    Manosueb, Anchalee; Koseeyaporn, Jeerasuda; Wardkein, Paramote

    2014-01-01

    This paper presents a technique for finding the optimal initial weight for adaptive filter by using difference equation. The obtained analytical response of the system identifies the appropriate weights for the system and shows that the MSE depends on the initial weight. The proposed technique is applied to eliminate the known frequency power line interference (PLI) signal in the electrocardiogram (ECG) signal. The PLI signal is considered as a combination of cosine and sine signals. The adaptive filter, therefore, attempts to adjust the amplitude of cosine and sine signals to synthesize a reference signal very similar to the contaminated PLI signal. To compare the potential of the proposed technique to other techniques, the system is simulated by using the Matlab program and the TMS320C6713 digital board. The simulation results demonstrate that the proposed technique enables the system to eliminate the PLI signal with the fastest time and gains the superior results of the recovered ECG signal.

  8. MR images restoration with the use of fuzzy filter having adaptive membership parameters.

    PubMed

    Güler, I; Toprak, A; Demirhan, A; Karakiş, R

    2008-06-01

    A new fuzzy adaptive median filter is presented for the noise reduction of magnetic resonance images corrupted with heavy impulse (salt and pepper) noise. In this paper, we have proposed a Fuzzy Adaptive Median Filter with Adaptive Membership Parameters (FAMFAMP) for removing highly corrupted salt and pepper noise, with preserving image edges and details. The FAMFAMP filter is an improved version of Adaptive Median Filter (AMF) and is presented in the aim of noise reduction of images corrupted with additive impulse noise. The proposed filter can preserve image details better than AMF while suppressing additive salt and pepper or impulse type noise. In this paper, we placed our preference on bell-shaped membership function with adaptive parameters instead of triangular membership function without variable coefficients in order to observe better results.

  9. 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.

  10. 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

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

    PubMed

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

    2016-07-16

    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.

  12. 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.

  13. 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

  14. The design of digital-adaptive controllers for VTOL aircraft

    NASA Technical Reports Server (NTRS)

    Stengel, R. F.; Broussard, J. R.; Berry, P. W.

    1976-01-01

    Design procedures for VTOL automatic control systems have been developed and are presented. Using linear-optimal estimation and control techniques as a starting point, digital-adaptive control laws have been designed for the VALT Research Aircraft, a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. These control laws are designed to interface with velocity-command and attitude-command guidance logic, which could be used in short-haul VTOL operations. Developments reported here include new algorithms for designing non-zero-set-point digital regulators, design procedures for rate-limited systems, and algorithms for dynamic control trim setting.

  15. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment

  16. Holographic fluorescence microscopy with incoherent digital holographic adaptive optics

    NASA Astrophysics Data System (ADS)

    Jang, Changwon; Kim, Jonghyun; Clark, David C.; Lee, Byoungho; Kim, Myung K.

    2015-03-01

    Introduction of adaptive optics technology into astronomy and ophthalmology has made great contributions in these fields, allowing one to recover images blurred by atmospheric turbulence or aberrations of the eye. Similar adaptive optics improvement in microscopic imaging is also of interest to researchers using various techniques. Current technology of adaptive optics typically contains three key elements: wavefront sensor, wavefront corrector and controller. These hardware elements tend to be bulky, expensive, and limited in resolution, involving, e.g., lenslet arrays for sensing or multi-acuator deformable mirrors for correcting. We have previously introduced an alternate approach to adaptive optics based on unique capabilities of digital holography, namely direct access to the phase profile of an optical field and the ability to numerically manipulate the phase profile. We have also demonstrated that direct access and compensation of the phase profile is possible not only with the conventional coherent type of digital holography, but also with a new type of digital holography using incoherent light: self-interference incoherent digital holography (SIDH). The SIDH generates complex - i.e. amplitude plus phase - hologram from one or several interferograms acquired with incoherent light, such as LEDs, lamps, sunlight, or fluorescence. The complex point spread function can be measured using a guide star illumination and it allows deterministic deconvolution of the full-field image. We present experimental demonstration of aberration compensation in holographic fluorescence microscopy using SIDH. The adaptive optics by SIDH provides new tools for improved cellular fluorescence microscopy through intact tissue layers or other types of aberrant media.

  17. A gradient-adaptive lattice-based complex adaptive notch filter

    NASA Astrophysics Data System (ADS)

    Zhu, Rui; Yang, Feiran; Yang, Jun

    2016-12-01

    This paper presents a new complex adaptive notch filter to estimate and track the frequency of a complex sinusoidal signal. The gradient-adaptive lattice structure instead of the traditional gradient one is adopted to accelerate the convergence rate. It is proved that the proposed algorithm results in unbiased estimations by using the ordinary differential equation approach. The closed-form expressions for the steady-state mean square error and the upper bound of step size are also derived. Simulations are conducted to validate the theoretical analysis and demonstrate that the proposed method generates considerably better convergence rates and tracking properties than existing methods, particularly in low signal-to-noise ratio environments.

  18. A Novel Adaptive Frequency Estimation Algorithm Based on Interpolation FFT and Improved Adaptive Notch Filter

    NASA Astrophysics Data System (ADS)

    Shen, Ting-ao; Li, Hua-nan; Zhang, Qi-xin; Li, Ming

    2017-02-01

    The convergence rate and the continuous tracking precision are two main problems of the existing adaptive notch filter (ANF) for frequency tracking. To solve the problems, the frequency is detected by interpolation FFT at first, which aims to overcome the convergence rate of the ANF. Then, referring to the idea of negative feedback, an evaluation factor is designed to monitor the ANF parameters and realize continuously high frequency tracking accuracy. According to the principle, a novel adaptive frequency estimation algorithm based on interpolation FFT and improved ANF is put forward. Its basic idea, specific measures and implementation steps are described in detail. The proposed algorithm obtains a fast estimation of the signal frequency, higher accuracy and better universality qualities. Simulation results verified the superiority and validity of the proposed algorithm when compared with original algorithms.

  19. Digital adaptive controllers for VTOL vehicles. Volume 1: Concept evaluation

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.; Pratt, S. G.

    1979-01-01

    A digital self-adaptive flight control system was developed for flight test in the VTOL approach and landing technology (VALT) research aircraft (a modified CH-47 helicopter). The control laws accept commands from an automatic on-board guidance system. The primary objective of the control laws is to provide good command-following with a minimum cross-axis response. Three attitudes and vertical velocity are separately commanded. Adaptation of the control laws is based on information from rate and attitude gyros and a vertical velocity measurement. The final design resulted from a comparison of two different adaptive concepts--one based on explicit parameter estimates from a real-time maximum-likelihood estimation algorithm, the other based on an implicit model reference adaptive system. The two designs were compared on the basis of performance and complexity.

  20. Advanced filter banks and time interleaving for analog and digital conversion

    NASA Astrophysics Data System (ADS)

    Velazquez, Scott R.

    1999-10-01

    This paper presents a comparison of Advanced Filter Banks (AFB) and Time-Interleaving for high-speed, high-resolution conversion between analog and digital signals using a parallel array of converters. The AFB is an unconventional class of filter bank that employs both analog and digital signal processing. The AFB improves the speed and resolution of the conversion compared to the standard Time-Interleaved array conversion technique. Gain and phase mismatch errors are analyzed for both the AFB and Time-Interleaving architectures. The filters in the AFB isolate the converters in the array from each other and attenuate the effects of mismatches. In four-channel example systems analyzed in this paper, gain and phase errors are attenuated by 21 dB more in the AFB (with 30 dB stopband attenuation) than in the Time- Interleaved system. The AFB is capable of analog-to-digital conversion with 14-bit resolution and 400 MHz sample rate.

  1. A Digital Filter Representation of the ASQ-81 Magnetometer

    DTIC Science & Technology

    1983-09-01

    81 magnetometer filter transfer functions. The input to the fixed high pass filter is called SIG (T), where I is the current data sample. The output...forth, and the symbol * denotes multiplication. For the fixed high pass filter: YO(I)=BFHPO* SIG (I) + BFHPl* SIG (I-1) + BFHP2* SIG (I-2) + AFHP1*YO(I-l...LU z - 0 -0 (4 ’ 0 1 0 LUL * U. . (li) . u ii w 0U c C33 -0 u- V ’ 0 co ij (3 %P 0-4 ( .1 - jue MOOC C (0JU) *d tn0C-QCI,- tn f-i -i."" a1 0 c

  2. A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

    PubMed Central

    Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

    2016-01-01

    The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

  3. 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.

  4. 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.

  5. Wavelet transforms and filter banks in digital communications

    NASA Astrophysics Data System (ADS)

    Lindsey, Alan R.; Medley, Michael J.

    1996-03-01

    Within the past few years, wavelet transforms and filter banks have received considerable attention in the technical literature, prompting applications in a variety of disciplines including applied mathematics, speech and image processing and compression, medical imaging, geophysics, signal processing, and information theory. More recently, several researchers in the field of communications have developed theoretical foundations for applications of wavelets as well. The objective of this paper is to survey the connections of wavelets and filter banks to communication theory and summarize current research efforts.

  6. Blood Cell Separation Device Using Serially Connected Membrane Filters for Adapting to Blood Flow Properties

    NASA Astrophysics Data System (ADS)

    Kobayashi, Taizo; Kato, Daiki; Koga, Hiroyuki; Morimoto, Kenichi; Fukuda, Makoto; Kinoshita, Yoshiharu; Yoshida, Hiroshi; Konishi, Satoshi

    This paper proposes a cooperative operation of serially connected membrane filters toward adaptive blood cell separation system in order to overcome a restriction of a single membrane filter. Serially connected membrane filters allow that downstream filters extract blood plasma from residual blood at upstream filters. Consequently, it becomes possible to adapt filtering characteristics to changing properties of blood. We focus on trans-membrane pressure difference in order to prevent hemolysis. Our strategy can be realized as a miniaturized PDMS fluidic chip. Our laboratory experiment using a prototype shows that plasma extraction efficiency is improved from 34% to 75%. Toward an integrated system, this paper also demonstrates multiple filters are successfully integrated into a PDMS fluidic chip.

  7. 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.

  8. Grid artifact reduction for direct digital radiography detectors based on rotated stationary grids with homomorphic filtering

    SciTech Connect

    Kim, Dong Sik; Lee, Sanggyun

    2013-06-15

    Purpose: Grid artifacts are caused when using the antiscatter grid in obtaining digital x-ray images. In this paper, research on grid artifact reduction techniques is conducted especially for the direct detectors, which are based on amorphous selenium. Methods: In order to analyze and reduce the grid artifacts, the authors consider a multiplicative grid image model and propose a homomorphic filtering technique. For minimal damage due to filters, which are used to suppress the grid artifacts, rotated grids with respect to the sampling direction are employed, and min-max optimization problems for searching optimal grid frequencies and angles for given sampling frequencies are established. The authors then propose algorithms for the grid artifact reduction based on the band-stop filters as well as low-pass filters. Results: The proposed algorithms are experimentally tested for digital x-ray images, which are obtained from direct detectors with the rotated grids, and are compared with other algorithms. It is shown that the proposed algorithms can successfully reduce the grid artifacts for direct detectors. Conclusions: By employing the homomorphic filtering technique, the authors can considerably suppress the strong grid artifacts with relatively narrow-bandwidth filters compared to the normal filtering case. Using rotated grids also significantly reduces the ringing artifact. Furthermore, for specific grid frequencies and angles, the authors can use simple homomorphic low-pass filters in the spatial domain, and thus alleviate the grid artifacts with very low implementation complexity.

  9. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Montenegro, Justino (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of Field Programmable Gate Arrays (FPGA's) in the hardware implementation of fast digital signal processing functions. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used Proportional-Integral-Derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a Digital Signal Processor (DSP) device or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using DSP devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, Pulse Width Modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. An alternative is required for compact implementation of such functionality to withstand the harsh environment encountered on spacemap. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive-control algorithm

  10. On the Performance of the Martin Digital Filter for High- and Low-pass Applications

    NASA Technical Reports Server (NTRS)

    Mcclain, C. R.

    1979-01-01

    A nonrecursive numerical filter is described in which the weighting sequence is optimized by minimizing the excursion from the ideal rectangular filter in a least squares sense over the entire domain of normalized frequency. Additional corrections to the weights in order to reduce overshoot oscillations (Gibbs phenomenon) and to insure unity gain at zero frequency for the low pass filter are incorporated. The filter is characterized by a zero phase shift for all frequencies (due to a symmetric weighting sequence), a finite memory and stability, and it may readily be transformed to a high pass filter. Equations for the filter weights and the frequency response function are presented, and applications to high and low pass filtering are examined. A discussion of optimization of high pass filter parameters for a rather stringent response requirement is given in an application to the removal of aircraft low frequency oscillations superimposed on remotely sensed ocean surface profiles. Several frequency response functions are displayed, both in normalized frequency space and in period space. A comparison of the performance of the Martin filter with some other commonly used low pass digital filters is provided in an application to oceanographic data.

  11. Adaptive carrier recovery systems for digital data communications receivers

    NASA Astrophysics Data System (ADS)

    Cupo, Robert L.; Gitlin, Richard D.

    1989-12-01

    Adaptive or predictive carrier recovery systems, which are essential in high-performance quadrature-amplitude-modulated (QAM) data communications systems to correct for phase jitter and frequency offset, are considered. Analytical and experimental results are presented for two structures that implement a predictive carrier recovery system. These systems, which adapt their structure to match the spectral properties of the impairments, avoid the conflict between a wide bandwidth (to track fast jitter) and a narrow bandwidth (to minimize output noise) inherent in most carrier recovery loops. Such a system increases the likelihood that very bandwidth-efficient modems (e.g., 7 bits/s/Hz for 19.2 kbits/s voiceband modem applications) can provide reliable transmission in the presence of severe phase jitter and frequency offset. In particular, the predictive carrier recovery systems can track sinusoidal jitter present at more than one frequency as well as generalized time-varying phase jitter processes. Both finite-impulse-response and infinite-impulse-response (IIR) adaptive phase tracking systems are considered. Prior limitations on adaptive IIR filters are overcome by designing a structure that is guaranteed to be stable and to possess only a global minimum as the filter coefficients converge to their desired values.

  12. Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

    NASA Technical Reports Server (NTRS)

    Baer-Riedhart, Jennifer L.; Landy, Robert J.

    1987-01-01

    The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.

  13. Digital IIR Filters Design Using Differential Evolution Algorithm with a Controllable Probabilistic Population Size

    PubMed Central

    Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Du, Wei

    2012-01-01

    Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digital IIR filter design in this paper. The suggested algorithm is a kind of DE variants with a controllable probabilistic (CPDE) population size. It considers the convergence speed and the computational cost simultaneously by nonperiodic partial increasing or declining individuals according to fitness diversities. In addition, we discuss as well some important aspects for IIR filter design, such as the cost function value, the influence of (noise) perturbations, the convergence rate and successful percentage, the parameter measurement, etc. As to the simulation result, it shows that the presented algorithm is viable and comparable. Compared with six existing State-of-the-Art algorithms-based digital IIR filter design methods obtained by numerical experiments, CPDE is relatively more promising and competitive. PMID:22808191

  14. Digital adaptive model following flight control. [using fighter aircraft mathematical model-following algorithm

    NASA Technical Reports Server (NTRS)

    Alag, G. S.; Kaufman, H.

    1974-01-01

    Simple mechanical linkages are often unable to cope with the many control problems associated with high performance aircraft maneuvering over a wide flight envelope. One procedure for retaining uniform handling qualities over such an envelope is to implement a digital adaptive controller. Towards such an implementation an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized equations of motion for a typical fighter aircraft. The system is composed of an online weighted least squares identifier, a Kalman state filter, and a single stage real model following control law. The corresponding control gains are readily adjustable in accordance with parameter changes to ensure asymptotic stability if the conditions for perfect model following are satisfied and stability in the sense of boundedness otherwise.

  15. An algorithmic approach to adaptive state filtering using recurrent neural networks.

    PubMed

    Parlos, A G; Menon, S K; Atiya, A

    2001-01-01

    Practical algorithms are presented for adaptive state filtering in nonlinear dynamic systems when the state equations are unknown. The state equations are constructively approximated using neural networks. The algorithms presented are based on the two-step prediction-update approach of the Kalman filter. The proposed algorithms make minimal assumptions regarding the underlying nonlinear dynamics and their noise statistics. Non-adaptive and adaptive state filtering algorithms are presented with both off-line and online learning stages. The algorithms are implemented using feedforward and recurrent neural network and comparisons are presented. Furthermore, extended Kalman filters (EKFs) are developed and compared to the filter algorithms proposed. For one of the case studies, the EKF converges but results in higher state estimation errors that the equivalent neural filters. For another, more complex case study with unknown system dynamics and noise statistics, the developed EKFs do not converge. The off-line trained neural state filters converge quite rapidly and exhibit acceptable performance. Online training further enhances the estimation accuracy of the developed adaptive filters, effectively decoupling the eventual filter accuracy from the accuracy of the process model.

  16. Optical Cluster-Finding with an Adaptive Matched-Filter Technique: Algorithm and Comparison with Simulations

    SciTech Connect

    Dong, Feng; Pierpaoli, Elena; Gunn, James E.; Wechsler, Risa H.

    2007-10-29

    We present a modified adaptive matched filter algorithm designed to identify clusters of galaxies in wide-field imaging surveys such as the Sloan Digital Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys with spectroscopic coverage, multicolor photometric redshifts, no redshift information at all, and any combination of these within one survey. It works with high efficiency in multi-band imaging surveys where photometric redshifts can be estimated with well-understood error distributions. Tests of the algorithm on realistic mock SDSS catalogs suggest that the detected sample is {approx} 85% complete and over 90% pure for clusters with masses above 1.0 x 10{sup 14}h{sup -1} M and redshifts up to z = 0.45. The errors of estimated cluster redshifts from maximum likelihood method are shown to be small (typically less that 0.01) over the whole redshift range with photometric redshift errors typical of those found in the Sloan survey. Inside the spherical radius corresponding to a galaxy overdensity of {Delta} = 200, we find the derived cluster richness {Lambda}{sub 200} a roughly linear indicator of its virial mass M{sub 200}, which well recovers the relation between total luminosity and cluster mass of the input simulation.

  17. 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.

  18. A complex-valued nonlinear neural adaptive filter with a gradient adaptive amplitude of the activation function.

    PubMed

    Hanna, Andrew I; Mandic, Danilo P

    2003-03-01

    A complex-valued nonlinear gradient descent (CNGD) learning algorithm for a simple finite impulse response (FIR) nonlinear neural adaptive filter with an adaptive amplitude of the complex activation function is proposed. This way the amplitude of the complex-valued analytic nonlinear activation function of a neuron in the learning algorithm is made gradient adaptive to give the complex-valued adaptive amplitude nonlinear gradient descent (CAANGD). Such an algorithm is beneficial when dealing with signals that have rich dynamical behavior. Simulations on the prediction of complex-valued coloured and nonlinear input signals show the gradient adaptive amplitude, CAANGD, outperforming the standard CNGD algorithm.

  19. 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.

  20. Extraction of a Weak Co-Channel Interfering Communication Signal Using Adaptive Filtering

    DTIC Science & Technology

    2015-03-01

    unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Conventional separation techniques such as filters cannot be used in a scenario where a...to achieve a reasonable error rate. 14. SUBJECT TERMS Adaptive filter, signal separation 15. NUMBER OF PAGES 71 16. PRICE CODE 17. SECURITY...INTENTIONALLY LEFT BLANK iv ABSTRACT Conventional separation techniques such as filters cannot be used in a scenario where a weak signal is embedded

  1. Classical sampling theorems in the context of multirate and polyphase digital filter bank structures

    NASA Astrophysics Data System (ADS)

    Vaidyanathan, P. P.; Liu, Vincent C.

    1988-09-01

    The recovery of a signal from so-called generalized samples is a problem of designing appropriate linear filters called reconstruction (or synthesis) filters. This relationship is reviewed and explored. Novel theorems for the subsampling of sequences are derived by direct use of the digital-filter-bank framework. These results are related to the theory of perfect reconstruction im maximally decimated digital-filter-bank systems. One of the theorems pertains to the subsampling of a sequence and its first few differences and its subsequent stable reconstruction at finite cost with no error. The reconstruction filters turn out to be multiplierless and of the FIR (finite impulse response) type. These ideas are extended to the case of two-dimensional signals by use of a Kronecker formalism. The subsampling of bandlimited sequences is also considered. A sequence x(n) with a Fourier transform vanishes for absolute value of omega greater than or equal to L pi/M, where L and M are integers with L less than M, can in principle be represented by reducing the data rate by the amount M/L. The digital polyphase framework is used as a convenient tool for the derivation as well as mechanization of the sampling theorems.

  2. 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

  3. 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).

  4. Feasability of adaptive vibration control of a space truss using modal filters and a neural network

    NASA Astrophysics Data System (ADS)

    Bosse, Albert; Fisher, Shalom; Shelley, Stuart J.; Lim, Tae W.

    1996-05-01

    An adaptive algorithm is proposed for the control of a large space truss structure which uses modal filters for independent modal space control and a simple neural network that provides an on-line system identification capability. The modal filters are computed off-line using measured frequency response functions and estimated pole values for the modes of interest, and provide a coordinate transformation that yields modal coordinates from physical response measurements. The time histories for the modal coordinates are then processed in real time by the neural network, which models a single degree of freedom system transfer function and provides estimates of modal parameters, namely, frequency, damping ratio and modal gain. The modal filters are used to implement independent modal space control on a 3.74 meter space truss using a single reaction-mass actuator and 32 accelerometers. The performance of the modal filter based controller is compared to that of a local rate feedback controller using the same actuator. The applicability of the adaptive filter to adaptive control is demonstrated by real time estimation of the modal parameters of the truss with and without control. Because the modal filter control gain can be adjusted to maintain a desired closed loop damping ratio, which is tracked by the adaptive filter, adaptive control of individual modes in a time-varying system is possible. The goal of this work is to field a control system which can maintain desired closed loop damping ratios for mode frequency variations as high as 10%.

  5. Construction of point process adaptive filter algorithms for neural systems using sequential Monte Carlo methods.

    PubMed

    Ergün, Ayla; Barbieri, Riccardo; Eden, Uri T; Wilson, Matthew A; Brown, Emery N

    2007-03-01

    The stochastic state point process filter (SSPPF) and steepest descent point process filter (SDPPF) are adaptive filter algorithms for state estimation from point process observations that have been used to track neural receptive field plasticity and to decode the representations of biological signals in ensemble neural spiking activity. The SSPPF and SDPPF are constructed using, respectively, Gaussian and steepest descent approximations to the standard Bayes and Chapman-Kolmogorov (BCK) system of filter equations. To extend these approaches for constructing point process adaptive filters, we develop sequential Monte Carlo (SMC) approximations to the BCK equations in which the SSPPF and SDPPF serve as the proposal densities. We term the two new SMC point process filters SMC-PPFs and SMC-PPFD, respectively. We illustrate the new filter algorithms by decoding the wind stimulus magnitude from simulated neural spiking activity in the cricket cercal system. The SMC-PPFs and SMC-PPFD provide more accurate state estimates at low number of particles than a conventional bootstrap SMC filter algorithm in which the state transition probability density is the proposal density. We also use the SMC-PPFs algorithm to track the temporal evolution of a spatial receptive field of a rat hippocampal neuron recorded while the animal foraged in an open environment. Our results suggest an approach for constructing point process adaptive filters using SMC methods.

  6. Real-time experimental demonstrations of software reconfigurable optical OFDM transceivers utilizing DSP-based digital orthogonal filters for SDN PONs.

    PubMed

    Duan, X; Giddings, R P; Bolea, M; Ling, Y; Cao, B; Mansoor, S; Tang, J M

    2014-08-11

    Real-time optical OFDM (OOFDM) transceivers with on-line software-controllable channel reconfigurability and transmission performance adaptability are experimentally demonstrated, for the first time, utilizing Hilbert-pair-based 32-tap digital orthogonal filters implemented in FPGAs. By making use of an 8-bit DAC/ADC operating at 2GS/s, an oversampling factor of 2 and an EML intensity modulator, the demonstrated RF conversion-free transceiver supports end-to-end real-time simultaneous adaptive transmissions, within a 1GHz signal spectrum region, of a 2.03Gb/s in-phase OOFDM channel and a 1.41Gb/s quadrature-phase OOFDM channel over a 25km SSMF IMDD system. In addition, detailed experimental explorations are also undertaken of key physical mechanisms limiting the maximum achievable transmission performance, impacts of transceiver's channel multiplexing/demultiplexing operations on the system BER performance, and the feasibility of utilizing adaptive modulation to combat impairments associated with low-complexity digital filter designs. Furthermore, experimental results indicate that the transceiver incorporating a fixed digital orthogonal filter DSP architecture can be made transparent to various signal modulation formats up to 64-QAM.

  7. Adaptive enhancement of magnetoencephalographic signals via multichannel filtering

    SciTech Connect

    Lewis, P.S.

    1989-01-01

    A time-varying spatial/temporal filter for enhancing multichannel magnetoencephalographic (MEG) recordings of evoked responses is described. This filter is based in projections derived from a combination of measured data and a priori models of the expected response. It produces estimates of the evoked fields in single trial measurements. These estimates can reduce the need for signal averaging in some situations. The filter uses the a priori model information to enhance responses where they exist, but avoids creating responses that do not exist. Examples are included of the filter's application to both MEG single trial data containing an auditory evoked field and control data with no evoked field. 5 refs., 7 figs.

  8. Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller.

    PubMed

    Lin, Chih-Min; Yang, Ming-Shu; Chao, Fei; Hu, Xiao-Min; Zhang, Jun

    2016-10-01

    This paper aims to propose an efficient network and applies it as an adaptive filter for the signal processing problems. An adaptive filter is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the CMAC. Due to the better ability of handling uncertainties, type-2 fuzzy sets can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so that the convergence of the filtering error can be guaranteed. In order to demonstrate the performance of the proposed adaptive T2FCMAC filter, it is tested in signal processing applications, including a nonlinear channel equalization system, a time-varying channel equalization system, and an adaptive noise cancellation system. The advantages of the proposed filter over the other adaptive filters are verified through simulations.

  9. Low-Cutoff, High-Pass Digital Filtering of Neural Signals

    NASA Technical Reports Server (NTRS)

    Mojarradi,Mohammad; Johnson, Travis; Ortiz, Monico; Cunningham, Thomas; Andersen, Richard

    2004-01-01

    The figure depicts the major functional blocks of a system, now undergoing development, for conditioning neural signals acquired by electrodes implanted in a brain. The overall functions to be performed by this system can be summarized as preamplification, multiplexing, digitization, and high-pass filtering. Other systems under development for recording neural signals typically contain resistor-capacitor analog low-pass filters characterized by cutoff frequencies in the vicinity of 100 Hz. In the application for which this system is being developed, there is a requirement for a cutoff frequency of 5 Hz. Because the resistors needed to obtain such a low cutoff frequency would be impractically large, it was decided to perform low-pass filtering by use of digital rather than analog circuitry. In addition, it was decided to timemultiplex the digitized signals from the multiple input channels into a single stream of data in a single output channel. The signal in each input channel is first processed by a preamplifier having a voltage gain of approximately 50. Embedded in each preamplifier is a low-pass anti-aliasing filter having a cutoff frequency of approximately 10 kHz. The anti-aliasing filters make it possible to couple the outputs of the preamplifiers to the input ports of a multiplexer. The output of the multiplexer is a single stream of time-multiplexed samples of analog signals. This stream is processed by a main differential amplifier, the output of which is sent to an analog-to-digital converter (ADC). The output of the ADC is sent to a digital signal processor (DSP).

  10. Adaptive optics in digital micromirror based confocal microscopy

    NASA Astrophysics Data System (ADS)

    Pozzi, P.; Wilding, D.; Soloviev, O.; Vdovin, G.; Verhaegen, M.

    2016-03-01

    This proceeding reports early results in the development of a new technique for adaptive optics in confocal microscopy. The term adaptive optics refers to the branch of optics in which an active element in the optical system is used to correct inhomogeneities in the media through which light propagates. In its most classical form, mostly used in astronomical imaging, adaptive optics is achieved through a closed loop in which the actuators of a deformable mirror are driven by a wavefront sensor. This approach is severely limited in fluorescence microscopy, as the use of a wavefront sensor requires the presence of a bright, point like source in the field of view, a condition rarely satisfied in microscopy samples. Previously reported approaches to adaptive optics in fluorescence microscopy are therefore limited to the inclusion of fluorescent microspheres in the sample, to use as bright stars for wavefront sensors, or time consuming sensorless optimization procedures, requiring several seconds of optimization before the acquisition of a single image. We propose an alternative approach to the problem, implementing sensorless adaptive optics in a Programmable array microscope. A programmable array microscope is a microscope based on a digital micromirror device, in which the single elements of the micromirror act both as point sources and pinholes.

  11. Noise-adaptive nonlinear diffusion filtering of MR images with spatially varying noise levels.

    PubMed

    Samsonov, Alexei A; Johnson, Chris R

    2004-10-01

    Anisotropic diffusion filtering is widely used for MR image enhancement. However, the anisotropic filter is nonoptimal for MR images with spatially varying noise levels, such as images reconstructed from sensitivity-encoded data and intensity inhomogeneity-corrected images. In this work, a new method for filtering MR images with spatially varying noise levels is presented. In the new method, a priori information regarding the image noise level spatial distribution is utilized for the local adjustment of the anisotropic diffusion filter. Our new method was validated and compared with the standard filter on simulated and real MRI data. The noise-adaptive method was demonstrated to outperform the standard anisotropic diffusion filter in both image error reduction and image signal-to-noise ratio (SNR) improvement. The method was also applied to inhomogeneity-corrected and sensitivity encoding (SENSE) images. The new filter was shown to improve segmentation of MR brain images with spatially varying noise levels.

  12. Measuring entropy in continuous and digitally filtered neural signals.

    PubMed

    French, Andrew S; Pfeiffer, Keram

    2011-03-15

    Neurons receive, process and transmit information using two distinct types of signaling methods: analog signals, such as graded changes in membrane potential, and binary digital action potentials. Quantitative estimates of information in neural signals have been based either on information capacity, which measures the theoretical maximum information flow through a communication channel, or on entropy, the amount of information that is required to describe or reproduce a signal. Measurement of entropy is straightforward for digital signals, including action potentials, but is more difficult for analog signals. This problem compromises attempts to estimate information in many neural signals, particularly when there is conversion between the two signal formats. We extended an established method for action potential entropy estimation to provide entropy estimation of analog signals. Our approach is based on context-independent data compression of analog signals, which we call analog compression. Although compression of analog signals is computationally intensive, we describe an algorithm that provides practical, efficient and reliable entropy estimation via analog compression. Implementation of the algorithm is demonstrated at two stages of sensory processing by a mechanoreceptor.

  13. 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.

  14. Adaptive two-pass median filter based on support vector machines for image restoration.

    PubMed

    Lin, Tzu-Chao; Yu, Pao-Ta

    2004-02-01

    In this letter, a novel adaptive filter, the adaptive two-pass median (ATM) filter based on support vector machines (SVMs), is proposed to preserve more image details while effectively suppressing impulse noise for image restoration. The proposed filter is composed of a noise decision maker and two-pass median filters. Our new approach basically uses an SVM impulse detector to judge whether the input pixel is noise. If a pixel is detected as a corrupted pixel, the noise-free reduction median filter will be triggered to replace it. Otherwise, it remains unchanged. Then, to improve the quality of the restored image, a decision impulse filter is put to work in the second-pass filtering procedure. As for the noise suppressing both fixed-valued and random-valued impulses without degrading the quality of the fine details, the results of our extensive experiments demonstrate that the proposed filter outperforms earlier median-based filters in the literature. Our new filter also provides excellent robustness at various percentages of impulse noise.

  15. Time-sequenced adaptive filtering using a modified P-vector algorithm

    NASA Astrophysics Data System (ADS)

    Williams, Robert L.

    1996-10-01

    An adaptive algorithm and two stage filter structure were developed for adaptive filtering of certain classes of signals that exhibit cyclostationary characteristics. The new modified P-vector algorithm (mPa) eliminates the need for a separate desired signal which is typically required by conventional adaptive algorithms. It is then implemented in a time-sequenced manner to counteract the nonstationary characteristics typically found in certain radar and bioelectromagnetic signals. Initial algorithm testing is performed on evoked responses generated by the visual cortex of the human brain with the objective, ultimately, to transition the results to radar signals. Each sample of the evoked response is modeled as the sum of three uncorrelated signal components, a time-varying mean (M), a noise component (N), and a random jitter component (Q). A two stage single channel time-sequenced adaptive filter structure was developed which improves convergence characteristics by de coupling the time-varying mean component from the `Q' and noise components in the first stage. The EEG statistics must be known a priori and are adaptively estimated from the pre stimulus data. The performance of the two stage mPa time-sequenced adaptive filter approaches the performance for the ideal case of an adaptive filter having a noiseless desired response.

  16. MobiDiC: Context Adaptive Digital Signage with Coupons

    NASA Astrophysics Data System (ADS)

    Müller, Jörg; Krüger, Antonio

    In this paper we present a field study of a digital signage system that measures audience response with coupons in order to enable context adaptivity. In the concept for context adaptivity, the signs sense their environment; decide which content to show, and then sense the audience reaction to the content shown. From this audience measurement, the strategies which content to show in which situation are refined. As one instantiation of audience measurement, we propose a novel simple couponing system, where customers can photograph the coupons at the signs. Thus, it can be measured whether customers really went to the shop. To investigate the feasibility of this approach, we implemented a prototype of 20 signs in the city center of Münster, Germany. During one year of deployment, we investigated usage of the system through interviews with shop owners and customers. Our experiences show that customer attention towards the signs is a major hurdle to overcome.

  17. General Principles of Digital Filtering and a Survey of Filters in Current Range Use

    DTIC Science & Technology

    1991-08-01

    purpose; they separate true data from errors which are added during the measurement process . Signal processing filters were originally circuits with...be applied; (3) in radar and theodolite data processing to give traie:tury estimates for position, velocity, and acceleration; (4) in satellite...trajectory determination; (5) in processing airplane flight test data; and (6) in reconstructing photographs or voices which have been transmitted

  18. Adaptive Low Dissipative High Order Filter Methods for Multiscale MHD Flows

    NASA Technical Reports Server (NTRS)

    Yee, H. C.; Sjoegreen, Bjoern

    2004-01-01

    Adaptive low-dissipative high order filter finite difference methods for long time wave propagation of shock/turbulence/combustion compressible viscous MHD flows has been constructed. Several variants of the filter approach that cater to different flow types are proposed. These filters provide a natural and efficient way for the minimization of the divergence of the magnetic field [divergence of B] numerical error in the sense that no standard divergence cleaning is required. For certain 2-D MHD test problems, divergence free preservation of the magnetic fields of these filter schemes has been achieved.

  19. Adaptive digital beamforming for a CDMA mobile communications payload

    NASA Technical Reports Server (NTRS)

    Munoz-Garcia, Samuel G.; Ruiz, Javier Benedicto

    1993-01-01

    In recent years, Spread-Spectrum Code Division Multiple Access (CDMA) has become a very popular access scheme for mobile communications due to a variety of reasons: excellent performance in multipath environments, high scope for frequency reuse, graceful degradation near saturation, etc. In this way, a CDMA system can support simultaneous digital communication among a large community of relatively uncoordinated users sharing a given frequency band. Nevertheless, there are also important problems associated with the use of CDMA. First, in a conventional CDMA scheme, the signature sequences of asynchronous users are not orthogonal and, as the number of active users increases, the self-noise generated by the mutual interference between users considerably degrades the performance, particularly in the return link. Furthermore, when there is a large disparity in received powers - due to differences in slant range or atmospheric attenuation - the non-zero cross-correlation between the signals gives rise to the so-called near-far problem. This leads to an inefficient utilization of the satellite resources and, consequently, to a drastic reduction in capacity. Several techniques were proposed to overcome this problem, such as Synchronized CDMA - in which the signature sequences of the different users are quasi-orthogonal - and power control. At the expense of increased network complexity and user coordination, these techniques enable the system capacity to be restored by equitably sharing the satellite resources among the users. An alternative solution is presented based upon the use of time-reference adaptive digital beamforming on board the satellite. This technique enables a high number of independently steered beams to be generated from a single phased array antenna, which automatically track the desired user signal and null the unwanted interference source. In order to use a time-reference adaptive antenna in a communications system, the main challenge is to obtain a

  20. Adaptive digital beamforming for a CDMA mobile communications payload

    NASA Astrophysics Data System (ADS)

    Munoz-Garcia, Samuel G.; Ruiz, Javier Benedicto

    In recent years, Spread-Spectrum Code Division Multiple Access (CDMA) has become a very popular access scheme for mobile communications due to a variety of reasons: excellent performance in multipath environments, high scope for frequency reuse, graceful degradation near saturation, etc. In this way, a CDMA system can support simultaneous digital communication among a large community of relatively uncoordinated users sharing a given frequency band. Nevertheless, there are also important problems associated with the use of CDMA. First, in a conventional CDMA scheme, the signature sequences of asynchronous users are not orthogonal and, as the number of active users increases, the self-noise generated by the mutual interference between users considerably degrades the performance, particularly in the return link. Furthermore, when there is a large disparity in received powers - due to differences in slant range or atmospheric attenuation - the non-zero cross-correlation between the signals gives rise to the so-called near-far problem. This leads to an inefficient utilization of the satellite resources and, consequently, to a drastic reduction in capacity. Several techniques were proposed to overcome this problem, such as Synchronized CDMA - in which the signature sequences of the different users are quasi-orthogonal - and power control. At the expense of increased network complexity and user coordination, these techniques enable the system capacity to be restored by equitably sharing the satellite resources among the users. An alternative solution is presented based upon the use of time-reference adaptive digital beamforming on board the satellite. This technique enables a high number of independently steered beams to be generated from a single phased array antenna, which automatically track the desired user signal and null the unwanted interference source. In order to use a time-reference adaptive antenna in a communications system, the main challenge is to obtain a

  1. 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.

  2. 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…

  3. Study on GPS attitude determination system aided INS using adaptive Kalman filter

    NASA Astrophysics Data System (ADS)

    Bian, Hongwei; Jin, Zhihua; Tian, Weifeng

    2005-10-01

    A marine INS/GPS (inertial navigation system/global positioning system) adaptive navigation system is presented in this paper. The GPS with two antennae providing vessel attitude is selected as the auxiliary system to fuse with INS. The Kalman filter is the most frequently used algorithm in the integrated navigation system, which is capable of estimating INS errors online based on the measured errors between INS and GPS. The conventional Kalman filter (CKF) assumes that the statistics of the noise of each sensor are given. As long as the noise distributions do not change, the Kalman filter will give the optimal estimation. However, the GPS receiver will be disturbed easily and thus temporally changing measurement noise will join into the outputs of GPS, which will lead to performance degradation of the Kalman filter. Many researchers introduce a fuzzy logic control method into innovation-based adaptive estimation Kalman filtering (IAE-AKF) algorithm, and accordingly propose various adaptive Kalman filters. However, how to design the fuzzy logic controller is a very complicated problem, which is still without a convincing solution. A novel IAE-AKF is proposed herein, which is based on the maximum likelihood criterion for the proper computation of the filter innovation covariance and hence of the filter gain. The approach is direct and simple without having to establish fuzzy inference rules. After having deduced the proposed IAE-AKF algorithm theoretically in detail, the approach is tested in the developed INS/GPS integrated marine navigation system. Real field test results show that the adaptive Kalman filter outperforms the CKF with higher accuracy and robustness. It is demonstrated that this proposed approach is a valid solution for the unknown changing measurement noise existing in the Kalman filter.

  4. Detection of signals by the digital integrate-and-dump filter with offset sampling

    NASA Technical Reports Server (NTRS)

    Sadr, R.; Hurd, W. J.

    1987-01-01

    The Integrate and Dump Filter (IDF) is used as a matched filter for the detection of signals in additive white Gaussian noise. The performance of the digital integrate and dump filter is evaluated. The case considered is when symbol times are known and the sampling clock is free running at a constant rate, i.e., the sampling clock is not phase locked to the symbol clock. Degradations in the output signal to noise ratio of the digital implementation due to sampling rate, sampling offset, and finite bandwidth, resulting from the anti-aliasing low pass prefilter, are computed and compared with those of the analog counterpart. It is shown that the digital IDF performs within 0.6 dB of the ideal analog IDF whenever the prefilter bandwidth exceeds four times the symbol rate and when sampling is performed at the Nyquist rate. The loss can be reduced to 0.3 dB by doubling the sampling rate, where 0.2 dB loss results from finite bandwidth and 0.1 dB results from the digital IDF.

  5. Dynamic optical tomographic imager with optimized digital lock-in filtering

    NASA Astrophysics Data System (ADS)

    Lasker, Joseph M.; Masciotti, James M.; Li, Yang; Fong, Chris; Hielscher, Andreas H.

    2007-07-01

    We describe a new dynamic optical tomography system that is, unlike currently available analog instrumentation, based on digital data-acquisition and filtering techniques. At the heart of this continuous wave instrument is a digital signal processor (DSP) that collects, collates, processes, and filters the digitized data set. A digital lock-in filter that has been designed for this particular application maximizes measurement fidelity. The synchronously-timed processes are controlled by a complex programmable logic device (CPLD) that is also used in conjunction with the DSP to orchestrate data flow. Real-time data rates as high as 140Hz can be achieved. The operation of the system is implemented through a graphical user interface designed with LabVIEW software, Performance analysis shows very low system noise (~600fW RMS noise equivalent power), excellent signal precision (<0.04% - 0.2%) and long-term system stability (<1% over 40 min). A large dynamic range (~195dB) accommodates a wide scope of measurement geometries and tissue types. First experiments on tissue phantoms show that dynamic behavior is accurately captured and spatial location can be correctly tracked using this system.

  6. Signal-to-noise ratio adaptive post-filtering method for intelligibility enhancement of telephone speech.

    PubMed

    Jokinen, Emma; Yrttiaho, Santeri; Pulakka, Hannu; Vainio, Martti; Alku, Paavo

    2012-12-01

    Post-filtering can be utilized to improve the quality and intelligibility of telephone speech. Previous studies have shown that energy reallocation with a high-pass type filter works effectively in improving the intelligibility of speech in difficult noise conditions. The present study introduces a signal-to-noise ratio adaptive post-filtering method that utilizes energy reallocation to transfer energy from the first formant to higher frequencies. The proposed method adapts to the level of the background noise so that, in favorable noise conditions, the post-filter has a flat frequency response and the effect of the post-filtering is increased as the level of the ambient noise increases. The performance of the proposed method is compared with a similar post-filtering algorithm and unprocessed speech in subjective listening tests which evaluate both intelligibility and listener preference. The results indicate that both of the post-filtering methods maintain the quality of speech in negligible noise conditions and are able to provide intelligibility improvement over unprocessed speech in adverse noise conditions. Furthermore, the proposed post-filtering algorithm performs better than the other post-filtering method under evaluation in moderate to difficult noise conditions, where intelligibility improvement is mostly required.

  7. The use of linear programming techniques to design optimal digital filters for pulse shaping and channel equalization

    NASA Technical Reports Server (NTRS)

    Houts, R. C.; Burlage, D. W.

    1972-01-01

    A time domain technique is developed to design finite-duration impulse response digital filters using linear programming. Two related applications of this technique in data transmission systems are considered. The first is the design of pulse shaping digital filters to generate or detect signaling waveforms transmitted over bandlimited channels that are assumed to have ideal low pass or bandpass characteristics. The second is the design of digital filters to be used as preset equalizers in cascade with channels that have known impulse response characteristics. Example designs are presented which illustrate that excellent waveforms can be generated with frequency-sampling filters and the ease with which digital transversal filters can be designed for preset equalization.

  8. 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.

  9. 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.

  10. Incrementing data quality of multi-frequency echograms using the Adaptive Wiener Filter (AWF) denoising algorithm

    NASA Astrophysics Data System (ADS)

    Peña, M.

    2016-10-01

    Achieving acceptable signal-to-noise ratio (SNR) can be difficult when working in sparsely populated waters and/or when species have low scattering such as fluid filled animals. The increasing use of higher frequencies and the study of deeper depths in fisheries acoustics, as well as the use of commercial vessels, is raising the need to employ good denoising algorithms. The use of a lower Sv threshold to remove noise or unwanted targets is not suitable in many cases and increases the relative background noise component in the echogram, demanding more effectiveness from denoising algorithms. The Adaptive Wiener Filter (AWF) denoising algorithm is presented in this study. The technique is based on the AWF commonly used in digital photography and video enhancement. The algorithm firstly increments the quality of the data with a variance-dependent smoothing, before estimating the noise level as the envelope of the Sv minima. The AWF denoising algorithm outperforms existing algorithms in the presence of gaussian, speckle and salt & pepper noise, although impulse noise needs to be previously removed. Cleaned echograms present homogenous echotraces with outlined edges.

  11. Noise impact of single-event upsets on an FPGA-based digital filter

    SciTech Connect

    Morgan, Keith S; Caffrey, Michael P; Graham, Paul S; Pratt, Brian H; Wirthlin, Michael J

    2009-01-01

    Field-programmable gate arrays are well-suited to DSP and digital communications applications. SRAM-based FPGAs, however, are susceptible to radiation-induced single-event upsets (SEUs) when deployed in space environments. These effects are often handled with the area and power-intensive TMR mitigation technique. This paper evaluates the effects of SEUs in the FPGA configuration memory as noise in a digital filter, showing that many SEUs in a digital communications system cause effects that could be considered noise rather than circuit failure. Since DSP and digital communications applications are designed to withstand certain types of noise, SEU mitigation techniques that are less costly than TMR may be applicable. This could result in large savings in area and power when implementing a reliable system. Our experiments show that, of the SEUs that affected the digital filter with a 20 dB SNR input signal, less than 14% caused an SNR loss of more than 1 dB at the output.

  12. The role of adaptive immunity as an ecological filter on the gut microbiota in zebrafish.

    PubMed

    Stagaman, Keaton; Burns, Adam R; Guillemin, Karen; Bohannan, Brendan Jm

    2017-03-17

    All animals live in intimate association with communities of microbes, collectively referred to as their microbiota. Certain host traits can influence which microbial taxa comprise the microbiota. One potentially important trait in vertebrate animals is the adaptive immune system, which has been hypothesized to act as an ecological filter, promoting the presence of some microbial taxa over others. Here we surveyed the intestinal microbiota of 68 wild-type zebrafish, with functional adaptive immunity, and 61 rag1(-) zebrafish, lacking functional B- and T-cell receptors, to test the role of adaptive immunity as an ecological filter on the intestinal microbiota. In addition, we tested the robustness of adaptive immunity's filtering effects to host-host interaction by comparing the microbiota of fish populations segregated by genotype to those containing both genotypes. The presence of adaptive immunity individualized the gut microbiota and decreased the contributions of neutral processes to gut microbiota assembly. Although mixing genotypes led to increased phylogenetic diversity in each, there was no significant effect of adaptive immunity on gut microbiota composition in either housing condition. Interestingly, the most robust effect on microbiota composition was co-housing within a tank. In all, these results suggest that adaptive immunity has a role as an ecological filter of the zebrafish gut microbiota, but it can be overwhelmed by other factors, including transmission of microbes among hosts.The ISME Journal advance online publication, 17 March 2017; doi:10.1038/ismej.2017.28.

  13. Photonic analog-to-digital converter using soliton self-frequency shift and interleaving spectral filters.

    PubMed

    Xu, Chris; Liu, Xiang

    2003-06-15

    We propose a novel ultrafast photonic analog-to-digital converter that uses the soliton self-frequency shift in an optical fiber as an optical power-to-frequency conversion mechanism and a set of interleaving spectral filters as the optical comparators. Our method does all the signal processing in the optical domain and requires binary receivers in only the electronic domain. In contrast to the usual exponential scaling, the simultaneous binary search architecture that we propose results in a flash analog-to-digital converter with remarkable linear scaling between the number of comparators and the number of bits resolved.

  14. Adaptive Kalman filtering methods for tracking GPS signals in high noise/high dynamic environments

    NASA Astrophysics Data System (ADS)

    Zuo, Qiyao; Yuan, Hong; Lin, Baojun

    2007-11-01

    GPS C/A signal tracking algorithms have been developed based on adaptive Kalman filtering theory. In the research, an adaptive Kalman filter is used to substitute for standard tracking loop filters. The goal is to improve estimation accuracy and tracking stabilization in high noise and high dynamic environments. The linear dynamics model and the measurements model are designed to estimate code phase, carrier phase, Doppler shift, and rate of change of Doppler shift. Two adaptive algorithms are applied to improve robustness and adaptive faculty of the tracking, one is Sage adaptive filtering approach and the other is strong tracking method. Both the new algorithms and the conventional tracking loop have been tested by using simulation data. In the simulation experiment, the highest jerk of the receiver is set to 10G m/s 3 with the lowest C/No 30dBHz. The results indicate that the Kalman filtering algorithms are more robust than the standard tracking loop, and performance of tracking loop using the algorithms is satisfactory in such extremely adverse circumstances.

  15. Chi-squared smoothed adaptive particle-filtering based prognosis

    NASA Astrophysics Data System (ADS)

    Ley, Christopher P.; Orchard, Marcos E.

    2017-01-01

    This paper presents a novel form of selecting the likelihood function of the standard sequential importance sampling/re-sampling particle filter (SIR-PF) with a combination of sliding window smoothing and chi-square statistic weighting, so as to: (a) increase the rate of convergence of a flexible state model with artificial evolution for online parameter learning (b) improve the performance of a particle-filter based prognosis algorithm. This is applied and tested with real data from oil total base number (TBN) measurements from three haul trucks. The oil data has high measurement uncertainty and an unknown phenomenological state model. Performance of the proposed algorithm is benchmarked against the standard form of SIR-PF estimation which utilises the Normal (Gaussian) likelihood function. Both implementations utilise the same particle filter based prognosis algorithm so as to provide a common comparison. A sensitivity analysis is also performed to further explore the effects of the combination of sliding window smoothing and chi-square statistic weighting to the SIR-PF.

  16. 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

  17. Digital adaptive controllers using second order models with transport lag

    NASA Technical Reports Server (NTRS)

    Joshi, S.; Kaufman, H.

    1975-01-01

    Design of a discrete optimal regulator requires the a priori knowledge of a mathematical model for the system of interest. Because a second-order model with transport lag is very amenable to control computations and because this type of model has been used previously to represent certain high order single input-single output processes, an adaptive controller was designed based upon adjustment of controls computed for such a model. An extended Kalman filter was utilized for tracking the model parameters which were subsequently used to update a set of optimal control gains. Favorable results were obtained in applying this procedure to the control of several examples including a ninth order nonlinear process.

  18. Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression.

    PubMed

    Riaz, Nadeem; Shanker, Piyush; Wiersma, Rodney; Gudmundsson, Olafur; Mao, Weihua; Widrow, Bernard; Xing, Lei

    2009-10-07

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

  19. Design of film-micro-cavity interleaver filters based on digital signal processing

    NASA Astrophysics Data System (ADS)

    Hua, Dong; Zhang, Juan

    2016-01-01

    Based on digital signal processing theory, a novel and simple method is proposed to design asymmetrical film-microcavity interleaver filters (FMCIF) with arbitrary duty cycles. The transmission spectrums obtained have the characteristics of high isolation, great rectangular degree and wide flat passband. Design examples of different duty cycles are given and the influence of some key parameters on the spectral performance is discussed. The proposed method is simpler and more efficient than existing methods.

  20. 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.

  1. Gear Fault Signal Detection based on an Adaptive Fractional Fourier Transform Filter

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaojun; Shao, Yimin; Zhen, Dong; Gu, Fengshou; Ball, Andrew

    2011-07-01

    Vibration-based fault diagnosis is widely used for gearbox monitoring. However, it often needs considerable effort to extract effective diagnostic feature signal from noisy vibration signals because of rich signal components contained in a complex gear transmission system. In this paper, an adaptive fractional Fourier transform filter is proposed to suppress noise in gear vibration signals and hence to highlight signal components originated from gear fault dynamic characteristics. The approach relies on the use of adaptive filters in the fractional Fourier transform domain with the optimised fractional transform order and the filter parameters, while the transform orders are selected when the signal have the highest energy gathering and the filter parameters are determined by evolutionary rules. The results from the simulation and experiments have verified the performance of the proposed algorithm in extracting the gear failure signal components from the noisy signals based on a multistage gearbox system.

  2. Two dimensional recursive digital filters for near real time image processing

    NASA Technical Reports Server (NTRS)

    Olson, D.; Sherrod, E.

    1980-01-01

    A program was designed toward the demonstration of the feasibility of using two dimensional recursive digital filters for subjective image processing applications that require rapid turn around. The concept of the use of a dedicated minicomputer for the processor for this application was demonstrated. The minicomputer used was the HP1000 series E with a RTE 2 disc operating system and 32K words of memory. A Grinnel 256 x 512 x 8 bit display system was used to display the images. Sample images were provided by NASA Goddard on a 800 BPI, 9 track tape. Four 512 x 512 images representing 4 spectral regions of the same scene were provided. These images were filtered with enhancement filters developed during this effort.

  3. Blind detection of median filtering in digital images: a difference domain based approach.

    PubMed

    Chen, Chenglong; Ni, Jiangqun; Huang, Jiwu

    2013-12-01

    Recently, the median filtering (MF) detector as a forensic tool for the recovery of images' processing history has attracted wide interest. This paper presents a novel method for the blind detection of MF in digital images. Following some strongly indicative analyses in the difference domain of images, we introduce two new feature sets that allow us to distinguish a median-filtered image from an untouched image or average-filtered one. The effectiveness of the proposed features is verified with evidence from exhaustive experiments on a large composite image database. Compared with prior arts, the proposed method achieves significant performance improvement in the case of low resolution and strong JPEG post-compression. In addition, it is demonstrated that our method is more robust against additive noise than other existing MF detectors. With analyses and extensive experimental researches presented in this paper, we hope that the proposed method will add a new tool to the arsenal of forensic analysts.

  4. Phase Response Design of Recursive All-Pass Digital Filters Using a Modified PSO Algorithm.

    PubMed

    Chang, Wei-Der

    2015-01-01

    This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to improve the searching ability. In the proposed method, all of the designed filter coefficients are firstly collected to be a parameter vector and this vector is regarded as a particle of the algorithm. The MPSO with a modified velocity formula will force all particles into moving toward the optimal or near optimal solution by minimizing some defined objective function of the optimization problem. To show the effectiveness of the proposed method, two different kinds of linear phase response design examples are illustrated and the general PSO algorithm is compared as well. The obtained results show that the MPSO is superior to the general PSO for the phase response design of digital recursive all-pass filter.

  5. Phase Response Design of Recursive All-Pass Digital Filters Using a Modified PSO Algorithm

    PubMed Central

    Chang, Wei-Der

    2015-01-01

    This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to improve the searching ability. In the proposed method, all of the designed filter coefficients are firstly collected to be a parameter vector and this vector is regarded as a particle of the algorithm. The MPSO with a modified velocity formula will force all particles into moving toward the optimal or near optimal solution by minimizing some defined objective function of the optimization problem. To show the effectiveness of the proposed method, two different kinds of linear phase response design examples are illustrated and the general PSO algorithm is compared as well. The obtained results show that the MPSO is superior to the general PSO for the phase response design of digital recursive all-pass filter. PMID:26366168

  6. Online digital filter and QRS detector applicable in low resource ECG monitoring systems.

    PubMed

    Tabakov, Serafim; Iliev, Ivo; Krasteva, Vessela

    2008-11-01

    The present work describes fast computation methods for real-time digital filtration and QRS detection, both applicable in autonomous personal ECG systems for long-term monitoring. Since such devices work under considerable artifacts of intensive body and electrode movements, the input filtering should provide high-quality ECG signals supporting the accurate ECG interpretation. In this respect, we propose a combined high-pass and power-line interference rejection filter, introducing the simple principle of averaging of samples with a predefined distance between them. In our implementation (sampling frequency of 250 Hz), we applied averaging over 17 samples distanced by 10 samples (Filter10x17), thus realizing a comb filter with a zero at 50 Hz and high-pass cut-off at 1.1 Hz. Filter10x17 affords very fast filtering procedure at the price of minimal computing resources. Another benefit concerns the small ECG distortions introduced by the filter, providing its powerful application in the preprocessing module of diagnostic systems analyzing the ECG morphology. Filter10x17 does not attenuate the QRS amplitude, or introduce significant ST-segment elevation/depression. The filter output produces a constant error, leading to uniform shifting of the entire P-QRS-T segment toward about 5% of the R-peak amplitude. Tests with standardized ECG signals proved that Filter10x17 is capable to remove very strong baseline wanderings, and to fully suppress 50 Hz interferences. By changing the number of the averaged samples and the distance between them, a filter design with different cut-off and zero frequency could be easily achieved. The real-time QRS detector is designed with simplified computations over single channel, low-resolution ECGs. It relies on simple evaluations of amplitudes and slopes, including history of their mean values estimated over the preceding beats, smart adjustable thresholds, as well as linear logical rules for identification of the R-peaks in real

  7. Image pre-filtering for measurement error reduction in digital image correlation

    NASA Astrophysics Data System (ADS)

    Zhou, Yihao; Sun, Chen; Song, Yuntao; Chen, Jubing

    2015-02-01

    In digital image correlation, the sub-pixel intensity interpolation causes a systematic error in the measured displacements. The error increases toward high-frequency component of the speckle pattern. In practice, a captured image is usually corrupted by additive white noise. The noise introduces additional energy in the high frequencies and therefore raises the systematic error. Meanwhile, the noise also elevates the random error which increases with the noise power. In order to reduce the systematic error and the random error of the measurements, we apply a pre-filtering to the images prior to the correlation so that the high-frequency contents are suppressed. Two spatial-domain filters (binomial and Gaussian) and two frequency-domain filters (Butterworth and Wiener) are tested on speckle images undergoing both simulated and real-world translations. By evaluating the errors of the various combinations of speckle patterns, interpolators, noise levels, and filter configurations, we come to the following conclusions. All the four filters are able to reduce the systematic error. Meanwhile, the random error can also be reduced if the signal power is mainly distributed around DC. For high-frequency speckle patterns, the low-pass filters (binomial, Gaussian and Butterworth) slightly increase the random error and Butterworth filter produces the lowest random error among them. By using Wiener filter with over-estimated noise power, the random error can be reduced but the resultant systematic error is higher than that of low-pass filters. In general, Butterworth filter is recommended for error reduction due to its flexibility of passband selection and maximal preservation of the allowed frequencies. Binomial filter enables efficient implementation and thus becomes a good option if computational cost is a critical issue. While used together with pre-filtering, B-spline interpolator produces lower systematic error than bicubic interpolator and similar level of the random

  8. 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.

  9. Fourier transform digital holographic adaptive optics imaging system

    PubMed Central

    Liu, Changgeng; Yu, Xiao; Kim, Myung K.

    2013-01-01

    A Fourier transform digital holographic adaptive optics imaging system and its basic principles are proposed. The CCD is put at the exact Fourier transform plane of the pupil of the eye lens. The spherical curvature introduced by the optics except the eye lens itself is eliminated. The CCD is also at image plane of the target. The point-spread function of the system is directly recorded, making it easier to determine the correct guide-star hologram. Also, the light signal will be stronger at the CCD, especially for phase-aberration sensing. Numerical propagation is avoided. The sensor aperture has nothing to do with the resolution and the possibility of using low coherence or incoherent illumination is opened. The system becomes more efficient and flexible. Although it is intended for ophthalmic use, it also shows potential application in microscopy. The robustness and feasibility of this compact system are demonstrated by simulations and experiments using scattering objects. PMID:23262541

  10. Effect of filter on average glandular dose and image quality in digital mammography

    NASA Astrophysics Data System (ADS)

    Songsaeng, C.; Krisanachinda, A.; Theerakul, K.

    2016-03-01

    To determine the average glandular dose and entrance surface air kerma in both phantoms and patients to assess image quality for different target-filters (W/Rh and W/Ag) in digital mammography system. The compressed breast thickness, compression force, average glandular dose, entrance surface air kerma, peak kilovoltage and tube current time were recorded and compared between W/Rh and W/Ag target filter. The CNR and the figure of merit were used to determine the effect of target filter on image quality. The mean AGD of the W/Rh target filter was 1.75 mGy, the mean ESAK was 6.67 mGy, the mean CBT was 54.1 mm, the mean CF was 14 1bs. The mean AGD of W/Ag target filter was 2.7 mGy, the mean ESAK was 12.6 mGy, the mean CBT was 75.5 mm, the mean CF was 15 1bs. In phantom study, the AGD was 1.2 mGy at 4 cm, 3.3 mGy at 6 cm and 3.83 mGy at 7 cm thickness. The FOM was 24.6, CNR was 9.02 at thickness 6 cm. The FOM was 18.4, CNR was 8.6 at thickness 7 cm. The AGD from Digital Mammogram system with W/Rh of thinner CBT was lower than the AGD from W/Ag target filter.

  11. Design of minimum multiplier fractional order differentiator based on lattice wave digital filter.

    PubMed

    Barsainya, Richa; Rawat, Tarun Kumar; Kumar, Manjeet

    2017-01-01

    In this paper, a novel design of fractional order differentiator (FOD) based on lattice wave digital filter (LWDF) is proposed which requires minimum number of multiplier for its structural realization. Firstly, the FOD design problem is formulated as an optimization problem using the transfer function of lattice wave digital filter. Then, three optimization algorithms, namely, genetic algorithm (GA), particle swarm optimization (PSO) and cuckoo search algorithm (CSA) are applied to determine the optimal LWDF coefficients. The realization of FOD using LWD structure increases the design accuracy, as only N number of coefficients are to be optimized for Nth order FOD. Finally, two design examples of 3rd and 5th order lattice wave digital fractional order differentiator (LWDFOD) are demonstrated to justify the design accuracy. The performance analysis of the proposed design is carried out based on magnitude response, absolute magnitude error (dB), root mean square (RMS) magnitude error, arithmetic complexity, convergence profile and computation time. Simulation results are attained to show the comparison of the proposed LWDFOD with the published works and it is observed that an improvement of 29% is obtained in the proposed design. The proposed LWDFOD approximates the ideal FOD and surpasses the existing ones reasonably well in mid and high frequency range, thereby making the proposed LWDFOD a promising technique for the design of digital FODs.

  12. Recovering fluorescent spectra with an RGB digital camera and color filters using different matrix factorizations.

    PubMed

    Nieves, Juan L; Valero, Eva M; Hernández-Andrés, Javier; Romero, Javier

    2007-07-01

    The aim of a multispectral system is to recover a spectral function at each image pixel, but when a scene is digitally imaged under a light of unknown spectral power distribution (SPD), the image pixels give incomplete information about the spectral reflectances of objects in the scene. We have analyzed how accurately the spectra of artificial fluorescent light sources can be recovered with a digital CCD camera. The red-green-blue (RGB) sensor outputs are modified by the use of successive cutoff color filters. Four algorithms for simplifying the spectra datasets are used: nonnegative matrix factorization (NMF), independent component analysis (ICA), a direct pseudoinverse method, and principal component analysis (PCA). The algorithms are tested using both simulated data and data from a real RGB digital camera. The methods are compared in terms of the minimum rank of factorization and the number of sensors required to derive acceptable spectral and colorimetric SPD estimations; the PCA results are also given for the sake of comparison. The results show that all the algorithms surpass the PCA when a reduced number of sensors is used. The experimental results suggest a significant loss of quality when more than one color filter is used, which agrees with the previous results for reflectances. Nevertheless, an RGB digital camera with or without a prefilter is found to provide good spectral and colorimetric recovery of indoor fluorescent lighting and can be used for color correction without the need of a telespectroradiometer.

  13. Robust adaptive digital watermark for still images using hybrid modulation

    NASA Astrophysics Data System (ADS)

    Alturki, Faisal T.; Mersereau, Russell M.

    2001-08-01

    A digital watermark is a short sequence of information containing an owner identity or copyright information embedded in a way that is difficult to erase. We present a new oblivious digital watermarking technique for copyright protection of still images. The technique embeds the watermark in a subset of low to mid frequency coefficients. A key is used to randomly select a group of coefficients from that subset for watermark embedding. The original phases of the selected coefficients are removed and the new phases are set in accordance with the embedded watermark. Since the coefficients are selected at random, the powers of the low magnitude coefficients are increased to enhance their immunity against image attacks. To cope with small geometric attacks, a replica of the watermark is embedded by dividing the image into sub-blocks and taking the DCT of these blocks. The watermark is embedded in the DC component of some of these blocks selected in an adaptive way using quantization techniques. A major advantage of this technique is its complete suppression of the noise due to the host image. The robustness of the technique to a number of standard image processing attacks is demonstrated using the criteria of the latest Stirmark benchmark test.

  14. The prediction of EEG signals using a feedback-structured adaptive rational function filter.

    PubMed

    Kim, H S; Kim, T S; Choi, Y H; Park, S H

    2000-08-01

    In this article, we present a feedback-structured adaptive rational function filter based on a recursive modified Gram-Schmidt algorithm and apply it to the prediction of an EEG signal that has nonlinear and nonstationary characteristics. For the evaluation of the prediction performance, the proposed filter is compared with other methods, where a single-step prediction and a multi-step prediction are considered for a short-term prediction, and the prediction performance is assessed in normalized mean square error. The experimental results show that the proposed filter shows better performance than other methods considered for the short-term prediction of EEG signals.

  15. Fault estimation of satellite reaction wheels using covariance based adaptive unscented Kalman filter

    NASA Astrophysics Data System (ADS)

    Rahimi, Afshin; Kumar, Krishna Dev; Alighanbari, Hekmat

    2017-05-01

    Reaction wheels, as one of the most commonly used actuators in satellite attitude control systems, are prone to malfunction which could lead to catastrophic failures. Such malfunctions can be detected and addressed in time if proper analytical redundancy algorithms such as parameter estimation and control reconfiguration are employed. Major challenges in parameter estimation include speed and accuracy of the employed algorithm. This paper presents a new approach for improving parameter estimation with adaptive unscented Kalman filter. The enhancement in tracking speed of unscented Kalman filter is achieved by systematically adapting the covariance matrix to the faulty estimates using innovation and residual sequences combined with an adaptive fault annunciation scheme. The proposed approach provides the filter with the advantage of tracking sudden changes in the system non-measurable parameters accurately. Results showed successful detection of reaction wheel malfunctions without requiring a priori knowledge about system performance in the presence of abrupt, transient, intermittent, and incipient faults. Furthermore, the proposed approach resulted in superior filter performance with less mean squared errors for residuals compared to generic and adaptive unscented Kalman filters, and thus, it can be a promising method for the development of fail-safe satellites.

  16. 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.

  17. 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.

  18. Steganalysis of content-adaptive JPEG steganography based on Gauss partial derivative filter bank

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Liu, Fenlin; Yang, Chunfang; Luo, Xiangyang; Song, Xiaofeng; Lu, Jicang

    2017-01-01

    A steganalysis feature extraction method based on Gauss partial derivative filter bank is proposed in this paper to improve the detection performance for content-adaptive JPEG steganography. Considering that the embedding changes of content-adaptive steganographic schemes are performed in the texture and edge regions, the proposed method generates filtered images comprising rich texture and edge information using Gauss partial derivative filter bank, and histograms of absolute values of filtered subimages are extracted as steganalysis features. Gauss partial derivative filter bank can represent texture and edge information in multiple orientations with less computation load than conventional methods and prevent redundancy in different filtered images. These two properties are beneficial in the extraction of low-complexity sensitive features. The results of experiments conducted on three selected modern JPEG steganographic schemes-uniform embedding distortion, JPEG universal wavelet relative distortion, and side-informed UNIWARD-indicate that the proposed feature set is superior to the prior art feature sets-discrete cosine transform residual, phase aware rich model, and Gabor filter residual.

  19. Robust adaptive extended Kalman filtering for real time MR-thermometry guided HIFU interventions.

    PubMed

    Roujol, Sébastien; de Senneville, Baudouin Denis; Hey, Silke; Moonen, Chrit; Ries, Mario

    2012-03-01

    Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.

  20. 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.

  1. Adaptive Collaborative Gaussian Mixture Probability Hypothesis Density Filter for Multi-Target Tracking.

    PubMed

    Yang, Feng; Wang, Yongqi; Chen, Hao; Zhang, Pengyan; Liang, Yan

    2016-10-11

    In this paper, an adaptive collaborative Gaussian Mixture Probability Hypothesis Density (ACo-GMPHD) filter is proposed for multi-target tracking with automatic track extraction. Based on the evolutionary difference between the persistent targets and the birth targets, the measurements are adaptively partitioned into two parts, persistent and birth measurement sets, for updating the persistent and birth target Probability Hypothesis Density, respectively. Furthermore, the collaboration mechanism of multiple probability hypothesis density (PHDs) is established, where tracks can be automatically extracted. Simulation results reveal that the proposed filter yields considerable computational savings in processing requirements and significant improvement in tracking accuracy.

  2. Performance Analysis of Adaptive Volterra Filters in the Finite-Alphabet Input Case

    NASA Astrophysics Data System (ADS)

    Besbes, Hichem; Jaïdane, Mériem; Ezzine, Jelel

    2004-12-01

    This paper deals with the analysis of adaptive Volterra filters, driven by the LMS algorithm, in the finite-alphabet inputs case. A tailored approach for the input context is presented and used to analyze the behavior of this nonlinear adaptive filter. Complete and rigorous mean square analysis is provided without any constraining independence assumption. Exact transient and steady-state performances expressed in terms of critical step size, rate of transient decrease, optimal step size, excess mean square error in stationary mode, and tracking nonstationarities are deduced.

  3. Segmentation and tracking of the electro-encephalogram signal using an adaptive recursive bandpass filter.

    PubMed

    Gharieb, R R; Cichocki, A

    2001-03-01

    An adaptive filtering approach for the segmentation and tracking of electro-encephalogram (EEG) signal waves is described. In this approach, an adaptive recursive bandpass filter is employed for estimating and tracking the centre frequency associated with each EEG wave. The main advantage inherent in the approach is that the employed adaptive filter has only one unknown coefficient to be updated. This coefficient, having an absolute value less than 1, represents an efficient distinct feature for each EEG specific wave, and its time function reflects the non-stationarity behaviour of the EEG signal. Therefore the proposed approach is simple and accurate in comparison with existing multivariate adaptive approaches. The approach is examined using extensive computer simulations. It is applied to computer-generated EEG signals composed of different waves. The adaptive filter coefficient (i.e. the segmentation parameter) is -0.492 for the delta wave, -0.360 for the theta wave, -0.191 for the alpha wave, -0.027 for the sigma wave, 0.138 for the beta wave and 0.605 for the gamma wave. This implies that the segmentation parameter increases with the increase in the centre frequency of the EEG waves, which provides fast on-line information about the behaviour of the EEG signal. The approach is also applied to real-world EEG data for the detection of sleep spindles.

  4. Statistical properties of filtered pseudorandom digital sequences formed from the sum of maximum-length sequences

    NASA Technical Reports Server (NTRS)

    Wallace, G. R.; Weathers, G. D.; Graf, E. R.

    1973-01-01

    The statistics of filtered pseudorandom digital sequences called hybrid-sum sequences, formed from the modulo-two sum of several maximum-length sequences, are analyzed. The results indicate that a relation exists between the statistics of the filtered sequence and the characteristic polynomials of the component maximum length sequences. An analysis procedure is developed for identifying a large group of sequences with good statistical properties for applications requiring the generation of analog pseudorandom noise. By use of the analysis approach, the filtering process is approximated by the convolution of the sequence with a sum of unit step functions. A parameter reflecting the overall statistical properties of filtered pseudorandom sequences is derived. This parameter is called the statistical quality factor. A computer algorithm to calculate the statistical quality factor for the filtered sequences is presented, and the results for two examples of sequence combinations are included. The analysis reveals that the statistics of the signals generated with the hybrid-sum generator are potentially superior to the statistics of signals generated with maximum-length generators. Furthermore, fewer calculations are required to evaluate the statistics of a large group of hybrid-sum generators than are required to evaluate the statistics of the same size group of approximately equivalent maximum-length sequences.

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

    PubMed

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

    2015-01-26

    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.

  6. 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

  7. Interference Suppression for Spread Spectrum Signals Using Adaptive Beamforming and Adaptive Temporal Filter

    DTIC Science & Technology

    1996-12-01

    algorithms for obtaining rapid convergence of the tap weights of a transversal filter to their optimum settings ( Godard , 1974). This algorithm is...1366, Dec. 1989. 10. Godard , D. N. (1974) "Channel equalization using a Kalman filter for fast data transmission," IBM K. Res. Dev., vol. 18, pp. 267

  8. A New Synchronized Miniature Rubidium Oscillator with an Auto-Adaptive Disciplining Filter

    DTIC Science & Technology

    2001-11-01

    33rd Annual Precise Time and Time Interval (PTTI) Meeting A NEW SYNCHRONIZED MINIATURE RUBIDIUM DISCIPLINING FILTER OSCILLATOR WITH AN AUTO...ADAPTIVE Pascal Rochat and Bernard Leuenberger Temex Neuchfitel Time SA, Switzerland Abstract A new rubidium line (SRO) integrating timing functions and... time interval measurements was developed using an auto-adaptive disciplining algorithm. This led to an ultra-stable time & frequency machine usable

  9. Development of a digital method for neutron/gamma-ray discrimination based on matched filtering

    NASA Astrophysics Data System (ADS)

    Korolczuk, S.; Linczuk, M.; Romaniuk, R.; Zychor, I.

    2016-09-01

    Neutron/gamma-ray discrimination is crucial for measurements with detectors sensitive to both neutron and gamma-ray radiation. Different techniques to discriminate between neutrons and gamma-rays based on pulse shape analysis are widely used in many applications, e.g., homeland security, radiation dosimetry, environmental monitoring, fusion experiments, nuclear spectroscopy. A common requirement is to improve a radiation detection level with a high detection reliability. Modern electronic components, such as high speed analog to digital converters and powerful programmable digital circuits for signal processing, allow us to develop a fully digital measurement system. With this solution it is possible to optimize digital signal processing algorithms without changing any electronic components in an acquisition signal path. We report on results obtained with a digital acquisition system DNG@NCBJ designed at the National Centre for Nuclear Research. A 2'' × 2'' EJ309 liquid scintillator was used to register mixed neutron and gamma-ray radiation from PuBe sources. A dedicated algorithm for pulse shape discrimination, based on real-time filtering, was developed and implemented in hardware.

  10. An adaptive switching filter based on approximated variance for detection of impulse noise from color images.

    PubMed

    Pritamdas, K; Singh, Kh Manglem; Singh, L Lolitkumar

    2016-01-01

    A new adaptive switching algorithm is presented where two adaptive filters are switched correspondingly for lower and higher noise ratio of the image. An adaptive center weighted vector median filter is used for the lower noise ratio whereas for higher noise ratio the noisy pixels are detected based on the comparison of the difference between the mean of the vector pixels in the window and the approximated variance of the vector pixels in the window. Then the window comprising the detected noisy pixel is further considered where the pixels are given exponential weights according to their similarity to the other neighboring pixels, spatially and radio metrically. The noisy pixels are then replaced by the weighted average of the pixels within the window. The filter is able to preserve higher signal content in the higher noise ratio as compared to other robust filters in comparison. With a little high in computational complexity, this technique performs well both in lower and higher noise ratios. Simulation results on various RGB images show that the proposed algorithm outperforms many other existing nonlinear filters in terms of preservation of edges and fine details.

  11. 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.

  12. 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.

  13. Improved Data Preprocessing Algorithm for Time-Domain Induced Polarization Method with Digital Notch Filter

    NASA Astrophysics Data System (ADS)

    Ge, Shuang-Chao; Deng, Ming; Chen, Kai; Li, Bin; Li, Yuan

    2016-12-01

    Time-domain induced polarization (TDIP) measurement is seriously affected by power line interference and other field noise. Moreover, existing TDIP instruments generally output only the apparent chargeability, without providing complete secondary field information. To increase the robustness of TDIP method against interference and obtain more detailed secondary field information, an improved dataprocessing algorithm is proposed here. This method includes an efficient digital notch filter which can effectively eliminate all the main components of the power line interference. Hardware model of this filter was constructed and Vhsic Hardware Description Language code for it was generated using Digital Signal Processor Builder. In addition, a time-location method was proposed to extract secondary field information in case of unexpected data loss or failure of the synchronous technologies. Finally, the validity and accuracy of the method and the notch filter were verified by using the Cole-Cole model implemented by SIMULINK software. Moreover, indoor and field tests confirmed the application effect of the algorithm in the fieldwork.

  14. 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.

  15. Speckle reduction in ultrasound medical images using adaptive filter based on second order statistics.

    PubMed

    Thakur, A; Anand, R S

    2007-01-01

    This article discusses an adaptive filtering technique for reducing speckle using second order statistics of the speckle pattern in ultrasound medical images. Several region-based adaptive filter techniques have been developed for speckle noise suppression, but there are no specific criteria for selecting the region growing size in the post processing of the filter. The size appropriate for one local region may not be appropriate for other regions. Selection of the correct region size involves a trade-off between speckle reduction and edge preservation. Generally, a large region size is used to smooth speckle and a small size to preserve the edges into an image. In this paper, a smoothing procedure combines the first order statistics of speckle for the homogeneity test and second order statistics for selection of filters and desired region growth. Grey level co-occurrence matrix (GLCM) is calculated for every region during the region contraction and region growing for second order statistics. Further, these GLCM features determine the appropriate filter for the region smoothing. The performance of this approach is compared with the aggressive region-growing filter (ARGF) using edge preservation and speckle reduction tests. The processed image results show that the proposed method effectively reduces speckle noise and preserves edge details.

  16. Development of an adaptive bilateral filter for evaluating color image difference

    NASA Astrophysics Data System (ADS)

    Wang, Zhaohui; Hardeberg, Jon Yngve

    2012-04-01

    Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

  17. 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.

  18. An optimized locally adaptive non-local means denoising filter for cryo-electron microscopy data.

    PubMed

    Wei, Dai-Yu; Yin, Chang-Cheng

    2010-12-01

    Cryo-electron microscopy (cryo-EM) now plays an important role in structural analysis of macromolecular complexes, organelles and cells. However, the cryo-EM images obtained close to focus and under low dose conditions have a very high level of noise and a very low contrast, which hinders high-resolution structural analysis. Here, an optimized locally adaptive non-local (LANL) means filter, which can preserve signal details and simultaneously significantly suppress noise for cryo-EM data, is presented. This filter takes advantage of a wide range of pixels to estimate the denoised pixel values instead of the traditional filter that only uses pixels in the local neighborhood. The filter performed well on simulated data and showed promising results on raw cryo-EM images and tomograms. The predominant advantage of this optimized LANL-means filter is the structural signal and the background are clearly distinguishable. This locally adaptive non-local means filter may become a useful tool in the analysis of cryo-EM data, such as automatic particle picking, extracting structural features and segmentation of tomograms.

  19. 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.

  20. Adaptive Filter Techniques for Optical Beam Jitter Control and Target Tracking

    DTIC Science & Technology

    2008-12-01

    Analysis ......................................................51 5. Standard Deviation of Beam Position Error ...................................51 6...Organization of Analysis ...................................................................51 B. FEEDFORWARD ADAPTIVE FILTERS USING MULTIPLE...actuator (loud speaker or CFSM) before its effect reaches the error sensor. In ANC lingo , y(t) must first pass through the secondary plant dynamics of the

  1. Evaluation Of Digital Unsharp-Mask Filtering For The Detection Of Subtle Mammographic Microcalcifications

    NASA Astrophysics Data System (ADS)

    Chan, Heang-Ping; Vyborny, Carl J.; MacMahon, Heber; Metz, Charles E.; Doi, Kunio; Sickles, Edward A.

    1986-06-01

    We have conducted a study to assess the effects of digitization and unsharp-mask filtering on the ability of observers to detect subtle microcalcifications in mammograms. Thirty-two conventional screen-film mammograms were selected from patient files by two experienced mammographers. Twelve of the mammograms contained a suspicious cluster of microcalcifications in patients who subsequently underwent biopsy. Twenty of the mammograms were normal cases which were initially interpreted as being free of clustered microcalcifications and did not demonstrate such on careful review. The mammograms were digitized with a high-quality Fuji image processing/simulation system. The system consists of two drum scanners with which an original radiograph can be digitized, processed by a minicomputer, and reconstituted on film. In this study, we employed a sampling aperture of 0.1 mm X 0.1 mm and a sampling distance of 0.1 mm. The density range from 0.2 to 2.75 was digitized to 1024 grey levels per pixel. The digitized images were printed on a single emulsion film with a display aperture having the same size as the sampling aperture. The system was carefully calibrated so that the density and contrast of a digitized image were closely matched to those of the original radiograph. Initially, we evaluated the effects of the weighting factor and the mask size of a unsharp-mask filter on the appearance of mammograms for various types of breasts. Subjective visual comparisons suggested that a mask size of 91 X 91 pixels (9.1 mm X 9.1 mm) enhances the visibility of microcalcifications without excessively increasing the high-frequency noise. Further, a density-dependent weighting factor that increases linearly from 1.5 to 3.0 in the density range of 0.2 to 2.5 enhances the contrast of microcalcifications without introducing many potentially confusing artifacts in the low-density areas. An unsharp-mask filter with these parameters was used to process the digitized mammograms. We conducted

  2. 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.

  3. Impact of Rician adapted Non-Local Means filtering on HARDI.

    PubMed

    Descoteaux, Maxime; Wiest-Daesslé, Nicolas; Prima, Sylvain; Barillot, Christian; Deriche, Rachid

    2008-01-01

    In this paper we study the impact of denoising the raw high angular resolution diffusion imaging (HARDI) data with the Non-Local Means filter adapted to Rician noise (NLMr). We first show that NLMr filtering improves robustness of apparent diffusion coefficient (ADC) and orientation distribution function (ODF) reconstructions from synthetic HARDI datasets. Our results suggest that the NLMr filtering improve the quality of anisotropy maps computed from ADC and ODF and improve the coherence of q-ball ODFs with the underlying anatomy while not degrading angular resolution. These results are shown on a biological phantom with known ground truth and on a real human brain dataset. Most importantly, we show that multiple measurements of diffusion-weighted (DW) images and averaging these images along each direction can be avoided because NLMr filtering of the individual DW images produces better quality generalized fractional anisotropy maps and more accurate ODF fields than when computed from the averaged DW datasets.

  4. Common spatial pattern patches - an optimized filter ensemble for adaptive brain-computer interfaces.

    PubMed

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

    2010-01-01

    Laplacian filters are commonly used in Brain Computer Interfacing (BCI). When only data from few channels are available, or when, like at the beginning of an experiment, no previous data from the same user is available complex features cannot be used. In this case band power features calculated from Laplacian filtered channels represents an easy, robust and general feature to control a BCI, since its calculation does not involve any class information. For the same reason, the performance obtained with Laplacian features is poor in comparison to subject-specific optimized spatial filters, such as Common Spatial Patterns (CSP) analysis, which, on the other hand, can be used just in a later phase of the experiment, since they require a considerable amount of training data in order to enroll a stable and good performance. This drawback is particularly evident in case of poor performing BCI users, whose data is highly non-stationary and contains little class relevant information. Therefore, Laplacian filtering is preferred to CSP, e.g., in the initial period of co-adaptive calibration, a novel BCI paradigm designed to alleviate the problem of BCI illiteracy. In fact, in the co-adaptive calibration design the experiment starts with a subject-independent classifier and simple features are needed in order to obtain a fast adaptation of the classifier to the newly acquired user's data. Here, the use of an ensemble of local CSP patches (CSPP) is proposed, which can be considered as a compromise between Laplacians and CSP: CSPP needs less data and channels than CSP, while being superior to Laplacian filtering. This property is shown to be particularly useful for the co-adaptive calibration design and is demonstrated on off-line data from a previous co-adaptive BCI study.

  5. Static and Dynamic Characteristics of DC-DC Converter Using a Digital Filter

    NASA Astrophysics Data System (ADS)

    Kurokawa, Fujio; Okamatsu, Masashi

    This paper presents the regulation and dynamic characteristics of the dc-dc converter with digital PID control, the minimum phase FIR filter or the IIR filter, and then the design criterion to improve the dynamic characteristics is discussed. As a result, it is clarified that the DC-DC converter using the IIR filter method has superior performance characteristics. The regulation range is within 1.3%, the undershoot against the step change of the load is less than 2% and the transient time is less than 0.4ms with the IIR filter method. In this case, the switching frequency is 100kHz and the step change of the load R is from 50 Ω to 10 Ω. Further, the superior characteristics are obtained when the first gain, the second gain and the second cut-off frequency are relatively large, and the first cut-off frequency and the passing frequency are relatively low. Moreover, it is important that the gain strongly decreases at the second cut-off frequency because the upper band pass frequency range must be always less than half of the sampling frequency based on the sampling theory.

  6. 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.

  7. FASART: An iterative reconstruction algorithm with inter-iteration adaptive NAD filter.

    PubMed

    Zhou, Ziying; Li, Yugang; Zhang, Fa; Wan, Xiaohua

    2015-01-01

    Electron tomography (ET) is an essential imaging technique for studying structures of large biological specimens. These structures are reconstructed from a set of projections obtained at different sample orientations by tilting the specimen. However, most of existing reconstruction methods are not appropriate when the data are extremely noisy and incomplete. A new iterative method has been proposed: adaptive simultaneous algebraic reconstruction with inter-iteration adaptive non-linear anisotropic diffusion (NAD) filter (FASART). We also adopted an adaptive parameter and discussed the step for the filter in this reconstruction method. Experimental results show that FASART can restrain the noise generated in the process of iterative reconstruction and still preserve the more details of the structure edges.

  8. 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.

  9. Digital holographic microscope with low-frequency attenuation filter for position measurement of a nanoparticle.

    PubMed

    Pham, Quang Duc; Kusumi, Yuichi; Hasegawa, Satoshi; Hayasaki, Yoshio

    2012-10-01

    We propose a new method for three-dimensional (3D) position measurement of nanoparticles using an in-line digital holographic microscope. The method improves the signal-to-noise ratio of the amplitude of the interference fringes to achieve higher accuracy in the position measurement by increasing weak scattered light from a nanoparticle relative to the reference light by using a low spatial frequency attenuation filter. We demonstrated the improvements of signal-to-noise ratio of the optical system and contrast of the interference fringes, allowing the 3D positions of nanoparticles to be determined more precisely.

  10. A Digital Forgery Image Detection Algorithm Based on Wavelet Homomorphic Filtering

    NASA Astrophysics Data System (ADS)

    Zheng, Jiangbin; Liu, Miao

    A novel forgery image detection algorithm is proposed to recognize some traces of artificial blur operation that is one of common ways to forge a digital image. Firstly, a wavelet homonorphic filtering is applied to enhance the high frequency edges after the blurring process. Secondly, the natural edges are eroded by mathematical morphology method, and then the enhanced artificial blur edges are preserved. Finally, the forgery image regions are localized by the region labeling method. Experimental results demonstrate the proposed method can detect forgery area accurately and reduce the detecting errors when some artificial blur operations are used to create a forgery image.

  11. Digital implementation of filters for nuclear applications using the discrete wavelet transform

    NASA Astrophysics Data System (ADS)

    Garcia-Belmonte, G.; Perez, J. M.; Fernandez-Marron, J. L.; Bisquert, J.

    1996-10-01

    This paper presents a novel digital pulse processing technique based on fast implementations of a modern signal analysis method known as the wavelet transform (WT). From the point of view of standard nuclear filtering, the whole analysis may be understood as the action of a bank of gaussian shapers. The algorithm permits the evaluation of relevant parameters on each pulse and, making use of this information, a spectral improvement is achieved in the response of HgI 2 detectors constructed in our laboratories. As the performance of these detectors is mainly limited by the hole trapping phenomenon, the introduction of a charge loss correction making use of the WT has been considered. In this work, the pulse processing has been carried out by transferring the digital recorded pulses to a computer where a software version of the algorithm is performed.

  12. Active listening room compensation for massive multichannel sound reproduction systems using wave-domain adaptive filtering.

    PubMed

    Spors, Sascha; Buchner, Herbert; Rabenstein, Rudolf; Herbordt, Wolfgang

    2007-07-01

    The acoustic theory for multichannel sound reproduction systems usually assumes free-field conditions for the listening environment. However, their performance in real-world listening environments may be impaired by reflections at the walls. This impairment can be reduced by suitable compensation measures. For systems with many channels, active compensation is an option, since the compensating waves can be created by the reproduction loudspeakers. Due to the time-varying nature of room acoustics, the compensation signals have to be determined by an adaptive system. The problems associated with the successful operation of multichannel adaptive systems are addressed in this contribution. First, a method for decoupling the adaptation problem is introduced. It is based on a generalized singular value decomposition and is called eigenspace adaptive filtering. Unfortunately, it cannot be implemented in its pure form, since the continuous adaptation of the generalized singular value decomposition matrices to the variable room acoustics is numerically very demanding. However, a combination of this mathematical technique with the physical description of wave propagation yields a realizable multichannel adaptation method with good decoupling properties. It is called wave domain adaptive filtering and is discussed here in the context of wave field synthesis.

  13. Phase aberration correction by correlation in digital holographic adaptive optics

    PubMed Central

    Liu, Changgeng; Yu, Xiao; Kim, Myung K.

    2013-01-01

    We present a phase aberration correction method based on the correlation between the complex full-field and guide-star holograms in the context of digital holographic adaptive optics (DHAO). Removal of a global quadratic phase term before the correlation operation plays an important role in the correction. Correlation operation can remove the phase aberration at the entrance pupil plane and automatically refocus the corrected optical field. Except for the assumption that most aberrations lie at or close to the entrance pupil, the presented method does not impose any other constraints on the optical systems. Thus, it greatly enhances the flexibility of the optical design for DHAO systems in vision science and microscopy. Theoretical studies show that the previously proposed Fourier transform DHAO (FTDHAO) is just a special case of this general correction method, where the global quadratic phase term and a defocus term disappear. Hence, this correction method realizes the generalization of FTDHAO into arbitrary DHAO systems. The effectiveness and robustness of this method are demonstrated by simulations and experiments. PMID:23669707

  14. 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.

  15. Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter

    PubMed Central

    2014-01-01

    Background The calculation of arterial oxygen saturation (SpO2) relies heavily on the amplitude information of the high-quality photoplethysmographic (PPG) signals, which could be contaminated by motion artifacts (MA) during monitoring. Methods A new method combining temporally constrained independent component analysis (cICA) and adaptive filters is presented here to extract the clean PPG signals from the MA corrupted PPG signals with the amplitude information reserved. The underlying PPG signal could be extracted from the MA contaminated PPG signals automatically by using cICA algorithm. Then the amplitude information of the PPG signals could be recovered by using adaptive filters. Results Compared with conventional ICA algorithms, the proposed approach is permutation and scale ambiguity-free. Numerical examples with both synthetic datasets and real-world MA corrupted PPG signals demonstrate that the proposed method could remove the MA from MA contaminated PPG signals more effectively than the two existing FFT-LMS and moving average filter (MAF) methods. Conclusions This paper presents a new method which combines the cICA algorithm and adaptive filter to extract the underlying PPG signals from the MA contaminated PPG signals with the amplitude information reserved. The new method could be used in the situations where one wants to extract the interested source automatically from the mixed observed signals with the amplitude information reserved. The results of study demonstrated the efficacy of this proposed method. PMID:24761769

  16. Effect of adaptive threshold filtering on ultrasonic nakagami parameter to detect variation in scatterer concentration.

    PubMed

    Tsui, Po-Hsiang; Wan, Yung-Liang; Huang, Chih-Chung; Wang, Ming-Chen

    2010-10-01

    The Nakagami parameter is associated with the Nakagami distribution estimated from ultrasonic backscattered signals and closely reflects the scatterer concentrations in tissues. There is an interest in exploring the possibility of enhancing the ability of the Nakagami parameter to characterize tissues. In this paper, we explore the effect of adaptive thresholdfiltering based on the noise-assisted empirical mode decomposition of the ultrasonic backscattered signals on the Nakagami parameter as a function of scatterer concentration for improving the Nakagami parameter performance. We carried out phantom experiments using 5 MHz focused and nonfocused transducers. Before filtering, the dynamic ranges of the Nakagami parameter, estimated using focused and nonfocused transducers between the scatterer concentrations of 2 and 32 scatterers/mm3, were 0.44 and 0.1, respectively. After filtering, the dynamic ranges of the Nakagami parameter, using the focused and nonfocused transducers, were 0.71 and 0.79, respectively. The experimental results showed that the adaptive threshold filter makes the Nakagami parameter measured by a focused transducer more sensitive to the variation in the scatterer concentration. The proposed method also endows the Nakagami parameter measured by a nonfocused transducer with the ability to differentiate various scatterer concentrations. However, the Nakagami parameters estimated by focused and nonfocused transducers after adaptive threshold filtering have different physical meanings: the former represents the statistics of signals backscattered from unresolvable scatterers while the latter is associated with stronger resolvable scatterers or local inhomogeneity due to scatterer aggregation.

  17. Reducing the effect of respiration in baroreflex sensitivity estimation with adaptive filtering.

    PubMed

    Tiinanen, Suvi; Tulppo, Mikko; Seppänen, Tapio

    2008-01-01

    Cardiac baroreflex is described by baroreflex sensitivity (BRS) from blood pressure and heart rate interval (RRi) fluctuations. However, respiration affects both blood pressure and RRi via mechanisms that are not necessarily of baroreflex origin. To separate the effects of baroreflex and respiration, metronome-guided breathing in a high frequency band (HF, 0.25-0.4 Hz) and a low frequency spectral band (LF, 0.04-0.15 Hz) have therefore been commonly used for BRS estimation. The controlled breathing may, however, change the natural functioning of the autonomic system and interfere BRS estimates. To enable usage of spontaneous breathing, we propose an adaptive LMS-based filter for removing the respiration effect from the BRS estimates. ECG, continuous blood pressure and respiration were measured during 5 min spontaneous and 5 min controlled breathing at 0.25 Hz in healthy males (n = 24, 33+/-7 years). BRS was calculated with spectral methods from the LF band with and without filtering. In those subjects whose spontaneous breathing rate was <0.15 Hz, the BRS(LF) values were overestimated, whereas the adaptive filtering reduced the bias significantly. As a conclusion, the adaptive filter reduces the distorting effect of respiration on BRS values, which enables more accurate estimation of BRS and the usage of spontaneous breathing as a measurement protocol.

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

    SciTech Connect

    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 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.

  19. A novel approach for using polyphase filter bank in directly digital RF conversion from RF to baseband

    NASA Astrophysics Data System (ADS)

    Zhang, Deying; Jiang, Qin; Ahmed, Mohiuddin

    2012-05-01

    Software defined radio (SDR) hardware platform is in high demand for ultra-wideband digital EW receiver to carry out different mission requirements. Due to the limitations of current Analog-to-Digital conversion (ADC) techniques, the ideal receiver structure of SDR, with digital RF frequency conversion, cannot be achieved. In this article, a new channelization technique called ADC polyphase fast Fourier transformation (ADC PFFT) filter bank channelization is demonstrated. The key concept is to separate the speed at which the two functional units of an ADC - the sample and hold and the quantizer - operate. The sample and hold unit operates at the sampling frequency fs and the quantizer (the speed limiting factor in ADCs) can operate at a much slower rate, fs/M, where M is the decimation factor for digital filter bank. By integrated this ADC PFFT technique in ultra-wideband digital channelized EW receivers, directly digital RF down conversion can be achieved. With the ADC PFFT channelization for RF down conversion and polyphase FFT channelization for IF down conversion, 2-18 GHz frequency coverage can be accomplished in such ultra-wideband digital channelized EW receivers without the requirement of EW receivers being time-shared among outputs from many subbands due to bandwidth limitation in digital IF channelized EW receivers. Because the frequency down conversion from RF to BB are all processed digitally, issues such as image rejection and I/Q imbalance due to analog mixing will be eliminated in the ultrawideband digital channelized EW receivers.

  20. Processing of noisy magnetotelluric data using digital filters and additional data selection criteria

    NASA Astrophysics Data System (ADS)

    Fontes, S. L.; Harinarayana, T.; Dawes, G. J. K.; Hutton, V. R. S.

    1988-10-01

    Although the magnetotelluric (MT) method is known to be effective and fast in probing the electrical conductivity structure of the Earth at crustal depths, the results are often degraded by industrial and cultural noise. To obtain reliable processed results for modelling, it is first necessary to extract or select the natural signals from the contaminated time series. Various noise-reduction techniques based on digital filters are discussed with special reference to persistent noise signals, e.g. from power lines, DC-operated railways and electrical fences. Both previously suggested techniques (delay-line and notch filtering) and two other procedures (maximum entropy extension and deconvolution filtering) are applied to both synthetic data and to field observations from southern Scotland and the Italian Alps. Better quality data sets and more geophysically acceptable Earth models are shown to result. Noise of a more intermittent nature has recently been observed in MT observations near the development site of the geothermal power station on Milos, Greece. Large highly coherent electromagnetic field signals were observed to coincide with the opening and closure of the valves on the test wells. In this case, meaningful apparent resistivity curves could be obtained from an undisturbed subset of the previously accepted data, which had been selected mainly on the basis of signal power. Delay-line filtering is shown to be superior to notch filtering in eliminating non-sinusoidal noise, while both the MEM extension and the window deconvolution techniques are found to be useful in spike removal. These studies illustrate that use of an automatic data selection procedure should only be undertaken with great care in areas where the cultural noise is high. In such cases, continuous time-domain monitoring of the MT signals is recommended. The appropriate techniques of noise reduction can then be applied.

  1. Envelope analysis with a genetic algorithm-based adaptive filter bank for bearing fault detection.

    PubMed

    Kang, Myeongsu; Kim, Jaeyoung; Choi, Byeong-Keun; Kim, Jong-Myon

    2015-07-01

    This paper proposes a fault detection methodology for bearings using envelope analysis with a genetic algorithm (GA)-based adaptive filter bank. Although a bandpass filter cooperates with envelope analysis for early identification of bearing defects, no general consensus has been reached as to which passband is optimal. This study explores the impact of various passbands specified by the GA in terms of a residual frequency components-to-defect frequency components ratio, which evaluates the degree of defectiveness in bearings and finally outputs an optimal passband for reliable bearing fault detection.

  2. The application of dummy noise adaptive Kalman filter in underwater navigation

    NASA Astrophysics Data System (ADS)

    Li, Song; Zhang, Chun-Hua; Luan, Jingde

    2011-10-01

    The track of underwater target is easy to be affected by the various by the various factors, which will cause poor performance in Kalman filter with the error in the state and measure model. In order to solve the situation, a method is provided with dummy noise compensative technology. Dummy noise is added to state and measure model artificially, and then the question can be solved by the adaptive Kalman filter with unknown time-changed statistical character. The simulation result of underwater navigation proves the algorithm is effective.

  3. Modified Log-LMS adaptive filter with low signal distortion for biomedical applications.

    PubMed

    Jiao, Yuzhong; Cheung, Rex Y P; Mok, Mark P C

    2012-01-01

    Life signals from human body, e.g. heartbeat or electrocardiography (ECG), are usually weak and susceptible to external noise and interference. Adaptive filter is a good tool to reduce the influence of ambient noise/interference on the life signals. Least mean squares (LMS) algorithm, as one of most popular adaptive algorithms for active noise cancellation (ANC) by adaptive filtering, has the advantage of easy implementation. In order to further decrease the complexity of LMS algorithm based adaptive filter, a Log-LMS algorithm was proposed, which quantized signals by the function of log2. The algorithm can replace multipliers by simple shifting. However, both LMS algorithm and Log-LMS algorithm have the disadvantage of serious signal distortion in biomedical applications. In this paper, a modified Log-LMS algorithm is presented, which divides the convergence process into two different stages, and utilizes different quantization method in each stage. Two scenarios of biomedical applications are used for analysis, 1) using stethoscope in emergence medical helicopter and 2) measuring ECG under power line interference. The simulated results show that the modified algorithm can achieve fast convergence and low signal distortion in processing periodic life signals.

  4. Adaptive filtering and feed-forward control for suppression of vibration and jitter

    NASA Astrophysics Data System (ADS)

    Anderson, Eric H.; Blankinship, Ross L.; Fowler, Leslie P.; Glaese, Roger M.; Janzen, Paul C.

    2007-04-01

    This paper describes the use of adaptive filtering to control vibration and optical jitter. Adaptive filtering is a class of signal processing techniques developed over the last several decades and applied since to applications ranging from communications to image processing. Basic concepts in adaptive filtering and feedforward control are reviewed. A series of examples in vibration, motion and jitter control, including cryocoolers, ground-based active optics systems, flight motion simulators, wind turbines and airborne optical beam control systems, illustrates the effectiveness of the adaptive methods. These applications make use of information and signals that originate from system disturbances and minimize the correlations between disturbance information and error and performance measures. The examples incorporate a variety of disturbance types including periodic, multi-tonal, broadband stationary and non-stationary. Control effectiveness with slowly-varying narrowband disturbances originating from cryocoolers can be extraordinary, reaching 60 dB of reduction or rejection. In other cases, performance improvements are only 30-50%, but such reductions effectively complement feedback servo performance in many applications.

  5. An adaptive panoramic filter bank as a qualitative model of the filtering system of the cochlea: the peculiarities in linear and nonlinear mode.

    PubMed

    Stasiunas, Antanas; Verikas, Antanas; Bacauskiene, Marija; Miliauskas, Rimvydas

    2012-03-01

    Outer hair cells in the cochlea of the ear, together with the local structures of the basilar membrane, reticular lamina and tectorial membrane constitute the adaptive primary filters (PF) of the second order. We used them for designing a serial-parallel signal filtering system. We determined a rational number of the PF included in Gaussian channels of the system, summation weights of the output signals, and distribution of the PF along the basilar membrane. A Gaussian panoramic filter bank each channel of which consists of five PF is presented as an example. The properties of the PF, the channel and the filter bank operating in the linear and nonlinear modes are determined during adaptation and under efferent control. The results suggest that application of biological filtering principles can be useful for designing cochlear implants with new speech encoding strategies.

  6. Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

    NASA Astrophysics Data System (ADS)

    Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

    2017-04-01

    Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We

  7. Design of digital filters for frequency weightings (A and C) required for risk assessments of workers exposed to noise.

    PubMed

    Rimell, Andrew N; Mansfield, Neil J; Paddan, Gurmail S

    2015-01-01

    Many workers are exposed to noise in their industrial environment. Excessive noise exposure can cause health problems and therefore it is important that the worker's noise exposure is assessed. This may require measurement by an equipment manufacturer or the employer. Human exposure to noise may be measured using microphones; however, weighting filters are required to correlate the physical noise sound pressure level measurements to the human's response to an auditory stimulus. IEC 61672-1 and ANSI S1.43 describe suitable weighting filters, but do not explain how to implement them for digitally recorded sound pressure level data. By using the bilinear transform, it is possible to transform the analogue equations given in the standards into digital filters. This paper describes the implementation of the weighting filters as digital IIR (Infinite Impulse Response) filters and provides all the necessary formulae to directly calculate the filter coefficients for any sampling frequency. Thus, the filters in the standards can be implemented in any numerical processing software (such as a spreadsheet or programming language running on a PC, mobile device or embedded system).

  8. Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

    PubMed

    Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

    2014-05-01

    In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

  9. 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.

  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. Adapting a truly nonlinear filter to the ocean acoustic inverse problem

    NASA Astrophysics Data System (ADS)

    Ganse, Andrew A.; Odom, Robert I.

    2005-04-01

    Nonlinear inverse problems including the ocean acoustic problem have been solved by Monte Carlo, locally-linear, and filter based techniques such as the Extended Kalman Filter (EKF). While these techniques do provide statistical information about the solution (e.g., mean and variance), each suffers from inherent limitations in their approach to nonlinear problems. Monte Carlo techniques are expensive to compute and do not contribute to intuitive interpretation of a problem, and locally-linear techniques (including the EKF) are limited by the multimodal objective landscape of nonlinear problems. A truly nonlinear filter, based on recent work in nonlinear tracking, estimates state information for a nonlinear problem in continual measurement updates and is adapted to solving nonlinear inverse problems. Additional terms derived from the system's state PDF are added to the mean and covariance of the solution to address the nonlinearities of the problem, and overall the technique offers improved performance in nonlinear inversion. [Work supported by ONR.

  12. 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.

  13. 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

  14. Detecting curvatures in digital images using filters derived from differential geometry

    NASA Astrophysics Data System (ADS)

    Toro Giraldo, Juanita

    2015-09-01

    Detection of curvature in digital images is an important theoretical and practical problem in image processing. Many important features in an image are associated with curvature and the detection of such features is reduced to detection and characterization of curvatures. Differential geometry studies many kinds of curvature operators and from these curvature operators is possible to derive powerful filters for image processing which are able to detect curvature in digital images and videos. The curvature operators are formulated in terms of partial differential operators which can be applied to images via convolution with generalized kernels derived from the the Korteweg- de Vries soliton . We present an algorithm for detection of curvature in digital images which is implemented using the Maple package ImageTools. Some experiments were performed and the results were very good. In a future research will be interesting to compare the results using the Korteweg-de Vries soliton with the results obtained using Airy derivatives. It is claimed that the resulting curvature detectors could be incorporated in standard programs for image processing.

  15. Can digital image forgery detection unevadable? A case study: color filter array interpolation statistical feature recovery

    NASA Astrophysics Data System (ADS)

    Huang, Yizhen

    2005-07-01

    Digital image forgery detection is becoming increasing important. In recently 2 years, a new upsurge has been started to study direct detection methods, which utilize the hardware features of digital cameras. Such features may be weakened or lost once tampered, or they may not be consistent if synthesizing several images into a single one. This manuscript first clarifies the concept of trueness of digital images and summarizes these methods with their crack by a general model. The recently proposed EM algorithm plus Fourier transform that checks the Color Filter Array (CFA) interpolation statistical feature (ISF) is taken as a case study. We propose 3 methods to recover the CFA-ISF of a fake image: (1) artificial CFA interpolation (2) a linear CFA-ISF recovery model with optimal uniform measure (3) a quadratic CFA-ISF recovery model with least square measure. A software prototype CFA-ISF Indicator & Adjustor integrating the detection and anti-detection algorithms is developed and shown. Experiments under our product validate the effectiveness of our methods.

  16. Robust respiration rate estimation using adaptive Kalman filtering with textile ECG sensor and accelerometer.

    PubMed

    Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi; Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi; Koizumi, Hiroshi; Ogasawara, Takayuki; Tajima, Takuro; Kasahara, Ryoichi; Lepine, Nicholas N

    2016-08-01

    An adaptive Kalman filter-based fusion algorithm capable of estimating respiration rate for unobtrusive respiratory monitoring is proposed. Using both signal characteristics and a priori information, the Kalman filter is adaptively optimized to improve accuracy. Furthermore, the system is able to combine the respiration-related signals extracted from a textile ECG sensor and an accelerometer to create a single robust measurement. We measured derived respiratory rates and, when compared to a reference, found root-mean-square error of 2.11 breaths-per-minute (BrPM) while lying down, 2.30 BrPM while sitting, 5.97 BrPM while walking, and 5.98 BrPM while running. These results demonstrate that the proposed system is applicable to unobtrusive monitoring for various applications.

  17. 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.

  18. Adaptive control of a flexible beam using least square lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Montgomery, R. C.

    1983-01-01

    This paper presents an indirect adaptive control scheme for the control of flexible structures using recursive least square lattice filters. The identification scheme uses lattice filters which provide an on-line estimate of the number of modes, mode shapes and modal amplitudes. These modes are coupled and a transformation to decouple them in order to obtain the natural modes is presented. The decoupled modal amplitude time series are then used in an equation error identification scheme to identify the model parameters in an autoregressive moving average (ARMA) form. The control is based on modal pole placement scheme with the objective of vibration suppression. The control gains are calculated based on the identified ARMA parameters. Before using the identified parameters for control, detailed testing and validation procedures are carried out on the identified parameters. The full adaptive control scheme is demonstrated using the simulation for the 12 foot free-free beam apparatus at NASA Langley Research Center.

  19. Performance characteristics of an adaptive controller based on least-mean-square filters

    NASA Technical Reports Server (NTRS)

    Mehta, R. S.; Merhav, S. J.

    1986-01-01

    A closed-loop, adaptive-control scheme that uses a least-mean-square filter as the controller model is presented, along with simulation results that demonstrate the excellent robustness of this scheme. It is shown that the scheme adapts very well to unknown plants, even those that are marginally stable, responds appropriately to changes in plant parameters, and is not unduly affected by additive noise. A heuristic argument for the conditions necessary for convergence is presented. Potential applications and extensions of the scheme are also discussed.

  20. Performance characteristics of an adaptive controller based on least-mean-square filters

    NASA Technical Reports Server (NTRS)

    Mehta, Rajiv S.; Merhav, Shmuel J.

    1986-01-01

    A closed loop, adaptive control scheme that uses a least mean square filter as the controller model is presented, along with simulation results that demonstrate the excellent robustness of this scheme. It is shown that the scheme adapts very well to unknown plants, even those that are marginally stable, responds appropriately to changes in plant parameters, and is not unduly affected by additive noise. A heuristic argument for the conditions necessary for convergence is presented. Potential applications and extensions of the scheme are also discussed.

  1. 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

  2. Adaptive filtering of biodynamic stick feedthrough in manipulation tasks on board moving platforms

    NASA Technical Reports Server (NTRS)

    Velger, M.; Grunwald, A.; Merhav, S.

    1986-01-01

    A novel approach to suppress the effects of biodynamic interference is presented. An adaptive noise canceling technique is employed for substracting the platform motion correlated components from the control stick output. The effects of biodynamic interference and its suppression by adaptive noise cancellation has been evaluated in a series of tracking tasks performed in a moving base simulator. Simulator motions were in pitch, roll and combined pitch and roll. Human operator performance was assessed from the mean square values of the tracking error and the control activity. The tracking error and the total stick output signal were found to increase significantly with motion and to diminish substantially with adaptive noise cancellation, thus providing a considerable improvement in tracking performance under conditions in which platform motion were present. The adaptive filter was found to cause a significant increase in the cross-over frequency and decrease in the phase margin. Moreover, the adaptive filter was found to significantly improve the human operator visual motor response. This improvement is manifested as an increased human operator gain, a smaller time delay and lower pilot workload.

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

    PubMed

    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.

  4. 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.

  5. Fuzzy adaptive interacting multiple model nonlinear filter for integrated navigation sensor fusion.

    PubMed

    Tseng, Chien-Hao; Chang, Chih-Wen; Jwo, Dah-Jing

    2011-01-01

    In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF) approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF) employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching) mechanism, the interacting multiple model (IMM), which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS) is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS). The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.

  6. 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.

  7. Digital filtering of three-dimensional lower extremity kinematics: an assessment.

    PubMed

    Sinclair, Jonathan; Taylor, Paul John; Hobbs, Sarah Jane

    2013-12-18

    Errors in kinematic data are referred to as noise and are an undesirable portion of any waveform. Noise is typically removed using a low-pass filter which removes the high frequency components of the signal. The selection of an optimal frequency cut-off is very important when processing kinematic information and a number of techniques exists for the determination of an optimal frequency cut-off. Despite the importance of cut-off frequency to the efficacy of kinematic analyses there is currently a paucity of research examining the influence of different cut-off frequencies on the resultant 3-D kinematic waveforms and discrete parameters. Twenty participants ran at 4.0 m•s-1 as lower extremity kinematics in the sagittal, coronal and transverse planes were measured using an eight camera motion analysis system. The data were filtered at a range of cut-off frequencies and the discrete kinematic parameters were examined using repeated measures ANOVA's. The similarity between the raw and filtered waveforms were examined using intra-class correlations. The results show that the cut-off frequency has a significant influence on the discrete kinematic measure across displacement and derivative information in all three planes of rotation. Furthermore, it was also revealed that as the cut-off frequency decreased the attenuation of the kinematic waveforms became more pronounced, particularly in the coronal and transverse planes at the second derivative. In conclusion, this investigation provides new information regarding the influence of digital filtering on lower extremity kinematics and re-emphasizes the importance of selecting the correct cut-off frequency.

  8. 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.

  9. Adaptive filter based two-probe noise suppression system for transient evoked otoacoustic emission detection.

    PubMed

    Subotić, Miško; Šarić, Zoran; Jovičić, Slobodan T

    2012-03-01

    Transient otoacoustic emission (TEOAE) is a method widely used in clinical practice for assessment of hearing quality. The main problem in TEOAE detection is its much lower level than the level of environmental and biological noise. While the environmental noise level can be controlled, the biological noise can be only reduced by appropriate signal processing. This paper presents a new two-probe preprocessing TEOAE system for suppression of the biological noise by adaptive filtering. The system records biological noises in both ears and applies a specific adaptive filtering approach for suppression of biological noise in the ear canal with TEOAE. The adaptive filtering approach includes robust sign error LMS algorithm, stimuli response summation according to the derived non-linear response (DNLR) technique, subtraction of the estimated TEOAE signal and residual noise suppression. The proposed TEOAE detection system is tested by three quality measures: signal-to-noise ratio (S/N), reproducibility of TEOAE, and measurement time. The maximal TEOAE detection improvement is dependent on the coherence function between biological noise in left and right ears. The experimental results show maximal improvement of 7 dB in S/N, improvement in reproducibility near 40% and reduction in duration of TEOAE measurement of over 30%.

  10. Optoelectronic approach to adaptive radio-frequency transversal filter implementation with negative coefficients by using optical spectrum shaping.

    PubMed

    Arain, Muzammil A; Riza, Nabeel A

    2006-04-10

    A multitap negative and positive coefficient radio-frequency transversal filter is implemented by using a digital-micromirror-device spatial light modulator for weighting-factor control and a chirped fiber Bragg grating for time-delay control. The demonstrated architecture is reconfigurable, has high speed and low loss, and is robust through digital programmability for a wide variety of filtering algorithms. A design using an interleaver for differential detection realizes an ultrahigh bandwidth with a maximum processable frequency of 33.7 GHz. A multitap low-pass filter, a negative tap notch filter with 40 dB attenuation, and a multitap negative coefficient bandpass filter are experimentally demonstrated. The results are in agreement with theory.

  11. Adaptive Digital Signature Design and Short-Data-Record Adaptive Filtering

    DTIC Science & Technology

    2008-04-01

    of signal parameters via rotational invariance techniques FDMA frequency − division multiple − access GLR generalized likelihood ratio ISI inter...of sensor networks do not fa- vor time-division multiple-access (TDMA) developments. Similarly, frequency- division multiple-access ( FDMA ), would

  12. 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.

  13. Subband Quantum Scattering Times for Algaas/GaAs Obtained Using Digital Filtering

    NASA Technical Reports Server (NTRS)

    Mena, R. A.; Schacham, S. E.; Haughland, E. J.; Alterovitz, S. A.; Bibyk, S. B.; Ringel, S. A.

    1995-01-01

    In this study we investigate both the transport and quantum scattering times as a function of the carrier concentration for a modulation doped Al(0.3)Ga(0.7)As/GaAs structure. Carriers in the well are generated as a result of the persistent photoconductivity effect. When more than one subband becomes populated, digital filtering is used to separate the components for each of the excited subbands. We find that the quantum scattering time for the ground subband increases initially as the carrier concentration is increased. However, once the second subband becomes populated, the ground subband scattering time begins to decrease. The quantum scattering time for the excited subband is also observed to decrease as the concentration is increased. From the ratio of the transport and quantum scattering times, it is seen that the transport in the well becomes more isotropic also as the concentration is increased.

  14. Filter-bank based digital sub-banding ASIC architecture for coherent optical receivers

    NASA Astrophysics Data System (ADS)

    Nazarathy, Moshe; Tolmachev, Alex

    2013-01-01

    We introduce a highly efficient high performance architecture for the digital signal processing of high speed coherent optical receivers. Our ASIC signal processing architecture ports for the first time to optical reception efficient filter bank signal processing structures. The resulting optical receiver ASICs are applicable to long-haul and metro photonic communication and provide substantial energy efficiency saving 30%-50% in power consumption. We aim to develop an ultra-high-speed optical receiver ASIC for transporting 160 Gb/s in a 25 GHz optical band - seven such channels will together carry 1Tb/s (plus overhead) in our 'TeraSanta' project of TeraBitPerSecond efficient transponders.

  15. Bias error reduction of digital image correlation using Gaussian pre-filtering

    NASA Astrophysics Data System (ADS)

    Pan, Bing

    2013-10-01

    In digital image correlation (DIC), the iterative spatial domain cross-correlation algorithm using high-order B-spline interpolation algorithms has been strongly recommended for accurate sub-pixel displacement measurement. However, the magnitude of the position-dependent bias error increases with the increase of noise level, which dramatically reduces the registration accuracy of DIC for real experimental images. In this paper, a simple method, based on pre-smoothing the speckle images with a 5×5 pixels Gaussian low-pass filter prior to correlation analysis, is proposed for reducing the bias error in measured displacements. Both numerical simulations and real experiments reveal that the proposed technique is capable of reducing the bias error in measured displacement to a negligible degree for both noisy and noiseless images, even though a simple bicubic interpolation is used.

  16. Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography*

    PubMed Central

    Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

    2015-01-01

    Objective Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography. PMID:26811553

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

    DOE PAGES

    Stuart, Andrew M.; Shukla, Abhishek; Sanz-Alonso, Daniel; ...

    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

  18. Fully reconfigurable photonic microwave transversal filter based on digital micromirror device and continuous-wave, incoherent supercontinuum source.

    PubMed

    Lee, Ju Han; Chang, You Min; Han, Young-Geun; Lee, Sang Bae; Chung, Hae Yang

    2007-08-01

    The combined use of a programmable, digital micromirror device (DMD) and an ultrabroadband, cw, incoherent supercontinuum (SC) source is experimentally demonstrated to fully explore various aspects on the reconfiguration of a microwave filter transfer function by creating a range of multiwavelength optical filter shapes. Owing to both the unique characteristic of the DMD that an arbitrary optical filter shape can be readily produced and the ultrabroad bandwidth of the cw SC source that is 3 times larger than that of Er-amplified spontaneous emission, a multiwavelength optical beam pattern can be generated with a large number of wavelength filter taps apodized by an arbitrary amplitude window. Therefore various types of high-quality microwave filter can be readily achieved through the spectrum slicing-based photonic microwave transversal filter scheme. The experimental demonstration is performed in three aspects: the tuning of a filter resonance bandwidth at a fixed resonance frequency, filter resonance frequency tuning at a fixed resonance frequency, and flexible microwave filter shape reconstruction.

  19. Adapted fan-beam volume reconstruction for stationary digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Wu, Gongting; Inscoe, Christine; Calliste, Jabari; Lee, Yueh Z.; Zhou, Otto; Lu, Jianping

    2015-03-01

    Digital breast tomosynthesis (DBT) provides 3D images which remove tissue overlapping and enables better cancer detection. Stationary DBT (s-DBT) uses a fixed X-ray source array to eliminate image blur associated with the x-ray tube motion and provides better image quality as well as faster scanning speed. For limited angle tomography, it is known that iterative reconstructions generally produces better images with fewer artifacts. However classical iterative tomosynthesis reconstruction methods are considerably slower than the filtered back-projection (FBP) reconstruction. The linear x-ray source array used in s-DBT enables a computationally more efficient volume reconstruction using adapted fan beam slice sampling, which transforms the 3-D cone beam reconstruction to a series of 2-D fan beam slice reconstructions. In this paper, we report the first results of the adapted fan-beam volume reconstruction (AFVR) for the s-DBT system currently undergoing clinical trial at UNC, using a simultaneous algebraic reconstruction technique (SART). An analytic breast phantom is used to quantitatively analyze the performance of the AFVR. Image quality of a CIRS biopsy phantom reconstructed using the AFVR method are compared to that using FBP algorithm with a commercial package. Our results show a significant reduction in memory usage and an order of magnitude speed increase in reconstructing speed using AFVR compared to that of classical 3-D cone beam reconstruction. We also observed that images reconstructed by AFVR with SART had a better sharpness and contrast compared to that using FBP. Preliminary results on patient images demonstrates the improved detectability of the s-DBT system over the mammography. By utilizing parallel computing with graphics processing unit (GPU), it is expected that the AFVR method will enable iterative reconstruction technique to be practical for clinical applications.

  20. Design and implementation of a multiband digital filter using FPGA to extract the ECG signal in the presence of different interference signals.

    PubMed

    Aboutabikh, Kamal; Aboukerdah, Nader

    2015-07-01

    In this paper, we propose a practical way to synthesize and filter an ECG signal in the presence of four types of interference signals: (1) those arising from power networks with a fundamental frequency of 50Hz, (2) those arising from respiration, having a frequency range from 0.05 to 0.5Hz, (3) muscle signals with a frequency of 25Hz, and (4) white noise present within the ECG signal band. This was done by implementing a multiband digital filter (seven bands) of type FIR Multiband Least Squares using a digital programmable device (Cyclone II EP2C70F896C6 FPGA, Altera), which was placed on an education and development board (DE2-70, Terasic). This filter was designed using the VHDL language in the Quartus II 9.1 design environment. The proposed method depends on Direct Digital Frequency Synthesizers (DDFS) designed to synthesize the ECG signal and various interference signals. So that the synthetic ECG specifications would be closer to actual ECG signals after filtering, we designed in a single multiband digital filter instead of using three separate digital filters LPF, HPF, BSF. Thus all interference signals were removed with a single digital filter. The multiband digital filter results were studied using a digital oscilloscope to characterize input and output signals in the presence of differing sinusoidal interference signals and white noise.

  1. Towards standardization of x-ray beam filters in digital mammography and digital breast tomosynthesis: Monte Carlo simulations and analytical modelling

    NASA Astrophysics Data System (ADS)

    Shrestha, Suman; Vedantham, Srinivasan; Karellas, Andrew

    2017-03-01

    In digital breast tomosynthesis and digital mammography, the x-ray beam filter material and thickness vary between systems. Replacing K-edge filters with Al was investigated with the intent to reduce exposure duration and to simplify system design. Tungsten target x-ray spectra were simulated with K-edge filters (50 µm Rh; 50 µm Ag) and Al filters of varying thickness. Monte Carlo simulations were conducted to quantify the x-ray scatter from various filters alone, scatter-to-primary ratio (SPR) with compressed breasts, and to determine the radiation dose to the breast. These data were used to analytically compute the signal-difference-to-noise ratio (SDNR) at unit (1 mGy) mean glandular dose (MGD) for W/Rh and W/Ag spectra. At SDNR matched between K-edge and Al filtered spectra, the reductions in exposure duration and MGD were quantified for three strategies: (i) fixed Al thickness and matched tube potential in kilovolts (kV); (ii) fixed Al thickness and varying the kV to match the half-value layer (HVL) between Al and K-edge filtered spectra; and, (iii) matched kV and varying the Al thickness to match the HVL between Al and K-edge filtered spectra. Monte Carlo simulations indicate that the SPR with and without the breast were not different between Al and K-edge filters. Modelling for fixed Al thickness (700 µm) and kV matched to K-edge filtered spectra, identical SDNR was achieved with 37–57% reduction in exposure duration and with 2–20% reduction in MGD, depending on breast thickness. Modelling for fixed Al thickness (700 µm) and HVL matched by increasing the kV over (0,4) range, identical SDNR was achieved with 62–65% decrease in exposure duration and with 2–24% reduction in MGD, depending on breast thickness. For kV and HVL matched to K-edge filtered spectra by varying Al filter thickness over (700, 880) µm range, identical SDNR was achieved with 23–56% reduction in exposure duration and 2–20% reduction in MGD, depending on breast thickness

  2. 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.

  3. Speckle reduction process based on digital filtering and wavelet compounding in optical coherence tomography for dermatology

    NASA Astrophysics Data System (ADS)

    Gómez Valverde, Juan J.; Ortuño, Juan E.; Guerra, Pedro; Hermann, Boris; Zabihian, Behrooz; Rubio-Guivernau, José L.; Santos, Andrés.; Drexler, Wolfgang; Ledesma-Carbayo, Maria J.

    2015-07-01

    Optical Coherence Tomography (OCT) has shown a great potential as a complementary imaging tool in the diagnosis of skin diseases. Speckle noise is the most prominent artifact present in OCT images and could limit the interpretation and detection capabilities. In this work we propose a new speckle reduction process and compare it with various denoising filters with high edge-preserving potential, using several sets of dermatological OCT B-scans. To validate the performance we used a custom-designed spectral domain OCT and two different data set groups. The first group consisted in five datasets of a single B-scan captured N times (with N<20), the second were five 3D volumes of 25 Bscans. As quality metrics we used signal to noise (SNR), contrast to noise (CNR) and equivalent number of looks (ENL) ratios. Our results show that a process based on a combination of a 2D enhanced sigma digital filter and a wavelet compounding method achieves the best results in terms of the improvement of the quality metrics. In the first group of individual B-scans we achieved improvements in SNR, CNR and ENL of 16.87 dB, 2.19 and 328 respectively; for the 3D volume datasets the improvements were 15.65 dB, 3.44 and 1148. Our results suggest that the proposed enhancement process may significantly reduce speckle, increasing SNR, CNR and ENL and reducing the number of extra acquisitions of the same frame.

  4. Application of digital tomosynthesis (DTS) of optimal deblurring filters for dental X-ray imaging

    NASA Astrophysics Data System (ADS)

    Oh, J. E.; Cho, H. S.; Kim, D. S.; Choi, S. I.; Je, U. K.

    2012-04-01

    Digital tomosynthesis (DTS) is a limited-angle tomographic technique that provides some of the tomographic benefits of computed tomography (CT) but at reduced dose and cost. Thus, the potential for application of DTS to dental X-ray imaging seems promising. As a continuation of our dental radiography R&D, we developed an effective DTS reconstruction algorithm and implemented it in conjunction with a commercial dental CT system for potential use in dental implant placement. The reconstruction algorithm employed a backprojection filtering (BPF) method based upon optimal deblurring filters to suppress effectively both the blur artifacts originating from the out-focus planes and the high-frequency noise. To verify the usefulness of the reconstruction algorithm, we performed systematic simulation works and evaluated the image characteristics. We also performed experimental works in which DTS images of enhanced anatomical resolution were successfully obtained by using the algorithm and were promising to our ongoing applications to dental X-ray imaging. In this paper, our approach to the development of the DTS reconstruction algorithm and the results are described in detail.

  5. On the structural limitations of recursive digital filters for base flow estimation

    NASA Astrophysics Data System (ADS)

    Su, Chun-Hsu; Costelloe, Justin F.; Peterson, Tim J.; Western, Andrew W.

    2016-06-01

    Recursive digital filters (RDFs) are widely used for estimating base flow from streamflow hydrographs, and various forms of RDFs have been developed based on different physical models. Numerical experiments have been used to objectively evaluate their performance, but they have not been sufficiently comprehensive to assess a wide range of RDFs. This paper extends these studies to understand the limitations of a generalized RDF method as a pathway for future field calibration. Two formalisms are presented to generalize most existing RDFs, allowing systematic tuning of their complexity. The RDFs with variable complexity are evaluated collectively in a synthetic setting, using modeled daily base flow produced by Li et al. (2014) from a range of synthetic catchments simulated with HydroGeoSphere. Our evaluation reveals that there are optimal RDF complexities in reproducing base flow simulations but shows that there is an inherent physical inconsistency within the RDF construction. Even under the idealized setting where true base flow data are available to calibrate the RDFs, there is persistent disagreement between true and estimated base flow over catchments with small base flow components, low saturated hydraulic conductivity of the soil and larger surface runoff. The simplest explanation is that low base flow "signal" in the streamflow data is hard to distinguish, although more complex RDFs can improve upon the simpler Eckhardt filter at these catchments.

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

    PubMed

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

    2016-05-30

    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.

  7. 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

  8. Automatic nevi segmentation using adaptive mean shift filters and feature analysis

    NASA Astrophysics Data System (ADS)

    King, Michael A.; Lee, Tim K.; Atkins, M. Stella; McLean, David I.

    2004-05-01

    A novel automatic method of segmenting nevi is explained and analyzed in this paper. The first step in nevi segmentation is to iteratively apply an adaptive mean shift filter to form clusters in the image and to remove noise. The goal of this step is to remove differences in skin intensity and hairs from the image, while still preserving the shape of nevi present on the skin. Each iteration of the mean shift filter changes pixel values to be a weighted average of pixels in its neighborhood. Some new extensions to the mean shift filter are proposed to allow for better segmentation of nevi from the skin. The kernel, that describes how the pixels in its neighborhood will be averaged, is adaptive; the shape of the kernel is a function of the local histogram. After initial clustering, a simple merging of clusters is done. Finally, clusters that are local minima are found and analyzed to determine which clusters are nevi. When this algorithm was compared to an assessment by an expert dermatologist, it showed a sensitivity rate and diagnostic accuracy of over 95% on the test set, for nevi larger than 1.5mm.

  9. Performance enhancement for a GPS vector-tracking loop utilizing an adaptive iterated extended Kalman filter.

    PubMed

    Chen, Xiyuan; Wang, Xiying; Xu, Yuan

    2014-12-09

    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.

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

    SciTech Connect

    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 relatively 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 to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so-called "curse of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF could be even more computationally expensive than EnKF. Motivated by most recent developments in uncertainty quantification, 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. The "restart" technology is used to eliminate the inconsistency between model parameters and states. The performance of RAPCKF is tested with numerical cases of unsaturated flow models. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.

  11. Application of an automatic adaptive filter for Heart Rate Variability analysis.

    PubMed

    Dos Santos, Laurita; Barroso, Joaquim J; Macau, Elbert E N; de Godoy, Moacir F

    2013-12-01

    The presence of artifacts and noise effects in temporal series can seriously hinder the analysis of Heart Rate Variability (HRV). The tachograms should be carefully edited to avoid erroneous interpretations. The physician should carefully analyze the tachogram in order to detect points that might be associated with unlikely biophysical behavior and manually eliminate them from the data series. However, this is a time-consuming procedure. To facilitate the pre-analysis of the tachogram, this study uses a method of data filtering based on an adaptive filter which is quickly able to analyze a large amount of data. The method was applied to 229 time series from a database of patients with different clinical conditions: premature newborns, full-term newborns, healthy young adults, adults submitted to a very-low-calorie diet, and adults under preoperative evaluation for coronary artery bypass grafting. This proposed method is compared to the demanding conventional method, wherein the corrections of occasional ectopic beats and artifacts are usually manually executed by a specialist. To confirm the reliability of the results obtained, correlation coefficients were calculated, using both automatic and manual methods of ltering for each HRV index selected. A high correlation between the results was found, with highly significant p values, for all cases, except for some parameters analyzed in the premature newborns group, an issue that is thoroughly discussed. The authors concluded that the proposed adaptive filtering method helps to efficiently handle the task of editing temporal series for HRV analysis.

  12. Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Imani, Mahdi; Braga-Neto, Ulisses M.

    2017-01-01

    Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear models with application in estimation and control of Boolean processes based on noisy and incomplete measurements. The optimal minimum mean square error (MMSE) algorithms for POBDS state estimation, namely, the Boolean Kalman filter (BKF) and Boolean Kalman smoother (BKS), are intractable in the case of large systems, due to computational and memory requirements. To address this, we propose approximate MMSE filtering and smoothing algorithms based on the auxiliary particle filter (APF) method from sequential Monte-Carlo theory. These algorithms are used jointly with maximum-likelihood (ML) methods for simultaneous state and parameter estimation in POBDS models. In the presence of continuous parameters, ML estimation is performed using the expectation-maximization (EM) algorithm; we develop for this purpose a special smoother which reduces the computational complexity of the EM algorithm. The resulting particle-based adaptive filter is applied to a POBDS model of Boolean gene regulatory networks observed through noisy RNA-Seq time series data, and performance is assessed through a series of numerical experiments using the well-known cell cycle gene regulatory model.

  13. 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.

  14. Digital tapped delay lines for HWIL testing of matched filter radar receivers

    NASA Astrophysics Data System (ADS)

    Olson, Richard F.; Braselton, William J.; Mohlere, Richard D.

    2009-05-01

    Matched filter processing for pulse compression of phase coded waveforms is a classic method for increasing radar range measurement resolution. A generic approach for simulating high resolution range extended radar scenes in a Hardware in the Loop (HWIL) test environment is to pass the phase coded radar transmit pulse through an RF tapped delay line comprised of individually amplitude- and phase-weighted output taps. In the generic approach, the taps are closely spaced relative to time intervals equivalent to the range resolution of the compressed radar pulse. For a range-extended high resolution clutter scene, the increased number of these taps can make an analog implementation of an RF tapped delay system impractical. Engineers at the U.S. Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) have addressed this problem by transferring RF tapped delay line signal operations to the digital domain. New digital tapped delay line (DTDL) systems have been designed and demonstrated which are physically compact compared to analog RF TDLs, leverage low cost FPGA and data converter technology, and may be readily expanded using open slots in a VME card cage. In initial HWIL applications, the new DTDLs have been shown to produce better dynamic range in pulse compressed range profiles than their analog TDL predecessors. This paper describes the signal requirements and system architecture for digital tapped delay lines. Implementation, performance, and HWIL simulation integration issues for AMRDEC's first generation DTDLs are addressed. The paper concludes with future requirements and plans for ongoing DTDL technology development at AMRDEC.

  15. Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.; Pratt, S. G.

    1979-01-01

    The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.

  16. Rapid Transfer Alignment of MEMS SINS Based on Adaptive Incremental Kalman Filter

    PubMed Central

    Chu, Hairong; Sun, Tingting; Zhang, Baiqiang; Zhang, Hongwei; Chen, Yang

    2017-01-01

    In airborne MEMS SINS transfer alignment, the error of MEMS IMU is highly environment-dependent and the parameters of the system model are also uncertain, which may lead to large error and bad convergence of the Kalman filter. In order to solve this problem, an improved adaptive incremental Kalman filter (AIKF) algorithm is proposed. First, the model of SINS transfer alignment is defined based on the “Velocity and Attitude” matching method. Then the detailed algorithm progress of AIKF and its recurrence formulas are presented. The performance and calculation amount of AKF and AIKF are also compared. Finally, a simulation test is designed to verify the accuracy and the rapidity of the AIKF algorithm by comparing it with KF and AKF. The results show that the AIKF algorithm has better estimation accuracy and shorter convergence time, especially for the bias of the gyroscope and the accelerometer, which can meet the accuracy and rapidity requirement of transfer alignment. PMID:28098829

  17. 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.

  18. 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.

  19. Rapid Transfer Alignment of MEMS SINS Based on Adaptive Incremental Kalman Filter.

    PubMed

    Chu, Hairong; Sun, Tingting; Zhang, Baiqiang; Zhang, Hongwei; Chen, Yang

    2017-01-14

    In airborne MEMS SINS transfer alignment, the error of MEMS IMU is highly environment-dependent and the parameters of the system model are also uncertain, which may lead to large error and bad convergence of the Kalman filter. In order to solve this problem, an improved adaptive incremental Kalman filter (AIKF) algorithm is proposed. First, the model of SINS transfer alignment is defined based on the "Velocity and Attitude" matching method. Then the detailed algorithm progress of AIKF and its recurrence formulas are presented. The performance and calculation amount of AKF and AIKF are also compared. Finally, a simulation test is designed to verify the accuracy and the rapidity of the AIKF algorithm by comparing it with KF and AKF. The results show that the AIKF algorithm has better estimation accuracy and shorter convergence time, especially for the bias of the gyroscope and the accelerometer, which can meet the accuracy and rapidity requirement of transfer alignment.

  20. A stabilized dual Kalman filter for adaptive tracking of brain-computer interface decoding parameters.

    PubMed

    Zhang, Yin; Chase, Steve M

    2013-01-01

    Neural prosthetics are a promising technology for alleviating paralysis by actuating devices directly from the intention to move. Typical implementations of these devices require a calibration session to define decoding parameters that map recorded neural activity into movement of the device. However, a major factor limiting the clinical deployment of this technology is stability: with fixed decoding parameters, control of the prosthetic device has been shown to degrade over time. Here we apply a dual estimation procedure to adaptively capture changes in decoding parameters. In simulation, we find that our stabilized dual Kalman filter can run autonomously for hundreds of thousands of trials with little change in performance. Further, when we apply our algorithm off-line to estimate arm trajectories from neural data recorded over five consecutive days, we find that it outperforms a static Kalman filter, even when it is re-calibrated at the beginning of each day.

  1. Hydro-geo-chemical streamflow analysis as a support for digital hydrograph filtering in a small, rainfall dominated, sandstone watershed

    NASA Astrophysics Data System (ADS)

    Longobardi, A.; Villani, P.; Guida, D.; Cuomo, A.

    2016-08-01

    The aim of the present study is an analysis of the ability of digital hydrograph filtering tools for the characterization of the baseflow source contributing to total streamflow for a typical, small, sandstone, rainfall dominated catchment. Daily streamflow and electrical conductivity data for an experimental catchment, the Ciciriello catchment, a 3km2 watershed located in Southern Italy, have been collected to the purpose since 2012. The application of a mass balance filter (MBF), using electrical conductivity as tracer data, has pointed out a seasonal characterization of the baseflow pattern, contributing to total streamflow by 90% during the low flow period and up to 40% during the high flow period. The Lyne and Hollick one parameter and the two parameters Eckhardt digital filters have been furthermore processed, both in an uncalibrated and calibrated application. Providing a preliminary total streamflow and baseflow recession analysis, the one parameter filter appears particularly suited for ungauged cases, as the uncalibrated and calibrated applications are almost identical, with relative prediction errors, compared to MBF, smaller than 5%. The uncalibrated two parameters filter generates instead large relative error of about 35%. To improve the baseflow description, in particular during the low flow period, and to correct large (28%) underestimation of the minimum baseflow value, a seasonal calibration for the BFImax parameter (the maximum BaseFlow Index that can be modeled by the filter algorithm) is in fact needed.

  2. Frequency filtering to suppress background noise in fingerprint evidence: quantifying the fidelity of digitally enhanced fingerprint images.

    PubMed

    Speir, Jacqueline A; Hietpas, Jack

    2014-09-01

    Fingerprint evidence can benefit in image quality if transformed using digital image processing techniques. This is especially true when considering prints that cannot be easily lifted (such as those deposited on porous paper substrates), or when the mechanism of lifting does not effectively reduce background interferences. In these instances, frequency filtering is one type of mathematical transformation that can serve to increase image clarity and the ability to extract minutiae relevant to pairwise comparisons. To quantify the impact of frequency filtering on image quality, high quality and low quality (noisy) prints were collected. The high quality prints served as exemplars that were compared to the low quality prints both pre- and post-filtering. The resulting pairwise match scores indicate that: (1) frequency filtering has a low probability of creating false positive associations, (2) 90% of the post-filtered images result in a normalized gain in match score, (3) frequency filtering doubled the probability of obtaining match scores greater than 30% (for the automated algorithm employed in this study), and (4) filtering can double the probability of obtaining 10 or more matching minutiae when comparing same source prints. Overall, the research indicates a reasonable and quantifiable payoff in increased clarity, matching minutiae and pairwise similarity for post-filtered images when compared to known-match exemplars.

  3. Dynamic Pilot Channel Transmission with Adaptive Receive Filter Configuration for Cognitive Radio System

    NASA Astrophysics Data System (ADS)

    Sakata, Ren; Tomioka, Tazuko; Kobayashi, Takahiro

    When a cognitive radio system dynamically utilizes a frequency band, channel control information must be communicated over the network in order for the currently available carrier frequencies to be shared. In order to keep efficient spectrum utilization, this control information should also be dynamically transmitted through channels such as cognitive pilot channels based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers must receive the control signal without knowledge of its carrier frequencies. A novel scheme called differential code parallel transmission (DCPT) enables receivers to receive low-rate information without any knowledge of the carrier frequency. The transmitter simultaneously transmits two signals whose carrier frequencies are separated by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver receives the DCPT signal, it multiplies the signal by a frequency-shifted version of itself; this yields a DC component that represents the data signal, which is then demodulated. However, the multiplication process results in the noise power being squared, necessitating high received signal power. In this paper, to realize a bandpass filter that passes only DCPT signals of unknown frequency and that suppresses noise and interference at other frequencies, a DCPT-adaptive bandpass filter (ABF) that employs an adaptive equalizer is proposed. In the training phase, the received signal is the filter input and the frequency-shifted signal is the training input. Then, the filter is trained to pass the higher-frequency signal of the two DCPT signals. The performance of DCPT-ABF is evaluated through computer simulations. We find that DCPT-ABF operates successfully even under strong interference.

  4. 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.

  5. CT image artifacts from brachytherapy seed implants: A postprocessing 3D adaptive median filter

    SciTech Connect

    Basran, Parminder S.; Robertson, Andrew; Wells, Derek

    2011-02-15

    Purpose: To design a postprocessing 3D adaptive median filter that minimizes streak artifacts and improves soft-tissue contrast in postoperative CT images of brachytherapy seed implantations. Methods: The filter works by identifying voxels that are likely streaks and estimating more reflective voxel intensity by using voxel intensities in adjacent CT slices and applying a median filter over voxels not identified as seeds. Median values are computed over a 5x5x5 mm region of interest (ROI) within the CT volume. An acrylic phantom simulating a clinical seed implant arrangement and containing nonradioactive seeds was created. Low contrast subvolumes of tissuelike material were also embedded in the phantom. Pre- and postprocessed image quality metrics were compared using the standard deviation of ROIs between the seeds, the CT numbers of low contrast ROIs embedded within the phantom, the signal to noise ratio (SNR), and the contrast to noise ratio (CNR) of the low contrast ROIs. The method was demonstrated with a clinical postimplant CT dataset. Results: After the filter was applied, the standard deviation of CT values in streak artifact regions was significantly reduced from 76.5 to 7.2 HU. Within the observable low contrast plugs, the mean of all ROI standard deviations was significantly reduced from 60.5 to 3.9 HU, SNR significantly increased from 2.3 to 22.4, and CNR significantly increased from 0.2 to 4.1 (all P<0.01). The mean CT in the low contrast plugs remained within 5 HU of the original values. Conclusion: An efficient postprocessing filter that does not require access to projection data, which can be applied irrespective of CT scan parameters has been developed, provided the slice thickness and spacing is 3 mm or less.

  6. Wavefront phase retrieval with multi-aperture Zernike filter for atmospheric sensing and adaptive optics applications

    NASA Astrophysics Data System (ADS)

    Bordbar, Behzad; Farwell, Nathan H.; Vorontsov, Mikhail A.

    2016-09-01

    A novel scintillation resistant wavefront sensor based on a densely packed array of classical Zernike filters, referred to as the multi-aperture Zernike wavefront sensor (MAZ-WFS), is introduced and analyzed through numerical simulations. Wavefront phase reconstruction in the MAZ-WFS is performed using iterative algorithms that are optimized for phase aberration sensing in severe atmospheric turbulence conditions. The results demonstrate the potential of the MAZ-WFS for high-resolution retrieval of turbulence-induced phase aberrations in strong scintillation conditions for atmospheric sensing and adaptive optics applications.

  7. Adaptive modeling and spectral estimation of nonstationary biomedical signals based on Kalman filtering.

    PubMed

    Aboy, Mateo; Márquez, Oscar W; McNames, James; Hornero, Roberto; Trong, Tran; Goldstein, Brahm

    2005-08-01

    We describe an algorithm to estimate the instantaneous power spectral density (PSD) of nonstationary signals. The algorithm is based on a dual Kalman filter that adaptively generates an estimate of the autoregressive model parameters at each time instant. The algorithm exhibits superior PSD tracking performance in nonstationary signals than classical nonparametric methodologies, and does not assume local stationarity of the data. Furthermore, it provides better time-frequency resolution, and is robust to model mismatches. We demonstrate its usefulness by a sample application involving PSD estimation of intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI).

  8. SOGI-FLL Based Adaptive Filter for DSTATCOM Under Variable Supply Frequency

    NASA Astrophysics Data System (ADS)

    Puranik, Vishal; Arya, Sabha Raj

    2016-12-01

    This paper presents an adaptive filter based on second order generalized integrator-frequency locked loop (SOGI-FLL) for distribution static compensator (DSTATCOM) operating under variable supply frequency with nonlinear load. It is observed that under variable supply frequency, the FLL provides an excellent frequency tracking performance. Necessary compensation can be provided by DSTATCOM at any frequency with the help of SOGI-FLL. The MATLAB simulink model of DSTATCOM is developed with SOGI-FLL based control algorithm and rectifier based nonlinear load. This three wire system is simulated in power factor correction and zero voltage regulation mode under variable supply frequency.

  9. Target-adaptive polarimetric synthetic aperture radar target discrimination using maximum average correlation height filters.

    PubMed

    Sadjadi, Firooz A; Mahalanobis, Abhijit

    2006-05-01

    We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.

  10. Adaptive Filtering Methods for Identifying Cross-Frequency Couplings in Human EEG

    PubMed Central

    Van Zaen, Jérôme; Murray, Micah M.; Meuli, Reto A.; Vesin, Jean-Marc

    2013-01-01

    Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations. PMID:23560098

  11. Adaptive filtering methods for identifying cross-frequency couplings in human EEG.

    PubMed

    Van Zaen, Jérôme; Murray, Micah M; Meuli, Reto A; Vesin, Jean-Marc

    2013-01-01

    Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

  12. Minimum variance system identification with application to digital adaptive flight control

    NASA Technical Reports Server (NTRS)

    Kotob, S.; Kaufman, H.

    1975-01-01

    A new on-line minimum variance filter for the identification of systems with additive and multiplicative noise is described which embodies both accuracy and computational efficiency. The resulting filter is shown to use both the covariance of the parameter vector itself and the covariance of the error in identification. A bias reduction scheme can be used to yield asymptotically unbiased estimates. Experimental results for simulated linearized lateral aircraft motion in a digital closed loop mode are presented, showing the utility of the identification schemes.

  13. 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.

  14. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

    NASA Astrophysics Data System (ADS)

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

    2016-10-01

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

  15. 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.

  16. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array.

    PubMed

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J; Urbas, Augustine

    2016-10-10

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed "algorithmic spectrometry". We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

  17. Potential of hybrid adaptive filtering in inflammatory lesion detection from capsule endoscopy images

    PubMed Central

    Charisis, Vasileios S; Hadjileontiadis, Leontios J

    2016-01-01

    A new feature extraction technique for the detection of lesions created from mucosal inflammations in Crohn’s disease, based on wireless capsule endoscopy (WCE) images processing is presented here. More specifically, a novel filtering process, namely Hybrid Adaptive Filtering (HAF), was developed for efficient extraction of lesion-related structural/textural characteristics from WCE images, by employing Genetic Algorithms to the Curvelet-based representation of images. Additionally, Differential Lacunarity (DLac) analysis was applied for feature extraction from the HAF-filtered images. The resulted scheme, namely HAF-DLac, incorporates support vector machines for robust lesion recognition performance. For the training and testing of HAF-DLac, an 800-image database was used, acquired from 13 patients who undertook WCE examinations, where the abnormal cases were grouped into mild and severe, according to the severity of the depicted lesion, for a more extensive evaluation of the performance. Experimental results, along with comparison with other related efforts, have shown that the HAF-DLac approach evidently outperforms them in the field of WCE image analysis for automated lesion detection, providing higher classification results, up to 93.8% (accuracy), 95.2% (sensitivity), 92.4% (specificity) and 92.6% (precision). The promising performance of HAF-DLac paves the way for a complete computer-aided diagnosis system that could support physicians’ clinical practice. PMID:27818583

  18. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

    PubMed Central

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

    2016-01-01

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme. PMID:27721506

  19. Real-time scale-adaptive correlation filters tracker with depth information to handle occlusion

    NASA Astrophysics Data System (ADS)

    Pi, Jiatian; Gu, Yuzhang; Hu, Keli; Cheng, Xiaoliu; Zhan, Yunlong; Wang, Yingguan

    2016-07-01

    In visual object tracking, occlusions significantly undermine the performance of tracking algorithms. RGB-D cameras, such as Microsoft Kinect or the related PrimeSense camera, are widely available to consumers. Great attention has been focused on exploiting depth information for object tracking in recent years. We propose an algorithm that improves the existing correlation filter-based tracker for scale-adaptive tracking. Moreover, we utilize depth information provided by the Kinect camera to handle various types of occlusions. First, the optimal location of the target is obtained by the conventional kernelized correlation filter tracker. Then, we make use of the discriminative correlation filter for scale estimation as an independent part. At last, to further improve the tracking performance under occlusions, we present a simple yet effective occlusion handling mechanism to detect occlusion and recovery. In this mechanism, cluster analysis and object segmentation by K-means method have been applied to depth data. Numerous experiments on Princeton RGB-D tracking dataset demonstrate that the proposed algorithm outperforms several state-of-the-art trackers by successfully dealing with occlusions.

  20. 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

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

    PubMed

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

    2015-10-23

    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.

  2. Digital timing recovery combined with adaptive equalization for optical coherent receivers

    NASA Astrophysics Data System (ADS)

    Zhou, Xian; Chen, Xue; Zhou, Weiqing; Fan, Yangyang; Zhu, Hai; Li, Zhiyu

    2009-11-01

    We propose a novel equalization and timing recovery scheme, which adds an adaptive butterfly-structured equalizer in an all-digital timing recovery loop, for polarization multiplexing (POLMUX) coherent receivers. It resolves an incompatible problem that digital equalizer requires the timing recovered (synchronous) signal and Gardner timing-error detection algorithm requires the equalized signal because of its small tolerance on dispersion. This joint module can complete synchronization, equalization and polarization de-multiplexing simultaneously without any extra computational cost. Finally, we demonstrate the good performance of the new scheme in a 112-Gbit/s POLMUX-NRZ-DQPSK digital optical coherent receiver.

  3. Event synchronous adaptive filter based atrial activity estimation in single-lead atrial fibrillation electrocardiograms.

    PubMed

    Lee, Jeon; Song, Mi-hye; Shin, Dong-gu; Lee, Kyoung-joung

    2012-08-01

    In this paper, an event synchronous adaptive filter (ESAF) is proposed to estimate atrial activity (AA) from a single-lead AF ECG in real time. The proposed ESAF is a kind of adaptive filter designed to have the reference fed with the impulse train synchronized with the R peak in a raw atrial fibrillation (AF) ECG and to input the timely delayed AF ECG into the primary input. To assess the performance, for ten simulated AF ECGs, the cross-correlation coefficient (ρ) and the normalized mean square error (NMSE) between estimated AAs and ten original simulated AAs were calculated and, for ten real AF ECGs, the ventricular residue (VR) in QRS interval and similarity (S) in non-QRS interval were computed. As a result, these four parameters were revealed as ρ = 0.938 ± 0.016 and NMSE = 0.243 ± 0.051 for simulated AF ECGs and VR = 1.190 ± 0.476 and S = 0.967 ± 0.041 for real AF ECGs. These results were found to be better than those of the averaged beat subtraction (ABS) method, which had been previously considered the only way to estimate AA automatically in real time. In conclusion, even with single-lead AF ECGs, the proposed method estimated AAs accurately and calculated the atrial fibrillatory frequencies, the most valuable index in AF maintenance and therapy evaluation, with a remarkably low computational cost.

  4. An adaptive filter model of cerebellar zone C3 as a basis for safe limb control?

    PubMed

    Dean, Paul; Anderson, Sean; Porrill, John; Jörntell, Henrik

    2013-11-15

    The review asks how the adaptive filter model of the cerebellum might be relevant to experimental work on zone C3, one of the most extensively studied regions of cerebellar cortex. As far as features of the cerebellar microcircuit are concerned, the model appears to fit very well with electrophysiological discoveries concerning the importance of molecular layer interneurons and their plasticity, the significance of long-term potentiation and the striking number of silent parallel fibre synapses. Regarding external connectivity and functionality, a key feature of the adaptive filter model is its use of the decorrelation algorithm, which renders it uniquely suited to problems of sensory noise cancellation. However, this capacity can be extended to the avoidance of sensory interference, by appropriate movements of, for example, the eyes in the vestibulo-ocular reflex. Avoidance becomes particularly important when painful signals are involved, and as the climbing fibre input to zone C3 is extremely responsive to nociceptive stimuli, it is proposed that one function of this zone is the avoidance of pain by, for example, adjusting movements of the body to avoid self-harm. This hypothesis appears consistent with evidence from humans and animals concerning the role of the intermediate cerebellum in classically conditioned withdrawal reflexes, but further experiments focusing on conditioned avoidance are required to test the hypothesis more stringently. The proposed architecture may also be useful for automatic self-adjusting damage avoidance in robots, an important consideration for next generation 'soft' robots designed to interact with people.

  5. An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles.

    PubMed

    Johansson, A Torbjorn; White, Paul R

    2011-08-01

    This paper proposes an adaptive filter-based method for detection and frequency estimation of whistle calls, such as the calls of birds and marine mammals, which are typically analyzed in the time-frequency domain using a spectrogram. The approach taken here is based on adaptive notch filtering, which is an established technique for frequency tracking. For application to automatic whistle processing, methods for detection and improved frequency tracking through frequency crossings as well as interfering transients are developed and coupled to the frequency tracker. Background noise estimation and compensation is accomplished using order statistics and pre-whitening. Using simulated signals as well as recorded calls of marine mammals and a human whistled speech utterance, it is shown that the proposed method can detect more simultaneous whistles than two competing spectrogram-based methods while not reporting any false alarms on the example datasets. In one example, it extracts complete 1.4 and 1.8 s bottlenose dolphin whistles successfully through frequency crossings. The method performs detection and estimates frequency tracks even at high sweep rates. The algorithm is also shown to be effective on human whistled utterances.

  6. 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.

  7. A Digitalized Gyroscope System Based on a Modified Adaptive Control Method.

    PubMed

    Xia, Dunzhu; Hu, Yiwei; Ni, Peizhen

    2016-03-04

    In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm.

  8. A Digitalized Gyroscope System Based on a Modified Adaptive Control Method

    PubMed Central

    Xia, Dunzhu; Hu, Yiwei; Ni, Peizhen

    2016-01-01

    In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm. PMID:26959019

  9. Adaptive digital beamforming architecture and algorithm for nulling mainlobe and multiple sidelobe jammers

    NASA Astrophysics Data System (ADS)

    Yu, Kai-Bor; Murrow, David J.

    1999-11-01

    This paper describes a digital beamforming architecture for nulling a mainlobe jammer and multiple sidelobe jammers while maintaining the angle estimation accuracy of the monopulse ratio. A sidelobe jammer canceling adaptive array is cascaded with a mainlobe jammer canceller, imposing a mainlobe maintenance technique or constrained adaptation during sidelobe cancellation process so the results of sidelobe jammer cancellation process do not distort subsequent mainlobe cancellation process. The sidelobe jammers and the mainlobe jammer are thus cancelled sequentially in separate processes. This adaptive digital beamforming technique is for improving radar processing for determining the angular location of a target, and specifically to an improvement in the monopulse technique so as to maintain accuracy of the monopulse ratio in the presence of jamming by adaptive suppression of jamming before forming the sum and difference beams.

  10. Adaptive Learning in Psychology: Wayfinding in the Digital Age

    ERIC Educational Resources Information Center

    Dziuban, Charles D.; Moskal, Patsy D.; Cassisi, Jeffrey; Fawcett, Alexis

    2016-01-01

    This paper presents the results of a pilot study investigating the use of the Realizeit adaptive learning platform to deliver a fully online General Psychology course across two semesters. Through mutual cooperation, UCF and vendor (CCKF) researchers examined students' affective, behavioral, and cognitive reactions to the system. Student survey…

  11. 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

  12. 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

  13. Predicting the Quasar Photometric Reshift with the Sloan Digital Sky Survey Filter System

    NASA Astrophysics Data System (ADS)

    Laubacher, Emily M.; York, Donald G.

    1999-10-01

    Photometric data were obtained for a set of known quasars (QSOs) in five bands with the Sloan Digital Sky Survey (SDSS) filter system for the purpose of testing the ability of the SDSS system to accurately predict the photometric redshift of QSOs. The initial plot of the SDSS photometric redshift versus the measured redshift shows a good relationship, but a lot of scatter. A literature search was conducted on a selected sampling of 49 QSOs, 26 with redshift z <= 0.5 and 23 with 0.5 < z < 2.6, to confirm their accurate identifications as QSOs with their advertised redshifts. This search revealed 10 rejected QSOs which were not QSOs but rather Seyfert galaxies or Narrow Line Objects. Additionally, 11 QSOs were either Broad Absorption Line Systems or had spectra that were in some way incomplete, and therefore, their QSO identification could not be confirmed. The revised plot, with the rejected and unconfirmed QSOs removed, gives an excellent straight line with very little scatter. Although these results are preliminary and for only a small sampling of QSOs, they show that further study of the relationship is warranted and that eventually the SDSS method may be used to accurately predict the photometric redshift of QSOs.

  14. Quantitative phase analysis through scattering media by depth-filtered digital holography

    NASA Astrophysics Data System (ADS)

    Goebel, Sebastian; Jaedicke, Volker; Koukourakis, Nektarios; Wiethoff, Helge; Adinda-Ougba, Adamou; Gerhardt, Nils C.; Welp, Hubert; Hofmann, Martin R.

    2013-02-01

    Digital holography (DH) is capable of providing three-dimensional topological surface profiles with axial resolutions in the nanometer range. To achieve such high resolutions requires an analysis of the phase information of the reflected light by means of numerical reconstruction methods. Unfortunately, the phase analysis of structures located in scattering media is usually disturbed by interference with reflected light from different depths. In contrast, low-coherence interferometry and optical coherence tomography (OCT) use broadband light sources to investigate the sample with a coherence gate providing tomographic measurements in scattering samples with a poorer depth-resolution of a few micrometers. We propose a new approach that allows recovering the phase information even through scattering media. The approach combines both techniques by creating synthesized interference patterns from scanned spectra. After applying an inverse Fourier transform to each spectrum, we yield three-dimensional depth-resolved images. Subsequently, contributions of photons scattered from unwanted regions are suppressed by depth-filtering. The back-transformed data can be considered as multiple synthesized holograms and the corresponding phase information can be extracted directly from the depthfiltered spectra. We used this approach to record and reconstruct holograms of a reflective surface through a scattering layer. Our results demonstrate a proof-of-principle, as the quantitative phase-profile could be recovered and effectively separated from scattering influences. Moreover, additional processing steps could pave the way to further applications, i.e. spectroscopic analysis.

  15. Kalman Filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry.

    PubMed

    Zhang, Yuxin; Chen, Shuo; Deng, Kexin; Chen, Bingyao; Wei, Xing; Yang, Jiafei; Wang, Shi; Ying, Kui

    2017-01-01

    To develop a self-adaptive and fast thermometry method by combining the original hybrid magnetic resonance thermometry method and the bio heat transfer equation (BHTE) model. The proposed Kalman filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry, abbreviated as KalBHT hybrid method, introduced the BHTE model to synthesize a window on the regularization term of the hybrid algorithm, which leads to a self-adaptive regularization both spatially and temporally with change of temperature. Further, to decrease the sensitivity to accuracy of the BHTE model, Kalman filter is utilized to update the window at each iteration time. To investigate the effect of the proposed model, computer heating simulation, phantom microwave heating experiment and dynamic in-vivo model validation of liver and thoracic tumor were conducted in this study. The heating simulation indicates that the KalBHT hybrid algorithm achieves more accurate results without adjusting λ to a proper value in comparison to the hybrid algorithm. The results of the phantom heating experiment illustrate that the proposed model is able to follow temperature changes in the presence of motion and the temperature estimated also shows less noise in the background and surrounding the hot spot. The dynamic in-vivo model validation with heating simulation demonstrates that the proposed model has a higher convergence rate, more robustness to susceptibility problem surrounding the hot spot and more accuracy of temperature estimation. In the healthy liver experiment with heating simulation, the RMSE of the hot spot of the proposed model is reduced to about 50% compared to the RMSE of the original hybrid model and the convergence time becomes only about one fifth of the hybrid model. The proposed model is able to improve the accuracy of the original hybrid algorithm and accelerate the convergence rate of MR temperature estimation.

  16. Digital control of high performance aircraft using adaptive estimation techniques

    NASA Technical Reports Server (NTRS)

    Van Landingham, H. F.; Moose, R. L.

    1977-01-01

    In this paper, an adaptive signal processing algorithm is joined with gain-scheduling for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance STOL aircraft. The actual controller views the nonlinear behavior of the aircraft as equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. Nonlinear behavior is approximated by effective switching of the linear models at random times, with durations reflecting aircraft motion in response to pilot commands.

  17. ADAPTUBL. Adaptive Digitizing and Programming of Turbine Blades

    SciTech Connect

    Ray, L.; Loucks, C.

    1994-04-01

    ADAPTUBL involves adaptively machining cast turbine blades. Due to uncontrollable warpage during solidification of cast parts, each part has unique dimensions. A structured lighting sensor, added to the workspace of a 5-axis machining center, discerns the unique geometry of each part. The processed sensor data is then used to generate the unique, 5-axis tool paths required to perform a high precision machining operation on the tip of each blade.

  18. Tracking the Turn Maneuvering Target Using the Multi-Target Bayes Filter with an Adaptive Estimation of Turn Rate.

    PubMed

    Liu, Zong-Xiang; Wu, De-Hui; Xie, Wei-Xin; Li, Liang-Qun

    2017-02-15

    Tracking the target that maneuvers at a variable turn rate is a challenging problem. The traditional solution for this problem is the use of the switching multiple models technique, which includes several dynamic models with different turn rates for matching the motion mode of the target at each point in time. However, the actual motion mode of a target at any time may be different from all of the dynamic models, because these models are usually limited. To address this problem, we establish a formula for estimating the turn rate of a maneuvering target. By applying the estimation method of the turn rate to the multi-target Bayes (MB) filter, we develop a MB filter with an adaptive estimation of the turn rate, in order to track multiple maneuvering targets. Simulation results indicate that the MB filter with an adaptive estimation of the turn rate, is better than the existing filter at tracking the target that maneuvers at a variable turn rate.

  19. 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.

  20. Regional spatially adaptive total variation super-resolution with spatial information filtering and clustering.

    PubMed

    Yuan, Qiangqiang; Zhang, Liangpei; Shen, Huanfeng

    2013-06-01

    Total variation is used as a popular and effective image prior model in the regularization-based image processing fields. However, as the total variation model favors a piecewise constant solution, the processing result under high noise intensity in the flat regions of the image is often poor, and some pseudoedges are produced. In this paper, we develop a regional spatially adaptive total variation model. Initially, the spatial information is extracted based on each pixel, and then two filtering processes are added to suppress the effect of pseudoedges. In addition, the spatial information weight is constructed and classified with k-means clustering, and the regularization strength in each region is controlled by the clustering center value. The experimental results, on both simulated and real datasets, show that the proposed approach can effectively reduce the pseudoedges of the total variation regularization in the flat regions, and maintain the partial smoothness of the high-resolution image. More importantly, compared with the traditional pixel-based spatial information adaptive approach, the proposed region-based spatial information adaptive total variation model can better avoid the effect of noise on the spatial information extraction, and maintains robustness with changes in the noise intensity in the super-resolution process.

  1. Convergent Aeronautics Solutions (CAS) Showcase Presentation on Mission Adaptive Digital Composite Aerostructure Technologies (MADCAT)

    NASA Technical Reports Server (NTRS)

    Swei, Sean; Cheung, Kenneth

    2016-01-01

    This project is to develop a novel aerostructure concept that takes advantage of emerging digital composite materials and manufacturing methods to build high stiffness-to-density ratio, ultra-light structures that can provide mission adaptive and aerodynamically efficient future N+3N+4 air vehicles.

  2. Effects of Carpal Tunnel Syndrome on adaptation of multi-digit forces to object texture

    PubMed Central

    Afifi, Mostafa; Santello, Marco; Johnston, Jamie A.

    2012-01-01

    Objective The ability to adapt digit forces to object properties requires both anticipatory and feedback-driven control mechanisms which can be disrupted in individuals with a compromised sensorimotor system. Carpal Tunnel Syndrome (CTS) is a median nerve compression neuropathy affecting sensory and motor function in a subset of digits in the hand. Our objective was to examine how CTS patients coordinate anticipatory and feedback-driven control for multi-digit grip force adaptation. Methods We asked CTS patients and healthy controls to grasp, lift, and hold an object with different textures. Results CTS patients effectively adapted their digit forces to changes in object texture, but produced excessive grip forces. CTS patients also produced larger peak force rate profiles with fewer modulations of normal force prior to lift onset than did controls and continued to increase grip force throughout the lift whereas forces were set at lift onset for the controls. Conclusions These findings suggest that CTS patients use less online sensory feedback for fine-tuning their grip forces, relying more on anticipatory control than do healthy controls. Significance These characteristics in force adaptation in CTS patients indicate impaired sensorimotor control which leads to excessive grip forces with the potential to further exacerbate their median nerve compression. PMID:22627019

  3. Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

    PubMed

    Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

    2011-07-01

    In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC.

  4. Adaptive nonseparable vector lifting scheme for digital holographic data compression.

    PubMed

    Xing, Yafei; Kaaniche, Mounir; Pesquet-Popescu, Béatrice; Dufaux, Frédéric

    2015-01-01

    Holographic data play a crucial role in recent three-dimensional imaging as well as microscopic applications. As a result, huge amounts of storage capacity will be involved for this kind of data. Therefore, it becomes necessary to develop efficient hologram compression schemes for storage and transmission purposes. In this paper, we focus on the shifted distance information, obtained by the phase-shifting algorithm, where two sets of difference data need to be encoded. More precisely, a nonseparable vector lifting scheme is investigated in order to exploit the two-dimensional characteristics of the holographic contents. Simulations performed on different digital holograms have shown the effectiveness of the proposed method in terms of bitrate saving and quality of object reconstruction.

  5. The adaptation of health care marketing to the digital era.

    PubMed

    Radu, G; Solomon, M; Gheorghe, C M; Hostiuc, M; Bulescu, I A; Purcarea, V L

    2017-01-01

    The purpose of health care marketing is to learn and understand the needs and desires of prospective patients in order to be able to meet those necessities at the highest standards. A big advantage is the targeting capability of the electronic media that has led to its being used by managers of marketing in medical institutions as means of advertisement when they develop the marketing strategies. Regarding social media, it is safe to say that there are communication platforms that can promote certain behaviours thus influencing decision-making. Through social media, people stay in touch with other people and they can provide a mean for medical institutions to permanently communicate with the existing patients or with the potential ones. In addition, social media can be used in advertising and promoting strategies, by posting information about discounts, offers and advantages of accessing the products provided by a certain institution. A study was conducted on 126 patients of a dental clinic in Bucharest. 126 new patients were selected on a period of 22 months from January 2015 until October 2016. The patients never had any treatment in this clinic and were influenced by the Internet to seek for dental care services. The purpose of this study was to evaluate the digital methods of promoting medical services, bringing new patients to a clinic. The results of the study demonstrated the need for digital methods of promoting medical care services in order to expand a business. A strategic way of thinking in this case implied attracting new patients and offering them quality health care services, which ensured their satisfaction and the probability of their recommending the health facility further. This study revealed an important role of social networking sites in promoting. This high response was probably responsible due to targeted promoting services. Almost all the new patients who completed the form will remain patients of this clinic in future.

  6. The adaptation of health care marketing to the digital era

    PubMed Central

    Radu, G; Solomon, M; Gheorghe, CM; Hostiuc, M; Bulescu, IA; Purcarea, VL

    2017-01-01

    The purpose of health care marketing is to learn and understand the needs and desires of prospective patients in order to be able to meet those necessities at the highest standards. A big advantage is the targeting capability of the electronic media that has led to its being used by managers of marketing in medical institutions as means of advertisement when they develop the marketing strategies. Regarding social media, it is safe to say that there are communication platforms that can promote certain behaviours thus influencing decision-making. Through social media, people stay in touch with other people and they can provide a mean for medical institutions to permanently communicate with the existing patients or with the potential ones. In addition, social media can be used in advertising and promoting strategies, by posting information about discounts, offers and advantages of accessing the products provided by a certain institution. A study was conducted on 126 patients of a dental clinic in Bucharest. 126 new patients were selected on a period of 22 months from January 2015 until October 2016. The patients never had any treatment in this clinic and were influenced by the Internet to seek for dental care services. The purpose of this study was to evaluate the digital methods of promoting medical services, bringing new patients to a clinic. The results of the study demonstrated the need for digital methods of promoting medical care services in order to expand a business. A strategic way of thinking in this case implied attracting new patients and offering them quality health care services, which ensured their satisfaction and the probability of their recommending the health facility further. This study revealed an important role of social networking sites in promoting. This high response was probably responsible due to targeted promoting services. Almost all the new patients who completed the form will remain patients of this clinic in future. PMID:28255375

  7. Complementary Bandwidth Extension Method Using Analog Forward and Digital Inverse Filters and Its Application to Noncontact ECG Measurement

    NASA Astrophysics Data System (ADS)

    Kowada, Daisuke; Ueno, Akinori

    In this paper, we propose a novel method for extending bandwidth of ECG measuring device without deteriorating the baseline tolerance for body motion. The proposed method is realized by synthesizing a two-stage analog forward filter with two different corner frequencies and a digital inverse filter having a corner frequency identical with the higher one of the analog filter. We applied the method to bed-type capacitive ECG sensor which can detect electrocardiographic potential non-intrusively and indirectly. The results demonstrated that the proposed method could precisely recover low-frequency components like T-wave. Furthermore, we confirmed that QTc (corrected QT interval) could be estimated from the recovered wave and that the QTc correlated 0.81 on the average with that obtained from Lead II ECG for seven subjects. These results indicate that the proposed method is useful to screening of long QT syndrome by combining the method with the bed-type capacitive ECG sensor.

  8. Effects of yellow, orange and red filter glasses on the thresholds of a dark-adapted human eye.

    PubMed

    Aarnisalo, E; Pehkonen, P

    1990-04-01

    Effects of 13 different yellow, orange and red (Schott) longpass filter glasses on the extrafoveal thresholds obtained by 3 normal subjects after dark-adaptation were measured using a Goldman-Weekers adaptometer. When filters GG400, GG420, GG435, GG455, GG475, GG495, OG515 and OG530 (cutting off radiation up to 527 nm) were used there was no significant change in the threshold value. However, significantly higher threshold values were obtained with the use of the filters OG550, OG570, OG590, RG610 and RG630.

  9. Singular spectrum analysis and adaptive filtering enhance the functional connectivity analysis of resting state fMRI data.

    PubMed

    Piaggi, Paolo; Menicucci, Danilo; Gentili, Claudio; Handjaras, Giacomo; Gemignani, Angelo; Landi, Alberto

    2014-05-01

    Sources of noise in resting-state fMRI experiments include instrumental and physiological noises, which need to be filtered before a functional connectivity analysis of brain regions is performed. These noisy components show autocorrelated and nonstationary properties that limit the efficacy of standard techniques (i.e. time filtering and general linear model). Herein we describe a novel approach based on the combination of singular spectrum analysis and adaptive filtering, which allows a greater noise reduction and yields better connectivity estimates between regions at rest, providing a new feasible procedure to analyze fMRI data.

  10. Digital redesign of the decentralised adaptive tracker for linear large-scale systems

    NASA Astrophysics Data System (ADS)

    Lin, Ming-Hong; Sheng-Hong Tsai, Jason; Chen, Chia-Wei; Guo, Shu-Mei; Chu, Che-An

    2010-02-01

    A novel digital redesign of the analogue model-reference-based decentralized adaptive tracker is proposed for the sampled-data large scale system consisting of N interconnected linear subsystems, so that the system output will follow any trajectory specified at sampling instant which may not be presented by the analytic reference initially, and shows that the proposed decentralized controller induces a good robustness on the decoupling of the closed-loop controlled system. The adaptation of the analogue controller gain is derived by using the model-reference adaptive control theory based on Lyapunov's method. In this article, it is shown that using the sampled-data decentralized adaptive control system it is theoretically possible to asymptotically track the desired output with a desired performance. It is assumed that all the controllers share their prior information and the principal result is derived when they cooperate implicitly. Based on the prediction-based digital redesign methodology, the optimal digital redesigned tracker for the sampled-data decentralised adaptive control systems is newly proposed. An illustrative example of interconnected linear system is presented to demonstrate the effectiveness of the proposed design methodology.

  11. 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

  12. 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.

  13. 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.

  14. A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

    PubMed

    Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

    2017-01-01

    In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used.

  15. Adaptive wavelet packet-based de-speckling of ultrasound images with bilateral filter.

    PubMed

    Esakkirajan, Sankaralingam; Vimalraj, Chinna Thambi; Muhammed, Rashad; Subramanian, Ganapathi

    2013-12-01

    A new adaptive wavelet packet-based approach to minimize speckle noise in ultrasound images is proposed. This method combines wavelet packet thresholding with a bilateral filter. Here, the best bases after wavelet packet decomposition are selected by comparing the first singular value of all sub-bands, and the noisy coefficients are thresholded using a modified NeighShrink technique. The algorithm is tested with various ultrasound images, and the results, in terms of peak signal-to-noise ratio and mean structural similarity values, are compared with those for some well-known de-speckling techniques. The simulation results indicate that the proposed method has better potential to minimize speckle noise and retain fine details of the ultrasound image.

  16. Automatic seizure detection using correlation integral with nonlinear adaptive denoising and Kalman filter.

    PubMed

    Hongda Wang; Chiu-Sing Choy

    2016-08-01

    The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost. Since this algorithm is tested with long-term scalp EEG, it has the potential to achieve higher performance with intracranial EEG. The clinical value of this algorithm includes providing a pre-judgement to assist the doctor's diagnosis procedure and acting as a reliable warning system in a wearable device for epilepsy patients.

  17. 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.

  18. Adaptive update using visual models for lifting-based motion-compensated temporal filtering

    NASA Astrophysics Data System (ADS)

    Li, Song; Xiong, H. K.; Wu, Feng; Chen, Hong

    2005-03-01

    Motion compensated temporal filtering is a useful framework for fully scalable video compression schemes. However, when supposed motion models cannot represent a real motion perfectly, both the temporal high and the temporal low frequency sub-bands may contain artificial edges, which possibly lead to a decreased coding efficiency, and ghost artifacts appear in the reconstructed video sequence at lower bit rates or in case of temporal scaling. We propose a new technique that is based on utilizing visual models to mitigate ghosting artifacts in the temporal low frequency sub-bands. Specifically, we propose content adaptive update schemes where visual models are used to determine image dependent upper bounds on information to be updated. Experimental results show that the proposed algorithm can significantly improve subjective visual quality of the low-pass temporal frames and at the same time, coding performance can catch or exceed the classical update steps.

  19. Adaptive fused Kalman filter based on imaging laser radar for TAN

    NASA Astrophysics Data System (ADS)

    Gong, Junbin; Xu, Hongbo; Tian, Jinwen; Cheng, Hua; Zhang, Jun

    2007-11-01

    Terrain aided navigation (TAN) is an efficient way to periodically correct the error accumulation of INS. The imaging laser radar is an ideal imaging sensor in TAN for the low-flying aircraft and unmanned air vehicles for the high precision multi-dimensional data acquisition capability and concealable attribute. In this paper, a new framework for applying the laser radar to terrain aided navigation is put forward. Then a new adaptive fused Kalman Filter is proposed to improve the accuracy and robustness. At last, the key factors affected the algorithm are analyzed and the comparative experimentations are presented. The simulating experiments show that the proposed algorithm improves the location accuracy, and has good initial error tolerance and fine robustness. It shows that this approach is a valid solution for the application.

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

    PubMed

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

    2012-02-15

    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.