MIMO signal progressing with RLSCMA algorithm for multi-mode multi-core optical transmission system

NASA Astrophysics Data System (ADS)

Bi, Yuan; Liu, Bo; Zhang, Li-jia; Xin, Xiang-jun; Zhang, Qi; Wang, Yong-jun; Tian, Qing-hua; Tian, Feng; Mao, Ya-ya

2018-01-01

In the process of transmitting signals of multi-mode multi-core fiber, there will be mode coupling between modes. The mode dispersion will also occur because each mode has different transmission speed in the link. Mode coupling and mode dispersion will cause damage to the useful signal in the transmission link, so the receiver needs to deal received signal with digital signal processing, and compensate the damage in the link. We first analyzes the influence of mode coupling and mode dispersion in the process of transmitting signals of multi-mode multi-core fiber, then presents the relationship between the coupling coefficient and dispersion coefficient. Then we carry out adaptive signal processing with MIMO equalizers based on recursive least squares constant modulus algorithm (RLSCMA). The MIMO equalization algorithm offers adaptive equalization taps according to the degree of crosstalk in cores or modes, which eliminates the interference among different modes and cores in space division multiplexing(SDM) transmission system. The simulation results show that the distorted signals are restored efficiently with fast convergence speed.

Correlation processing for correction of phase distortions in subaperture imaging.

PubMed

Tavh, B; Karaman, M

1999-01-01

Ultrasonic subaperture imaging combines synthetic aperture and phased array approaches and permits low-cost systems with improved image quality. In subaperture processing, a large array is synthesized using echo signals collected from a number of receive subapertures by multiple firings of a phased transmit subaperture. Tissue inhomogeneities and displacements in subaperture imaging may cause significant phase distortions on received echo signals. Correlation processing on reference echo signals can be used for correction of the phase distortions, for which the accuracy and robustness are critically limited by the signal correlation. In this study, we explore correlation processing techniques for adaptive subaperture imaging with phase correction for motion and tissue inhomogeneities. The proposed techniques use new subaperture data acquisition schemes to produce reference signal sets with improved signal correlation. The experimental test results were obtained using raw radio frequency (RF) data acquired from two different phantoms with 3.5 MHz, 128-element transducer array. The results show that phase distortions can effectively be compensated by the proposed techniques in real-time adaptive subaperture imaging.

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

PubMed Central

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.

PubMed

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

Ephrin-A/EphA specific co-adaptation as a novel mechanism in topographic axon guidance

PubMed Central

Fiederling, Felix; Weschenfelder, Markus; Fritz, Martin; von Philipsborn, Anne; Bastmeyer, Martin; Weth, Franco

2017-01-01

Genetic hardwiring during brain development provides computational architectures for innate neuronal processing. Thus, the paradigmatic chick retinotectal projection, due to its neighborhood preserving, topographic organization, establishes millions of parallel channels for incremental visual field analysis. Retinal axons receive targeting information from quantitative guidance cue gradients. Surprisingly, novel adaptation assays demonstrate that retinal growth cones robustly adapt towards ephrin-A/EphA forward and reverse signals, which provide the major mapping cues. Computational modeling suggests that topographic accuracy and adaptability, though seemingly incompatible, could be reconciled by a novel mechanism of coupled adaptation of signaling channels. Experimentally, we find such ‘co-adaptation’ in retinal growth cones specifically for ephrin-A/EphA signaling. Co-adaptation involves trafficking of unliganded sensors between the surface membrane and recycling endosomes, and is presumably triggered by changes in the lipid composition of membrane microdomains. We propose that co-adaptative desensitization eventually relies on guidance sensor translocation into cis-signaling endosomes to outbalance repulsive trans-signaling. DOI: http://dx.doi.org/10.7554/eLife.25533.001 PMID:28722651

An accuracy aware low power wireless EEG unit with information content based adaptive data compression.

PubMed

Tolbert, Jeremy R; Kabali, Pratik; Brar, Simeranjit; Mukhopadhyay, Saibal

2009-01-01

We present a digital system for adaptive data compression for low power wireless transmission of Electroencephalography (EEG) data. The proposed system acts as a base-band processor between the EEG analog-to-digital front-end and RF transceiver. It performs a real-time accuracy energy trade-off for multi-channel EEG signal transmission by controlling the volume of transmitted data. We propose a multi-core digital signal processor for on-chip processing of EEG signals, to detect signal information of each channel and perform real-time adaptive compression. Our analysis shows that the proposed approach can provide significant savings in transmitter power with minimal impact on the overall signal accuracy.

Electronic filters, hearing aids and methods

NASA Technical Reports Server (NTRS)

Engebretson, A. Maynard (Inventor)

1995-01-01

An electronic filter for an electroacoustic system. The system has a microphone for generating an electrical output from external sounds and an electrically driven transducer for emitting sound. Some of the sound emitted by the transducer returns to the microphone means to add a feedback contribution to its electrical output. The electronic filter includes a first circuit for electronic processing of the electrical output of the microphone to produce a first signal. An adaptive filter, interconnected with the first circuit, performs electronic processing of the first signal to produce an adaptive output to the first circuit to substantially offset the feedback contribution in the electrical output of the microphone, and the adaptive filter includes means for adapting only in response to polarities of signals supplied to and from the first circuit. Other electronic filters for hearing aids, public address systems and other electroacoustic systems, as well as such systems and methods of operating them are also disclosed.

Electronic filters, hearing aids and methods

NASA Technical Reports Server (NTRS)

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

1991-01-01

An electronic filter for an electroacoustic system. The system has a microphone for generating an electrical output from external sounds and an electrically driven transducer for emitting sound. Some of the sound emitted by the transducer returns to the microphone means to add a feedback contribution to its electical output. The electronic filter includes a first circuit for electronic processing of the electrical output of the microphone to produce a filtered signal. An adaptive filter, interconnected with the first circuit, performs electronic processing of the filtered signal to produce an adaptive output to the first circuit to substantially offset the feedback contribution in the electrical output of the microphone, and the adaptive filter includes means for adapting only in response to polarities of signals supplied to and from the first circuit. Other electronic filters for hearing aids, public address systems and other electroacoustic systems, as well as such systems, and methods of operating them are also disclosed.

Long-term music training modulates the recalibration of audiovisual simultaneity.

PubMed

Jicol, Crescent; Proulx, Michael J; Pollick, Frank E; Petrini, Karin

2018-07-01

To overcome differences in physical transmission time and neural processing, the brain adaptively recalibrates the point of simultaneity between auditory and visual signals by adapting to audiovisual asynchronies. Here, we examine whether the prolonged recalibration process of passively sensed visual and auditory signals is affected by naturally occurring multisensory training known to enhance audiovisual perceptual accuracy. Hence, we asked a group of drummers, of non-drummer musicians and of non-musicians to judge the audiovisual simultaneity of musical and non-musical audiovisual events, before and after adaptation with two fixed audiovisual asynchronies. We found that the recalibration for the musicians and drummers was in the opposite direction (sound leading vision) to that of non-musicians (vision leading sound), and change together with both increased music training and increased perceptual accuracy (i.e. ability to detect asynchrony). Our findings demonstrate that long-term musical training reshapes the way humans adaptively recalibrate simultaneity between auditory and visual signals.

Balancing Vibrations at Harmonic Frequencies by Injecting Harmonic Balancing Signals into the Armature of a Linear Motor/Alternator Coupled to a Stirling Machine

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations at harmonic frequencies are reduced by injecting harmonic balancing signals into the armature of a linear motor/alternator coupled to a Stirling machine. The vibrations are sensed to provide a signal representing the mechanical vibrations. A harmonic balancing signal is generated for selected harmonics of the operating frequency by processing the sensed vibration signal with adaptive filter algorithms of adaptive filters for each harmonic. Reference inputs for each harmonic are applied to the adaptive filter algorithms at the frequency of the selected harmonic. The harmonic balancing signals for all of the harmonics are summed with a principal control signal. The harmonic balancing signals modify the principal electrical drive voltage and drive the motor/alternator with a drive voltage component in opposition to the vibration at each harmonic.

Sequential Adaptive Multi-Modality Target Detection and Classification Using Physics Based Models

DTIC Science & Technology

2006-09-01

estimation," R. Raghuram, R. Raich and A.O. Hero, IEEE Intl. Conf. on Acoustics, Speech , and Signal Processing, Toulouse France, June 2006, <http...can then be solved using off-the-shelf classifiers such as radial basis functions, SVM, or kNN classifier structures. When applied to mine detection we...stage waveform selection for adaptive resource constrained state estimation," 2006 IEEE Intl. Conf. on Acoustics, Speech , and Signal Processing

Adaptive EMG noise reduction in ECG signals using noise level approximation

NASA Astrophysics Data System (ADS)

Marouf, Mohamed; Saranovac, Lazar

2017-12-01

In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

2012-01-01

Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

Adaptive Two Dimensional RLS (Recursive Least Squares) Algorithms

DTIC Science & Technology

1989-03-01

in Monterey wonderful. IX I. INTRODUCTION Adaptive algorithms have been used successfully for many years in a wide range of digital signal...SIMULATION RESULTS The 2-D FRLS algorithm was tested both on computer-generated data and on digitized images. For a baseline reference the 2-D L:rv1S...Alexander, S. T. Adaptivt Signal Processing: Theory and Applications. Springer- Verlag, New York. 1986. 7. Bellanger, Maurice G. Adaptive Digital

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

Driving an Active Vibration Balancer to Minimize Vibrations at the Fundamental and Harmonic Frequencies

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations of a principal machine are reduced at the fundamental and harmonic frequencies by driving the drive motor of an active balancer with balancing signals at the fundamental and selected harmonics. Vibrations are sensed to provide a signal representing the mechanical vibrations. A balancing signal generator for the fundamental and for each selected harmonic processes the sensed vibration signal with adaptive filter algorithms of adaptive filters for each frequency to generate a balancing signal for each frequency. Reference inputs for each frequency are applied to the adaptive filter algorithms of each balancing signal generator at the frequency assigned to the generator. The harmonic balancing signals for all of the frequencies are summed and applied to drive the drive motor. The harmonic balancing signals drive the drive motor with a drive voltage component in opposition to the vibration at each frequency.

On adaptive robustness approach to Anti-Jam signal processing

NASA Astrophysics Data System (ADS)

Poberezhskiy, Y. S.; Poberezhskiy, G. Y.

An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.

Applied digital signal processing systems for vortex flowmeter with digital signal processing.

PubMed

Xu, Ke-Jun; Zhu, Zhi-Hai; Zhou, Yang; Wang, Xiao-Fen; Liu, San-Shan; Huang, Yun-Zhi; Chen, Zhi-Yuan

2009-02-01

The spectral analysis is combined with digital filter to process the vortex sensor signal for reducing the effect of disturbance at low frequency from pipe vibrations and increasing the turndown ratio. Using digital signal processing chip, two kinds of digital signal processing systems are developed to implement these algorithms. One is an integrative system, and the other is a separated system. A limiting amplifier is designed in the input analog condition circuit to adapt large amplitude variation of sensor signal. Some technique measures are taken to improve the accuracy of the output pulse, speed up the response time of the meter, and reduce the fluctuation of the output signal. The experimental results demonstrate the validity of the digital signal processing systems.

Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

NASA Astrophysics Data System (ADS)

Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

2018-05-01

The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

FGF-Dependent, Context-Driven Role for FRS Adapters in the Early Telencephalon

PubMed Central

Gutin, Grigoriy; Blackwood, Christopher A.; Kamatkar, Nachiket G.; Lee, Kyung W.; Fishell, Gordon; Wang, Fen

2017-01-01

FGF signaling, an important component of intercellular communication, is required in many tissues throughout development to promote diverse cellular processes. Whether FGF receptors (FGFRs) accomplish such varied tasks in part by activating different intracellular transducers in different contexts remains unclear. Here, we used the developing mouse telencephalon as an example to study the role of the FRS adapters FRS2 and FRS3 in mediating the functions of FGFRs. Using tissue-specific and germline mutants, we examined the requirement of Frs genes in two FGFR-dependent processes. We found that Frs2 and Frs3 are together required for the differentiation of a subset of medial ganglionic eminence (MGE)-derived neurons, but are dispensable for the survival of early telencephalic precursor cells, in which any one of three FGFRs (FGFR1, FGFR2, or FGFR3) is sufficient for survival. Although FRS adapters are dispensable for ERK-1/2 activation, they are required for AKT activation within the subventricular zone of the developing MGE. Using an FRS2,3-binding site mutant of Fgfr1, we established that FRS adapters are necessary for mediating most or all FGFR1 signaling, not only in MGE differentiation, but also in cell survival, implying that other adapters mediate at least in part the signaling from FGFR2 and FGFR3. Our study provides an example of a contextual role for an intracellular transducer and contributes to our understanding of how FGF signaling plays diverse developmental roles. SIGNIFICANCE STATEMENT FGFs promote a range of developmental processes in many developing tissues and at multiple developmental stages. The mechanisms underlying this multifunctionality remain poorly defined in vivo. Using telencephalon development as an example, we show here that FRS adapters exhibit some selectivity in their requirement for mediating FGF receptor (FGFR) signaling and activating downstream mediators that depend on the developmental process, with a requirement in neuronal differentiation but not cell survival. Differential engagement of FRS and non-FRS intracellular adapters downstream of FGFRs could therefore in principle explain how FGFs play several distinct roles in other developing tissues and developmental stages. PMID:28483978

FGF-Dependent, Context-Driven Role for FRS Adapters in the Early Telencephalon.

PubMed

Nandi, Sayan; Gutin, Grigoriy; Blackwood, Christopher A; Kamatkar, Nachiket G; Lee, Kyung W; Fishell, Gordon; Wang, Fen; Goldfarb, Mitchell; Hébert, Jean M

2017-06-07

FGF signaling, an important component of intercellular communication, is required in many tissues throughout development to promote diverse cellular processes. Whether FGF receptors (FGFRs) accomplish such varied tasks in part by activating different intracellular transducers in different contexts remains unclear. Here, we used the developing mouse telencephalon as an example to study the role of the FRS adapters FRS2 and FRS3 in mediating the functions of FGFRs. Using tissue-specific and germline mutants, we examined the requirement of Frs genes in two FGFR-dependent processes. We found that Frs2 and Frs3 are together required for the differentiation of a subset of medial ganglionic eminence (MGE)-derived neurons, but are dispensable for the survival of early telencephalic precursor cells, in which any one of three FGFRs (FGFR1, FGFR2, or FGFR3) is sufficient for survival. Although FRS adapters are dispensable for ERK-1/2 activation, they are required for AKT activation within the subventricular zone of the developing MGE. Using an FRS2,3-binding site mutant of Fgfr1 , we established that FRS adapters are necessary for mediating most or all FGFR1 signaling, not only in MGE differentiation, but also in cell survival, implying that other adapters mediate at least in part the signaling from FGFR2 and FGFR3. Our study provides an example of a contextual role for an intracellular transducer and contributes to our understanding of how FGF signaling plays diverse developmental roles. SIGNIFICANCE STATEMENT FGFs promote a range of developmental processes in many developing tissues and at multiple developmental stages. The mechanisms underlying this multifunctionality remain poorly defined in vivo Using telencephalon development as an example, we show here that FRS adapters exhibit some selectivity in their requirement for mediating FGF receptor (FGFR) signaling and activating downstream mediators that depend on the developmental process, with a requirement in neuronal differentiation but not cell survival. Differential engagement of FRS and non-FRS intracellular adapters downstream of FGFRs could therefore in principle explain how FGFs play several distinct roles in other developing tissues and developmental stages. Copyright © 2017 the authors 0270-6474/17/375690-09$15.00/0.

An Alternative to Adaptation by Sexual Selection: Habitat Choice.

PubMed

Porter, Cody K; Akcali, Christopher K

2018-06-09

Adaptation in mating signals and preferences has generally been explained by sexual selection. We propose that adaptation in such mating traits might also arise via a non-mutually exclusive process wherein individuals preferentially disperse to habitats where they experience high mating performance. Here we explore the evolutionary implications of this process. Copyright © 2018 Elsevier Ltd. All rights reserved.

Extraction of ECG signal with adaptive filter for hearth abnormalities detection

NASA Astrophysics Data System (ADS)

Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti

2018-04-01

This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.

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.

Capillary Electrophoresis Sensitivity Enhancement Based on Adaptive Moving Average Method.

PubMed

Drevinskas, Tomas; Telksnys, Laimutis; Maruška, Audrius; Gorbatsova, Jelena; Kaljurand, Mihkel

2018-06-05

In the present work, we demonstrate a novel approach to improve the sensitivity of the "out of lab" portable capillary electrophoretic measurements. Nowadays, many signal enhancement methods are (i) underused (nonoptimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation because of a lack of computational power. The described innovative migration velocity-adaptive moving average method uses an optimal averaging window size and can be easily implemented with a microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher-frequency peaks, whereas lower electrophoretic mobility analytes exhibit lower-frequency peaks. On the basis of the obtained data, a migration velocity-adaptive moving average algorithm was created, adapted, and programmed into capillary electrophoresis data-processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method, the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis and other separation methods.

Signaling Network of Environmental Sensing and Adaptation in Plants:. Key Roles of Calcium Ion

NASA Astrophysics Data System (ADS)

Kurusu, Takamitsu; Kuchitsu, Kazuyuki

2011-01-01

Considering the important issues concerning food, environment, and energy that humans are facing in the 21st century, humans mostly depend on plants. Unlike animals which move from an inappropriate environment, plants do not move, but rapidly sense diverse environmental changes or invasion by other organisms such as pathogens and insects in the place they root, and adapt themselves by changing their own bodies, through which they developed adaptability. Whole genetic information corresponding to the blueprints of many biological systems has recently been analyzed, and comparative genomic studies facilitated tracing strategies of each organism in their evolutional processes. Comparison of factors involved in intracellular signal transduction between animals and plants indicated diversification of different gene sets. Reversible binding of Ca2+ to sensor proteins play key roles as a molecular switch both in animals and plants. Molecular mechanisms for signaling network of environmental sensing and adaptation in plants will be discussed with special reference to Ca2+ as a key element in information processing.

Communication system with adaptive noise suppression

NASA Technical Reports Server (NTRS)

Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

2007-01-01

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the 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 unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

Optical signal processing

NASA Astrophysics Data System (ADS)

Vanderlugt, A.

1993-07-01

A quasi-realtime adaptive processing system was used to correct the multipath distortion found in wideband digital radios. The measured power spectral density of the input signal was used to adaptively select one of eight equalization filters which reduce the residual distortion to less than 3.6 dB even for the most severe channel distortion. A related adaptive system was used for signal excision in which we removed narrowband interference from wideband signals with minimum signal distortion. An 8x8 acousto-optic switch in a multimode fiber-optic system was built. Insertion loss is approximately 2-4 dB, signal-to-crosstalk ratio is better than 25 dB, and the reconfiguration time is 880 nsec. Short pulses were detected by using the Fresnel transform. Pulses as short as the theoretical limit of 20 nanoseconds were detected for this system, and separated by as little as 60 nanoseconds or by as much as 17 nanoseconds. All possible acousto-optic scanning configurations were considered and classified into four basic types. A consistent set of design relationships for each of the scanning configurations was developed and presented in both tabular and graphic forms from which a preliminary design is obtained.

Adaptive regularization network based neural modeling paradigm for nonlinear adaptive estimation of cerebral evoked potentials.

PubMed

Zhang, Jian-Hua; Böhme, Johann F

2007-11-01

In this paper we report an adaptive regularization network (ARN) approach to realizing fast blind separation of cerebral evoked potentials (EPs) from background electroencephalogram (EEG) activity with no need to make any explicit assumption on the statistical (or deterministic) signal model. The ARNs are proposed to construct nonlinear EEG and EP signal models. A novel adaptive regularization training (ART) algorithm is proposed to improve the generalization performance of the ARN. Two adaptive neural modeling methods based on the ARN are developed and their implementation and performance analysis are also presented. The computer experiments using simulated and measured visual evoked potential (VEP) data have shown that the proposed ARN modeling paradigm yields computationally efficient and more accurate VEP signal estimation owing to its intrinsic model-free and nonlinear processing characteristics.

Roles of chemical signals in regulation of the adaptive responses to iron deficiency.

PubMed

Liu, Xing Xing; He, Xiao Lin; Jin, Chong Wei

2016-05-03

Iron is an essential micronutrient for plants but is not readily accessible in most calcareous soils. Although the adaptive responses of plants to iron deficiency have been well documented, the signals involved in the regulatory cascade leading to their activation are not well understood to date. Recent studies revealed that chemical compounds, including sucrose, auxin, ethylene and nitric oxide, positively regulated the Fe-deficiency-induced Fe uptake processes in a cooperative manner. Nevertheless, cytokinins, jasmonate and abscisic acid were shown to act as negative signals in transmitting the iron deficiency information. The present mini review is to briefly address the roles of chemical signals in regulation of the adaptive responses to iron deficiency based on the literatures published in recent years.

Adaptation of velocity encoding in synaptically coupled neurons in the fly visual system.

PubMed

Kalb, Julia; Egelhaaf, Martin; Kurtz, Rafael

2008-09-10

Although many adaptation-induced effects on neuronal response properties have been described, it is often unknown at what processing stages in the nervous system they are generated. We focused on fly visual motion-sensitive neurons to identify changes in response characteristics during prolonged visual motion stimulation. By simultaneous recordings of synaptically coupled neurons, we were able to directly compare adaptation-induced effects at two consecutive processing stages in the fly visual motion pathway. This allowed us to narrow the potential sites of adaptation effects within the visual system and to relate them to the properties of signal transfer between neurons. Motion adaptation was accompanied by a response reduction, which was somewhat stronger in postsynaptic than in presynaptic cells. We found that the linear representation of motion velocity degrades during adaptation to a white-noise velocity-modulated stimulus. This effect is caused by an increasingly nonlinear velocity representation rather than by an increase of noise and is similarly strong in presynaptic and postsynaptic neurons. In accordance with this similarity, the dynamics and the reliability of interneuronal signal transfer remained nearly constant. Thus, adaptation is mainly based on processes located in the presynaptic neuron or in more peripheral processing stages. In contrast, changes of transfer properties at the analyzed synapse or in postsynaptic spike generation contribute little to changes in velocity coding during motion adaptation.

Adaptive threshold shearlet transform for surface microseismic data denoising

NASA Astrophysics Data System (ADS)

Tang, Na; Zhao, Xian; Li, Yue; Zhu, Dan

2018-06-01

Random noise suppression plays an important role in microseismic data processing. The microseismic data is often corrupted by strong random noise, which would directly influence identification and location of microseismic events. Shearlet transform is a new multiscale transform, which can effectively process the low magnitude of microseismic data. In shearlet domain, due to different distributions of valid signals and random noise, shearlet coefficients can be shrunk by threshold. Therefore, threshold is vital in suppressing random noise. The conventional threshold denoising algorithms usually use the same threshold to process all coefficients, which causes noise suppression inefficiency or valid signals loss. In order to solve above problems, we propose the adaptive threshold shearlet transform (ATST) for surface microseismic data denoising. In the new algorithm, we calculate the fundamental threshold for each direction subband firstly. In each direction subband, the adjustment factor is obtained according to each subband coefficient and its neighboring coefficients, in order to adaptively regulate the fundamental threshold for different shearlet coefficients. Finally we apply the adaptive threshold to deal with different shearlet coefficients. The experimental denoising results of synthetic records and field data illustrate that the proposed method exhibits better performance in suppressing random noise and preserving valid signal than the conventional shearlet denoising method.

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

An adaptive spatio-temporal Gaussian filter for processing cardiac optical mapping data.

PubMed

Pollnow, S; Pilia, N; Schwaderlapp, G; Loewe, A; Dössel, O; Lenis, G

2018-06-04

Optical mapping is widely used as a tool to investigate cardiac electrophysiology in ex vivo preparations. Digital filtering of fluorescence-optical data is an important requirement for robust subsequent data analysis and still a challenge when processing data acquired from thin mammalian myocardium. Therefore, we propose and investigate the use of an adaptive spatio-temporal Gaussian filter for processing optical mapping signals from these kinds of tissue usually having low signal-to-noise ratio (SNR). We demonstrate how filtering parameters can be chosen automatically without additional user input. For systematic comparison of this filter with standard filtering methods from the literature, we generated synthetic signals representing optical recordings from atrial myocardium of a rat heart with varying SNR. Furthermore, all filter methods were applied to experimental data from an ex vivo setup. Our developed filter outperformed the other filter methods regarding local activation time detection at SNRs smaller than 3 dB which are typical noise ratios expected in these signals. At higher SNRs, the proposed filter performed slightly worse than the methods from literature. In conclusion, the proposed adaptive spatio-temporal Gaussian filter is an appropriate tool for investigating fluorescence-optical data with low SNR. The spatio-temporal filter parameters were automatically adapted in contrast to the other investigated filters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Adaptive Arrays for Weak Interfering Signals: An Experimental System. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ward, James

1987-01-01

An experimental adaptive antenna system was implemented to study the performance of adaptive arrays in the presence of weak interfering signals. It is a sidelobe canceler with two auxiliary elements. Modified feedback loops, which decorrelate the noise components of the two inputs to the loop correlators, control the array weights. Digital processing is used for algorithm implementation and performance evaluation. The results show that the system can suppress interfering signals which are 0 to 10 dB below the thermal noise level in the main channel by 20 to 30 dB. When the desired signal is strong in the auxiliary elements the amount of interference suppression decreases. The amount of degradation depends on the number of interfering signals incident on the communication system. A modified steering vector which overcomes this problem is proposed.

Synthetic aperture radar signal data compression using block adaptive quantization

NASA Technical Reports Server (NTRS)

Kuduvalli, Gopinath; Dutkiewicz, Melanie; Cumming, Ian

1994-01-01

This paper describes the design and testing of an on-board SAR signal data compression algorithm for ESA's ENVISAT satellite. The Block Adaptive Quantization (BAQ) algorithm was selected, and optimized for the various operational modes of the ASAR instrument. A flexible BAQ scheme was developed which allows a selection of compression ratio/image quality trade-offs. Test results show the high quality of the SAR images processed from the reconstructed signal data, and the feasibility of on-board implementation using a single ASIC.

Investigation of FPGA-Based Real-Time Adaptive Digital Pulse Shaping for High-Count-Rate Applications

NASA Astrophysics Data System (ADS)

Saxena, Shefali; Hawari, Ayman I.

2017-07-01

Digital signal processing techniques have been widely used in radiation spectrometry to provide improved stability and performance with compact physical size over the traditional analog signal processing. In this paper, field-programmable gate array (FPGA)-based adaptive digital pulse shaping techniques are investigated for real-time signal processing. National Instruments (NI) NI 5761 14-bit, 250-MS/s adaptor module is used for digitizing high-purity germanium (HPGe) detector's preamplifier pulses. Digital pulse processing algorithms are implemented on the NI PXIe-7975R reconfigurable FPGA (Kintex-7) using the LabVIEW FPGA module. Based on the time separation between successive input pulses, the adaptive shaping algorithm selects the optimum shaping parameters (rise time and flattop time of trapezoid-shaping filter) for each incoming signal. A digital Sallen-Key low-pass filter is implemented to enhance signal-to-noise ratio and reduce baseline drifting in trapezoid shaping. A recursive trapezoid-shaping filter algorithm is employed for pole-zero compensation of exponentially decayed (with two-decay constants) preamplifier pulses of an HPGe detector. It allows extraction of pulse height information at the beginning of each pulse, thereby reducing the pulse pileup and increasing throughput. The algorithms for RC-CR2 timing filter, baseline restoration, pile-up rejection, and pulse height determination are digitally implemented for radiation spectroscopy. Traditionally, at high-count-rate conditions, a shorter shaping time is preferred to achieve high throughput, which deteriorates energy resolution. In this paper, experimental results are presented for varying count-rate and pulse shaping conditions. Using adaptive shaping, increased throughput is accepted while preserving the energy resolution observed using the longer shaping times.

Seeing a haptically explored face: visual facial-expression aftereffect from haptic adaptation to a face.

PubMed

Matsumiya, Kazumichi

2013-10-01

Current views on face perception assume that the visual system receives only visual facial signals. However, I show that the visual perception of faces is systematically biased by adaptation to a haptically explored face. Recently, face aftereffects (FAEs; the altered perception of faces after adaptation to a face) have been demonstrated not only in visual perception but also in haptic perception; therefore, I combined the two FAEs to examine whether the visual system receives face-related signals from the haptic modality. I found that adaptation to a haptically explored facial expression on a face mask produced a visual FAE for facial expression. This cross-modal FAE was not due to explicitly imaging a face, response bias, or adaptation to local features. Furthermore, FAEs transferred from vision to haptics. These results indicate that visual face processing depends on substrates adapted by haptic faces, which suggests that face processing relies on shared representation underlying cross-modal interactions.

Apparatus and Method for Assessing Vestibulo-Ocular Function

NASA Technical Reports Server (NTRS)

Shelhamer, Mark J. (Inventor)

2015-01-01

A system for assessing vestibulo-ocular function includes a motion sensor system adapted to be coupled to a user's head; a data processing system configured to communicate with the motion sensor system to receive the head-motion signals; a visual display system configured to communicate with the data processing system to receive image signals from the data processing system; and a gain control device arranged to be operated by the user and to communicate gain adjustment signals to the data processing system.

Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II

PubMed Central

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

2010-01-01

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

An experimental adaptive array to suppress weak interfering signals

NASA Technical Reports Server (NTRS)

Walton, Eric K.; Gupta, Inder J.; Ksienski, Aharon A.; Ward, James

1988-01-01

An experimental adaptive antenna system to suppress weak interfering signals is described. It is a sidelobe canceller with two auxiliary elements. Modified feedback loops are used to control the array weights. The received signals are simulated in hardware for parameter control. Digital processing is used for algorithm implementation and performance evaluation. The experimental results are presented. They show that interfering signals as much as 10 dB below the thermal noise level in the main channel are suppressed by 20-30 dB. Such a system has potential application in suppressing the interference encountered in direct broadcast satellite communication systems.

Signaling Task Awareness in Think-Aloud Protocols from Students Selecting Relevant Information from Text

ERIC Educational Resources Information Center

Schellings, Gonny L. M.; Broekkamp, Hein

2011-01-01

Self-regulated learning has been described as an adaptive process: students adapt their learning strategies for attaining different learning goals. In order to be adaptive, students must have a clear notion of what the task requirements consist of. Both trace data and questionnaire data indicate that students adapt study strategies in limited ways…

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

Brain processing of visual information during fast eye movements maintains motor performance.

PubMed

Panouillères, Muriel; Gaveau, Valérie; Socasau, Camille; Urquizar, Christian; Pélisson, Denis

2013-01-01

Movement accuracy depends crucially on the ability to detect errors while actions are being performed. When inaccuracies occur repeatedly, both an immediate motor correction and a progressive adaptation of the motor command can unfold. Of all the movements in the motor repertoire of humans, saccadic eye movements are the fastest. Due to the high speed of saccades, and to the impairment of visual perception during saccades, a phenomenon called "saccadic suppression", it is widely believed that the adaptive mechanisms maintaining saccadic performance depend critically on visual error signals acquired after saccade completion. Here, we demonstrate that, contrary to this widespread view, saccadic adaptation can be based entirely on visual information presented during saccades. Our results show that visual error signals introduced during saccade execution--by shifting a visual target at saccade onset and blanking it at saccade offset--induce the same level of adaptation as error signals, presented for the same duration, but after saccade completion. In addition, they reveal that this processing of intra-saccadic visual information for adaptation depends critically on visual information presented during the deceleration phase, but not the acceleration phase, of the saccade. These findings demonstrate that the human central nervous system can use short intra-saccadic glimpses of visual information for motor adaptation, and they call for a reappraisal of current models of saccadic adaptation.

Optimized mode-field adapter for low-loss fused fiber bundle signal and pump combiners

NASA Astrophysics Data System (ADS)

Koška, Pavel; Baravets, Yauhen; Peterka, Pavel; Písařík, Michael; Bohata, Jan

2015-03-01

In our contribution we report novel mode field adapter incorporated inside bundled tapered pump and signal combiner. Pump and signal combiners are crucial component of contemporary double clad high power fiber lasers. Proposed combiner allows simultaneous matching to single mode core on input and output. We used advanced optimization techniques to match the combiner to a single mode core simultaneously on input and output and to minimalize losses of the combiner signal branch. We designed two arrangements of combiners' mode field adapters. Our numerical simulations estimates losses in signal branches of optimized combiners of 0.23 dB for the first design and 0.16 dB for the second design for SMF-28 input fiber and SMF-28 matched output double clad fiber for the wavelength of 2000 nm. The splice losses of the actual combiner are expected to be even lower thanks to dopant diffusion during the splicing process.

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.

Frequency domain laser velocimeter signal processor: A new signal processing scheme

NASA Technical Reports Server (NTRS)

Meyers, James F.; Clemmons, James I., Jr.

1987-01-01

A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a smart instrument that is able to configure itself, based on the characteristics of the input signals, for optimum measurement accuracy. The signal processor is composed of a high-speed 2-bit transient recorder for signal capture and a combination of adaptive digital filters with energy and/or zero crossing detection signal processing. The system is designed to accept signals with frequencies up to 100 MHz with standard deviations up to 20 percent of the average signal frequency. Results from comparative simulation studies indicate measurement accuracies 2.5 times better than with a high-speed burst counter, from signals with as few as 150 photons per burst.

Adaptive Signal Processing Testbed: VME-based DSP board market survey

NASA Astrophysics Data System (ADS)

Ingram, Rick E.

1992-04-01

The Adaptive Signal Processing Testbed (ASPT) is a real-time multiprocessor system utilizing digital signal processor technology on VMEbus based printed circuit boards installed on a Sun workstation. The ASPT has specific requirements, particularly as regards to the signal excision application, with respect to interfacing with current and planned data generation equipment, processing of the data, storage to disk of final and intermediate results, and the development tools for applications development and integration into the overall EW/COM computing environment. A prototype ASPT was implemented using three VME-C-30 boards from Applied Silicon. Experience gained during the prototype development led to the conclusions that interprocessor communications capability is the most significant contributor to overall ASPT performance. In addition, the host involvement should be minimized. Boards using different processors were evaluated with respect to the ASPT system requirements, pricing, and availability. Specific recommendations based on various priorities are made as well as recommendations concerning the integration and interaction of various tools developed during the prototype implementation.

Rapid Structured Volume Grid Smoothing and Adaption Technique

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2006-01-01

A rapid, structured volume grid smoothing and adaption technique, based on signal processing methods, was developed and applied to the Shuttle Orbiter at hypervelocity flight conditions in support of the Columbia Accident Investigation. Because of the fast pace of the investigation, computational aerothermodynamicists, applying hypersonic viscous flow solving computational fluid dynamic (CFD) codes, refined and enhanced a grid for an undamaged baseline vehicle to assess a variety of damage scenarios. Of the many methods available to modify a structured grid, most are time-consuming and require significant user interaction. By casting the grid data into different coordinate systems, specifically two computational coordinates with arclength as the third coordinate, signal processing methods are used for filtering the data [Taubin, CG v/29 1995]. Using a reverse transformation, the processed data are used to smooth the Cartesian coordinates of the structured grids. By coupling the signal processing method with existing grid operations within the Volume Grid Manipulator tool, problems related to grid smoothing are solved efficiently and with minimal user interaction. Examples of these smoothing operations are illustrated for reductions in grid stretching and volume grid adaptation. In each of these examples, other techniques existed at the time of the Columbia accident, but the incorporation of signal processing techniques reduced the time to perform the corrections by nearly 60%. This reduction in time to perform the corrections therefore enabled the assessment of approximately twice the number of damage scenarios than previously possible during the allocated investigation time.

Rapid Structured Volume Grid Smoothing and Adaption Technique

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2004-01-01

A rapid, structured volume grid smoothing and adaption technique, based on signal processing methods, was developed and applied to the Shuttle Orbiter at hypervelocity flight conditions in support of the Columbia Accident Investigation. Because of the fast pace of the investigation, computational aerothermodynamicists, applying hypersonic viscous flow solving computational fluid dynamic (CFD) codes, refined and enhanced a grid for an undamaged baseline vehicle to assess a variety of damage scenarios. Of the many methods available to modify a structured grid, most are time-consuming and require significant user interaction. By casting the grid data into different coordinate systems, specifically two computational coordinates with arclength as the third coordinate, signal processing methods are used for filtering the data [Taubin, CG v/29 1995]. Using a reverse transformation, the processed data are used to smooth the Cartesian coordinates of the structured grids. By coupling the signal processing method with existing grid operations within the Volume Grid Manipulator tool, problems related to grid smoothing are solved efficiently and with minimal user interaction. Examples of these smoothing operations are illustrated for reduction in grid stretching and volume grid adaptation. In each of these examples, other techniques existed at the time of the Columbia accident, but the incorporation of signal processing techniques reduced the time to perform the corrections by nearly 60%. This reduction in time to perform the corrections therefore enabled the assessment of approximately twice the number of damage scenarios than previously possible during the allocated investigation time.

Statistical and Adaptive Signal Processing for UXO Discrimination for Next-Generation Sensor Data

DTIC Science & Technology

2009-09-01

using the energies of all polarizations as features in a KNN classifier variant resulted in 100% probability of detection at a probability of false...International Conference on Acoustics, Speech , and Signal Processing, vol. V, 2005, pp. 885-888. [12] C. Kreucher, K. Kastella, and A. O. Hero

Adaptive signal processing at NOSC

NASA Astrophysics Data System (ADS)

Albert, T. R.

1992-03-01

Adaptive signal processing work at the Naval Ocean Systems Center (NOSC) dates back to the late 1960s. It began as an IR/IED project by John McCool, who made use of an adaptive algorithm that had been developed by Professor Bernard Widrow of Stanford University. In 1972, a team lead by McCool built the first hardware implementation of the algorithm that could process in real-time at acoustic bandwidths. Early tests with the two units that were built were extremely successful, and attracted much attention. Sponsors from different commands provided funding to develop hardware for submarine, surface ship, airborne, and other systems. In addition, an effort was initiated to analyze performance and behavior of the algorithm. Most of the hardware development and analysis efforts were active through the 1970s, and a few into the 1980s. One of the original programs continues to this date.

Fetal Electrocardiogram Extraction and Analysis Using Adaptive Noise Cancellation and Wavelet Transformation Techniques.

PubMed

Sutha, P; Jayanthi, V E

2017-12-08

Birth defect-related demise is mainly due to congenital heart defects. In the earlier stage of pregnancy, fetus problem can be identified by finding information about the fetus to avoid stillbirths. The gold standard used to monitor the health status of the fetus is by Cardiotachography(CTG), cannot be used for long durations and continuous monitoring. There is a need for continuous and long duration monitoring of fetal ECG signals to study the progressive health status of the fetus using portable devices. The non-invasive method of electrocardiogram recording is one of the best method used to diagnose fetal cardiac problem rather than the invasive methods.The monitoring of the fECG requires development of a miniaturized hardware and a efficient signal processing algorithms to extract the fECG embedded in the mother ECG. The paper discusses a prototype hardware developed to monitor and record the raw mother ECG signal containing the fECG and a signal processing algorithm to extract the fetal Electro Cardiogram signal. We have proposed two methods of signal processing, first is based on the Least Mean Square (LMS) Adaptive Noise Cancellation technique and the other method is based on the Wavelet Transformation technique. A prototype hardware was designed and developed to acquire the raw ECG signal containing the mother and fetal ECG and the signal processing techniques were used to eliminate the noises and extract the fetal ECG and the fetal Heart Rate Variability was studied. Both the methods were evaluated with the signal acquired from a fetal ECG simulator, from the Physionet database and that acquired from the subject. Both the methods are evaluated by finding heart rate and its variability, amplitude spectrum and mean value of extracted fetal ECG. Also the accuracy, sensitivity and positive predictive value are also determined for fetal QRS detection technique. In this paper adaptive filtering technique uses Sign-sign LMS algorithm and wavelet techniques with Daubechies wavelet, employed along with de noising techniques for the extraction of fetal Electrocardiogram.Both the methods are having good sensitivity and accuracy. In adaptive method the sensitivity is 96.83, accuracy 89.87, wavelet sensitivity is 95.97 and accuracy is 88.5. Additionally, time domain parameters from the plot of heart rate variability of mother and fetus are analyzed.

Communications interface for wireless communications headset

NASA Technical Reports Server (NTRS)

Culotta, Jr., Anthony Joseph (Inventor); Seibert, Marc A. (Inventor)

2004-01-01

A universal interface adapter circuit interfaces, for example, a wireless communications headset with any type of communications system, including those that require push-to-talk (PTT) signaling. The interface adapter is comprised of several main components, including an RF signaling receiver, a microcontroller and associated circuitry for decoding and processing the received signals, and programmable impedance matching and line interfacing circuitry for interfacing a wireless communications headset system base to a communications system. A signaling transmitter, which is preferably portable (e.g., handheld), is employed by the wireless headset user to send signals to the signaling receiver. In an embodiment of the invention directed specifically to push-to-talk (PTT) signaling, the wireless headset user presses a button on the signaling transmitter when they wish to speak. This sends a signal to the microcontroller which decodes the signal and recognizes the signal as being a PTT request. In response, the microcontroller generates a control signal that closes a switch to complete a voice connection between the headset system base and the communications system so that the user can communicate with the communications system. With this arrangement, the wireless headset can be interfaced to any communications system that requires PTT signaling, without modification of the headset device. In addition, the interface adapter can also be configured to respond to or deliver any other types of signals, such as dual-tone-multiple-frequency (DTMF) tones, and on/off hook signals. The present invention is also scalable, and permits multiple wireless users to operate independently in the same environment through use of a plurality of the interface adapters.

A Novel Approach for Adaptive Signal Processing

NASA Technical Reports Server (NTRS)

Chen, Ya-Chin; Juang, Jer-Nan

1998-01-01

Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

Luminance and chromatic signals interact differently with melanopsin activation to control the pupil light response.

PubMed

Barrionuevo, Pablo A; Cao, Dingcai

2016-09-01

Intrinsically photosensitive retinal ganglion cells (ipRGCs) express the photopigment melanopsin. These cells receive afferent inputs from rods and cones, which provide inputs to the postreceptoral visual pathways. It is unknown, however, how melanopsin activation is integrated with postreceptoral signals to control the pupillary light reflex. This study reports human flicker pupillary responses measured using stimuli generated with a five-primary photostimulator that selectively modulated melanopsin, rod, S-, M-, and L-cone excitations in isolation, or in combination to produce postreceptoral signals. We first analyzed the light adaptation behavior of melanopsin activation and rod and cones signals. Second, we determined how melanopsin is integrated with postreceptoral signals by testing with cone luminance, chromatic blue-yellow, and chromatic red-green stimuli that were processed by magnocellular (MC), koniocellular (KC), and parvocellular (PC) pathways, respectively. A combined rod and melanopsin response was also measured. The relative phase of the postreceptoral signals was varied with respect to the melanopsin phase. The results showed that light adaptation behavior for all conditions was weaker than typical Weber adaptation. Melanopsin activation combined linearly with luminance, S-cone, and rod inputs, suggesting the locus of integration with MC and KC signals was retinal. The melanopsin contribution to phasic pupil responses was lower than luminance contributions, but much higher than S-cone contributions. Chromatic red-green modulation interacted with melanopsin activation nonlinearly as described by a "winner-takes-all" process, suggesting the integration with PC signals might be mediated by a postretinal site.

The design of an adaptive predictive coder using a single-chip digital signal processor

NASA Astrophysics Data System (ADS)

Randolph, M. A.

1985-01-01

A speech coding processor architecture design study has been performed in which Texas Instruments TMS32010 has been selected from among three commercially available digital signal processing integrated circuits and evaluated in an implementation study of real-time Adaptive Predictive Coding (APC). The TMS32010 has been compared with AR&T Bell Laboratories DSP I and Nippon Electric Co. PD7720 and was found to be most suitable for a single chip implementation of APC. A preliminary design system based on TMS32010 has been performed, and several of the hardware and software design issues are discussed. Particular attention was paid to the design of an external memory controller which permits rapid sequential access of external RAM. As a result, it has been determined that a compact hardware implementation of the APC algorithm is feasible based of the TSM32010. Originator-supplied keywords include: vocoders, speech compression, adaptive predictive coding, digital signal processing microcomputers, speech processor architectures, and special purpose processor.

Processing of pulse oximeter signals using adaptive filtering and autocorrelation to isolate perfusion and oxygenation components

NASA Astrophysics Data System (ADS)

Ibey, Bennett; Subramanian, Hariharan; Ericson, Nance; Xu, Weijian; Wilson, Mark; Cote, Gerard L.

2005-03-01

A blood perfusion and oxygenation sensor has been developed for in situ monitoring of transplanted organs. In processing in situ data, motion artifacts due to increased perfusion can create invalid oxygenation saturation values. In order to remove the unwanted artifacts from the pulsatile signal, adaptive filtering was employed using a third wavelength source centered at 810nm as a reference signal. The 810 nm source resides approximately at the isosbestic point in the hemoglobin absorption curve where the absorbance of light is nearly equal for oxygenated and deoxygenated hemoglobin. Using an autocorrelation based algorithm oxygenation saturation values can be obtained without the need for large sampling data sets allowing for near real-time processing. This technique has been shown to be more reliable than traditional techniques and proven to adequately improve the measurement of oxygenation values in varying perfusion states.

[A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

PubMed

Wang, Yulin; Tian, Xuelong

2014-08-01

In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.

An Innovations-Based Noise Cancelling Technique on Inverse Kepstrum Whitening Filter and Adaptive FIR Filter in Beamforming Structure

PubMed Central

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. PMID:22163987

Blind adaptive equalization of polarization-switched QPSK modulation.

PubMed

Millar, David S; Savory, Seb J

2011-04-25

Coherent detection in combination with digital signal processing has recently enabled significant progress in the capacity of optical communications systems. This improvement has enabled detection of optimum constellations for optical signals in four dimensions. In this paper, we propose and investigate an algorithm for the blind adaptive equalization of one such modulation format: polarization-switched quaternary phase shift keying (PS-QPSK). The proposed algorithm, which includes both blind initialization and adaptation of the equalizer, is found to be insensitive to the input polarization state and demonstrates highly robust convergence in the presence of PDL, DGD and polarization rotation.

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems.

PubMed

Wu, Chengwei; Liu, Jianxing; Xiong, Yongyang; Wu, Ligang

2017-06-28

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of ''explosion of complexity''. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

SDR implementation of the receiver of adaptive communication system

NASA Astrophysics Data System (ADS)

Skarzynski, Jacek; Darmetko, Marcin; Kozlowski, Sebastian; Kurek, Krzysztof

2016-04-01

The paper presents software implementation of a receiver forming a part of an adaptive communication system. The system is intended for communication with a satellite placed in a low Earth orbit (LEO). The ability of adaptation is believed to increase the total amount of data transmitted from the satellite to the ground station. Depending on the signal-to-noise ratio (SNR) of the received signal, adaptive transmission is realized using different transmission modes, i.e., different modulation schemes (BPSK, QPSK, 8-PSK, and 16-APSK) and different convolutional code rates (1/2, 2/3, 3/4, 5/6, and 7/8). The receiver consists of a software-defined radio (SDR) module (National Instruments USRP-2920) and a multithread reception software running on Windows operating system. In order to increase the speed of signal processing, the software takes advantage of single instruction multiple data instructions supported by x86 processor architecture.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics.

PubMed

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control.

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics

PubMed Central

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control. PMID:26601042

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

VLSI implementation of a new LMS-based algorithm for noise removal in ECG signal

NASA Astrophysics Data System (ADS)

Satheeskumaran, S.; Sabrigiriraj, M.

2016-06-01

Least mean square (LMS)-based adaptive filters are widely deployed for removing artefacts in electrocardiogram (ECG) due to less number of computations. But they posses high mean square error (MSE) under noisy environment. The transform domain variable step-size LMS algorithm reduces the MSE at the cost of computational complexity. In this paper, a variable step-size delayed LMS adaptive filter is used to remove the artefacts from the ECG signal for improved feature extraction. The dedicated digital Signal processors provide fast processing, but they are not flexible. By using field programmable gate arrays, the pipelined architectures can be used to enhance the system performance. The pipelined architecture can enhance the operation efficiency of the adaptive filter and save the power consumption. This technique provides high signal-to-noise ratio and low MSE with reduced computational complexity; hence, it is a useful method for monitoring patients with heart-related problem.

Multichannel signal enhancement

DOEpatents

Lewis, Paul S.

1990-01-01

A mixed adaptive filter is formulated for the signal processing problem where desired a priori signal information is not available. The formulation generates a least squares problem which enables the filter output to be calculated directly from an input data matrix. In one embodiment, a folded processor array enables bidirectional data flow to solve the recursive problem by back substitution without global communications. In another embodiment, a balanced processor array solves the recursive problem by forward elimination through the array. In a particular application to magnetoencephalography, the mixed adaptive filter enables an evoked response to an auditory stimulus to be identified from only a single trial.

Advanced Communication Processing Techniques

NASA Astrophysics Data System (ADS)

Scholtz, Robert A.

This document contains the proceedings of the workshop Advanced Communication Processing Techniques, held May 14 to 17, 1989, near Ruidoso, New Mexico. Sponsored by the Army Research Office (under Contract DAAL03-89-G-0016) and organized by the Communication Sciences Institute of the University of Southern California, the workshop had as its objective to determine those applications of intelligent/adaptive communication signal processing that have been realized and to define areas of future research. We at the Communication Sciences Institute believe that there are two emerging areas which deserve considerably more study in the near future: (1) Modulation characterization, i.e., the automation of modulation format recognition so that a receiver can reliably demodulate a signal without using a priori information concerning the signal's structure, and (2) the incorporation of adaptive coding into communication links and networks. (Encoders and decoders which can operate with a wide variety of codes exist, but the way to utilize and control them in links and networks is an issue). To support these two new interest areas, one must have both a knowledge of (3) the kinds of channels and environments in which the systems must operate, and of (4) the latest adaptive equalization techniques which might be employed in these efforts.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing.

PubMed

Ölçer, İbrahim; Öncü, Ahmet

2017-06-05

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry ( ϕ -OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ -OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ -OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems.

Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

PubMed Central

Ölçer, İbrahim; Öncü, Ahmet

2017-01-01

Distributed vibration sensing based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) is being widely used in several applications. However, one of the main challenges in coherent detection-based ϕ-OTDR systems is the fading noise, which impacts the detection performance. In addition, typical signal averaging and differentiating techniques are not suitable for detecting high frequency events. This paper presents a new approach for reducing the effect of fading noise in fiber optic distributed acoustic vibration sensing systems without any impact on the frequency response of the detection system. The method is based on temporal adaptive processing of ϕ-OTDR signals. The fundamental theory underlying the algorithm, which is based on signal-to-noise ratio (SNR) maximization, is presented, and the efficacy of our algorithm is demonstrated with laboratory experiments and field tests. With the proposed digital processing technique, the results show that more than 10 dB of SNR values can be achieved without any reduction in the system bandwidth and without using additional optical amplifier stages in the hardware. We believe that our proposed adaptive processing approach can be effectively used to develop fiber optic-based distributed acoustic vibration sensing systems. PMID:28587240

Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

PubMed

Ze Wang; Chi Man Wong; Feng Wan

2017-07-01

An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

Parallel Signal Processing and System Simulation using aCe

NASA Technical Reports Server (NTRS)

Dorband, John E.; Aburdene, Maurice F.

2003-01-01

Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

Adaptive frequency-difference matched field processing for high frequency source localization in a noisy shallow ocean.

PubMed

Worthmann, Brian M; Song, H C; Dowling, David R

2017-01-01

Remote source localization in the shallow ocean at frequencies significantly above 1 kHz is virtually impossible for conventional array signal processing techniques due to environmental mismatch. A recently proposed technique called frequency-difference matched field processing (Δf-MFP) [Worthmann, Song, and Dowling (2015). J. Acoust. Soc. Am. 138(6), 3549-3562] overcomes imperfect environmental knowledge by shifting the signal processing to frequencies below the signal's band through the use of a quadratic product of frequency-domain signal amplitudes called the autoproduct. This paper extends these prior Δf-MFP results to various adaptive MFP processors found in the literature, with particular emphasis on minimum variance distortionless response, multiple constraint method, multiple signal classification, and matched mode processing at signal-to-noise ratios (SNRs) from -20 to +20 dB. Using measurements from the 2011 Kauai Acoustic Communications Multiple University Research Initiative experiment, the localization performance of these techniques is analyzed and compared to Bartlett Δf-MFP. The results show that a source broadcasting a frequency sweep from 11.2 to 26.2 kHz through a 106 -m-deep sound channel over a distance of 3 km and recorded on a 16 element sparse vertical array can be localized using Δf-MFP techniques within average range and depth errors of 200 and 10 m, respectively, at SNRs down to 0 dB.

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

Conflict and disfluency as aversive signals: context-specific processing adjustments are modulated by affective location associations.

PubMed

Dreisbach, Gesine; Reindl, Anna-Lena; Fischer, Rico

2018-03-01

Context-specific processing adjustments are one signature feature of flexible human action control. However, up to now the precise mechanisms underlying these adjustments are not fully understood. Here it is argued that aversive signals produced by conflict- or disfluency-experience originally motivate such context-specific processing adjustments. We tested whether the efficiency of the aversive conflict signal for control adaptation depends on the affective nature of the context it is presented in. In two experiments, high vs. low proportions of aversive signals (Experiment 1: conflict trials; Experiment 2: disfluent trials) were presented either above or below the screen center. This location manipulation was motivated by existing evidence that verticality is generally associated with affective valence with up being positive and down being negative. From there it was hypothesized that the aversive signals would lose their trigger function for processing adjustments when presented at the lower (i.e., more negative) location. This should then result in a reduced context-specific proportion effect when the high proportion of aversive signals was presented at the lower location. Results fully confirmed the predictions. In both experiments, the location-specific proportion effects were only present when the high proportion of aversive signals occurred at the more positive location above but were reduced (Experiment 1) or even eliminated (Experiment 2) when the high proportion occurred at the more negative location below. This interaction of processing adjustments with affective background contexts can thus be taken as further hint for an affective origin of control adaptations.

Adaptive-Adaptive Narrowband Subarray Beamforming

DTIC Science & Technology

1994-02-10

the ML ASA beamformer exhibits some extra noise gain. • In the presence of dominant transition band interferers, the NG ASA beamformer exhibits an...Inc., 87. [8] M. Rendas and J. Moura. Cramer-Rao bound for location systems in multipath environments. IEEE Transactions on Signal Processing, 39

Non-parametric PCM to ADM conversion. [Pulse Code to Adaptive Delta Modulation

NASA Technical Reports Server (NTRS)

Locicero, J. L.; Schilling, D. L.

1977-01-01

An all-digital technique to convert pulse code modulated (PCM) signals into adaptive delta modulation (ADM) format is presented. The converter developed is shown to be independent of the statistical parameters of the encoded signal and can be constructed with only standard digital hardware. The structure of the converter is simple enough to be fabricated on a large scale integrated circuit where the advantages of reliability and cost can be optimized. A concise evaluation of this PCM to ADM translation technique is presented and several converters are simulated on a digital computer. A family of performance curves is given which displays the signal-to-noise ratio for sinusoidal test signals subjected to the conversion process, as a function of input signal power for several ratios of ADM rate to Nyquist rate.

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

Removing damped sinusoidal vibrations in adaptive optics systems using a DFT-based estimation method

NASA Astrophysics Data System (ADS)

Kania, Dariusz

2017-06-01

The problem of a vibrations rejection in adaptive optics systems is still present in publications. These undesirable signals emerge because of shaking the system structure, the tracking process, etc., and they usually are damped sinusoidal signals. There are some mechanical solutions to reduce the signals but they are not very effective. One of software solutions are very popular adaptive methods. An AVC (Adaptive Vibration Cancellation) method has been presented and developed in recent years. The method is based on the estimation of three vibrations parameters and values of frequency, amplitude and phase are essential to produce and adjust a proper signal to reduce or eliminate vibrations signals. This paper presents a fast (below 10 ms) and accurate estimation method of frequency, amplitude and phase of a multifrequency signal that can be used in the AVC method to increase the AO system performance. The method accuracy depends on several parameters: CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, THD, b - number of A/D converter bits in a real time system, γ - the damping ratio of the tested signal, φ - the phase of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value of systematic error for γ = 0.1%, CiR = 1.1 and N = 32 is approximately 10^-4 Hz/Hz. This paper focuses on systematic errors of and effect of the signal phase and values of γ on the results.

The role of strategies in motor learning

PubMed Central

Taylor, Jordan A.; Ivry, Richard B.

2015-01-01

There has been renewed interest in the role of strategies in sensorimotor learning. The combination of new behavioral methods and computational methods has begun to unravel the interaction between processes related to strategic control and processes related to motor adaptation. These processes may operate on very different error signals. Strategy learning is sensitive to goal-based performance error. In contrast, adaptation is sensitive to prediction errors between the desired and actual consequences of a planned movement. The former guides what the desired movement should be, whereas the latter guides how to implement the desired movement. Whereas traditional approaches have favored serial models in which an initial strategy-based phase gives way to more automatized forms of control, it now seems that strategic and adaptive processes operate with considerable independence throughout learning, although the relative weight given the two processes will shift with changes in performance. As such, skill acquisition involves the synergistic engagement of strategic and adaptive processes. PMID:22329960

The correlates of subjective perception of identity and expression in the face network: an fMRI adaptation study

PubMed Central

Fox, Christopher J.; Moon, So Young; Iaria, Giuseppe; Barton, Jason J.S.

2009-01-01

The recognition of facial identity and expression are distinct tasks, with current models hypothesizing anatomic segregation of processing within a face-processing network. Using fMRI adaptation and a region-of-interest approach, we assessed how the perception of identity and expression changes in morphed stimuli affected the signal within this network, by contrasting (a) changes that crossed categorical boundaries of identity or expression with those that did not, and (b) changes that subjects perceived as causing identity or expression to change, versus changes that they perceived as not affecting the category of identity or expression. The occipital face area (OFA) was sensitive to any structural change in a face, whether it was identity or expression, but its signal did not correlate with whether subjects perceived a change or not. Both the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS) showed release from adaptation when subjects perceived a change in either identity or expression, although in the pSTS this effect only occurred when subjects were explicitly attending to expression. The middle superior temporal sulcus (mSTS) showed release from adaptation for expression only, and the precuneus for identity only. The data support models where the OFA is involved in the early perception of facial structure. However, evidence for a functional overlap in the FFA and pSTS, with both identity and expression signals in both areas, argues against a complete independence of identity and expression processing in these regions of the core face-processing network. PMID:18852053

The correlates of subjective perception of identity and expression in the face network: an fMRI adaptation study.

PubMed

Fox, Christopher J; Moon, So Young; Iaria, Giuseppe; Barton, Jason J S

2009-01-15

The recognition of facial identity and expression are distinct tasks, with current models hypothesizing anatomic segregation of processing within a face-processing network. Using fMRI adaptation and a region-of-interest approach, we assessed how the perception of identity and expression changes in morphed stimuli affected the signal within this network, by contrasting (a) changes that crossed categorical boundaries of identity or expression with those that did not, and (b) changes that subjects perceived as causing identity or expression to change, versus changes that they perceived as not affecting the category of identity or expression. The occipital face area (OFA) was sensitive to any structural change in a face, whether it was identity or expression, but its signal did not correlate with whether subjects perceived a change or not. Both the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS) showed release from adaptation when subjects perceived a change in either identity or expression, although in the pSTS this effect only occurred when subjects were explicitly attending to expression. The middle superior temporal sulcus (mSTS) showed release from adaptation for expression only, and the precuneus for identity only. The data support models where the OFA is involved in the early perception of facial structure. However, evidence for a functional overlap in the FFA and pSTS, with both identity and expression signals in both areas, argues against a complete independence of identity and expression processing in these regions of the core face-processing network.

Time-delayed directional beam phased array antenna

DOEpatents

Fund, Douglas Eugene; Cable, John William; Cecil, Tony Myron

2004-10-19

An antenna comprising a phased array of quadrifilar helix or other multifilar antenna elements and a time-delaying feed network adapted to feed the elements. The feed network can employ a plurality of coaxial cables that physically bridge a microstrip feed circuitry to feed power signals to the elements. The cables provide an incremental time delay which is related to their physical lengths, such that replacing cables having a first set of lengths with cables having a second set of lengths functions to change the time delay and shift or steer the antenna's main beam. Alternatively, the coaxial cables may be replaced with a programmable signal processor unit adapted to introduce the time delay using signal processing techniques applied to the power signals.

Adaptive Wiener filtering for improved acquisition of distortion product otoacoustic emissions.

PubMed

Ozdamar, O; Delgado, R E; Rahman, S; Lopez, C

1998-01-01

An innovative acoustic noise canceling method using adaptive Wiener filtering (AWF) was developed for improved acquisition of distortion product otoacoustic emissions (DPOAEs). The system used one microphone placed in the test ear for the primary signal. Noise reference signals were obtained from three different sources: (a) pre-stimulus response from the test ear microphone, (b) post-stimulus response from a microphone placed near the head of the subject and (c) post-stimulus response obtained from a microphone placed in the subject's nontest ear. In order to improve spectral estimation, block averaging of a different number of single sweep responses was used. DPOAE data were obtained from 11 ears of healthy newborns in a well-baby nursery of a hospital under typical noise conditions. Simultaneously obtained recordings from all three microphones were digitized, stored and processed off-line to evaluate the effects of AWF with respect to DPOAE detection and signal-to-noise ratio (SNR) improvement. Results show that compared to standard DPOAE processing, AWF improved signal detection and improved SNR.

Signal processing for distributed sensor concept: DISCO

NASA Astrophysics Data System (ADS)

Rafailov, Michael K.

2007-04-01

Distributed Sensor concept - DISCO proposed for multiplication of individual sensor capabilities through cooperative target engagement. DISCO relies on ability of signal processing software to format, to process and to transmit and receive sensor data and to exploit those data in signal synthesis process. Each sensor data is synchronized formatted, Signal-to-Noise Ration (SNR) enhanced and distributed inside of the sensor network. Signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique that was initially proposed [1] as a way to improve the SNR, reduce data rate and mitigate FPA correlated noise of an individual sensor digital video-signal processing. In Distributed Sensor Concept RAFIL technique is used in segmented way, when constituencies of the technique are spatially and/or temporally separated between transmitters and receivers. Those constituencies include though not limited to two thresholds - one is tuned for optimum probability of detection, the other - to manage required false alarm rate, and limited frame integration placed somewhere between the thresholds as well as formatters, conventional integrators and more. RAFIL allows a non-linear integration that, along with SNR gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability [2]. DISCO architecture allows flexible optimization of SNR gain, data rates and noise suppression on sensor's side and limited integration, re-formatting and final threshold on node's side. DISCO with Recursive Adaptive Frame Integration of Limited data may have flexible architecture that allows segmenting the hardware and software to be best suitable for specific DISCO applications and sensing needs - whatever it is air-or-space platforms, ground terminals or integration of sensors network.

Compressed sensing system considerations for ECG and EMG wireless biosensors.

PubMed

Dixon, Anna M R; Allstot, Emily G; Gangopadhyay, Daibashish; Allstot, David J

2012-04-01

Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and adaptive sampling techniques and several system-level design considerations are presented for CS acquisition systems including sparsity and compression limits, thresholding techniques, encoder bit-precision requirements, and signal recovery algorithms. Simulation studies show that compression factors greater than 16X are achievable for ECG and EMG signals with signal-to-quantization noise ratios greater than 60 dB.

Adaptive control system having hedge unit and related apparatus and methods

NASA Technical Reports Server (NTRS)

Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

2003-01-01

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

Fast reversible learning based on neurons functioning as anisotropic multiplex hubs

NASA Astrophysics Data System (ADS)

Vardi, Roni; Goldental, Amir; Sheinin, Anton; Sardi, Shira; Kanter, Ido

2017-05-01

Neural networks are composed of neurons and synapses, which are responsible for learning in a slow adaptive dynamical process. Here we experimentally show that neurons act like independent anisotropic multiplex hubs, which relay and mute incoming signals following their input directions. Theoretically, the observed information routing enriches the computational capabilities of neurons by allowing, for instance, equalization among different information routes in the network, as well as high-frequency transmission of complex time-dependent signals constructed via several parallel routes. In addition, this kind of hubs adaptively eliminate very noisy neurons from the dynamics of the network, preventing masking of information transmission. The timescales for these features are several seconds at most, as opposed to the imprint of information by the synaptic plasticity, a process which exceeds minutes. Results open the horizon to the understanding of fast and adaptive learning realities in higher cognitive brain's functionalities.

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.

Compensation for the signal processing characteristics of ultrasound B-mode scanners in adaptive speckle reduction.

PubMed

Crawford, D C; Bell, D S; Bamber, J C

1993-01-01

A systematic method to compensate for nonlinear amplification of individual ultrasound B-scanners has been investigated in order to optimise performance of an adaptive speckle reduction (ASR) filter for a wide range of clinical ultrasonic imaging equipment. Three potential methods have been investigated: (1) a method involving an appropriate selection of the speckle recognition feature was successful when the scanner signal processing executes simple logarithmic compressions; (2) an inverse transform (decompression) of the B-mode image was effective in correcting for the measured characteristics of image data compression when the algorithm was implemented in full floating point arithmetic; (3) characterising the behaviour of the statistical speckle recognition feature under conditions of speckle noise was found to be the method of choice for implementation of the adaptive speckle reduction algorithm in limited precision integer arithmetic. In this example, the statistical features of variance and mean were investigated. The third method may be implemented on commercially available fast image processing hardware and is also better suited for transfer into dedicated hardware to facilitate real-time adaptive speckle reduction. A systematic method is described for obtaining ASR calibration data from B-mode images of a speckle producing phantom.

Representation and Processing of Acoustic Information in a Biomimetic Neural Network

DTIC Science & Technology

1992-01-01

Zvorykin, 1959, 1963). Bat biosonar is adapted for use in cells, whose axons form the auditory eighth nerve. Tursiops air, whereas dolphin biosonar is...adapted for use underwater. ears contain approximately 105,000 ganglion cells Bat biosonar signals are relatively long in duration (up to distributed

Adaptive Fourier decomposition based ECG denoising.

PubMed

Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming

2016-10-01

A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Grinding Wheel System

DOEpatents

Malkin, Stephen; Gao, Robert; Guo, Changsheng; Varghese, Biju; Pathare, Sumukh

2003-08-05

A grinding wheel system includes a grinding wheel with at least one embedded sensor. The system also includes an adapter disk containing electronics that process signals produced by each embedded sensor and that transmits sensor information to a data processing platform for further processing of the transmitted information.

Grinding Wheel System

DOEpatents

Malkin, Stephen; Gao, Robert; Guo, Changsheng; Varghese, Biju; Pathare, Sumukh

2006-01-10

A grinding wheel system includes a grinding wheel with at least one embedded sensor. The system also includes an adapter disk containing electronics that process signals produced by each embedded sensor and that transmits sensor information to a data processing platform for further processing of the transmitted information.

Processing of fetal heart rate through non-invasive adaptive system based on recursive least squares algorithm

NASA Astrophysics Data System (ADS)

Fajkus, Marcel; Nedoma, Jan; Martinek, Radek; Vasinek, Vladimir

2017-10-01

In this article, we describe an innovative non-invasive method of Fetal Phonocardiography (fPCG) using fiber-optic sensors and adaptive algorithm for the measurement of fetal heart rate (fHR). Conventional PCG is based on a noninvasive scanning of acoustic signals by means of a microphone placed on the thorax. As for fPCG, the microphone is placed on the maternal abdomen. Our solution is based on patent pending non-invasive scanning of acoustic signals by means of a fiber-optic interferometer. Fiber-optic sensors are resistant to technical artifacts such as electromagnetic interferences (EMI), thus they can be used in situations where it is impossible to use conventional EFM methods, e.g. during Magnetic Resonance Imaging (MRI) examination or in case of delivery in water. The adaptive evaluation system is based on Recursive least squares (RLS) algorithm. Based on real measurements provided on five volunteers with their written consent, we created a simplified dynamic signal model of a distribution of heartbeat sounds (HS) through the human body. Our created model allows us to verification of the proposed adaptive system RLS algorithm. The functionality of the proposed non-invasive adaptive system was verified by objective parameters such as Sensitivity (S+) and Signal to Noise Ratio (SNR).

Rapid Link of Innate Immune Signal to Adaptive Immunity by Brain–Fat Axis

PubMed Central

Kim, Min Soo; Yan, Jingqi; Wu, Wenhe; Zhang, Guo; Zhang, Yalin; Cai, Dongsheng

2015-01-01

Innate immunity signals induced by pathogen/damage-associated molecular patterns are essential for adaptive immune responses, but it is unclear if the brain plays a role in this process. Here we show that while tumor necrosis factor (TNF) quickly increased in the brain of mice following bacterial infection, intra-brain TNF delivery mimicked bacterial infection to rapidly increase peripheral lymphocytes, especially in the spleen and fat. Multiple mouse models revealed that hypothalamic responses to TNF were accountable for this increase of peripheral lymphocytes in response to bacterial infection. Finally, hypothalamic induction of lipolysis was found to mediate the brain's action in promoting this increase in peripheral adaptive immune response. Thus, the brain-fat axis is important for rapidly linking innate immunity to adaptive immunity. PMID:25848866

Robust fundamental frequency estimation in sustained vowels: Detailed algorithmic comparisons and information fusion with adaptive Kalman filtering

PubMed Central

Tsanas, Athanasios; Zañartu, Matías; Little, Max A.; Fox, Cynthia; Ramig, Lorraine O.; Clifford, Gari D.

2014-01-01

There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F0) of speech signals. This study examines ten F0 estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F0 in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F0 estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F0 estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F0 estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F0 estimation is required. PMID:24815269

A FPGA-based Fast Converging Digital Adaptive Filter for Real-time RFI Mitigation on Ground Based Radio Telescopes

NASA Astrophysics Data System (ADS)

Finger, R.; Curotto, F.; Fuentes, R.; Duan, R.; Bronfman, L.; Li, D.

2018-02-01

Radio Frequency Interference (RFI) is a growing concern in the radio astronomy community. Single-dish telescopes are particularly susceptible to RFI. Several methods have been developed to cope with RF-polluted environments, based on flagging, excision, and real-time blanking, among others. All these methods produce some degree of data loss or require assumptions to be made on the astronomical signal. We report the development of a real-time, digital adaptive filter implemented on a Field Programmable Gate Array (FPGA) capable of processing 4096 spectral channels in a 1 GHz of instantaneous bandwidth. The filter is able to cancel a broad range of interference signals and quickly adapt to changes on the RFI source, minimizing the data loss without any assumption on the astronomical or interfering signal properties. The speed of convergence (for a decrease to a 1%) was measured to be 208.1 μs for a broadband noise-like RFI signal and 125.5 μs for a multiple-carrier RFI signal recorded at the FAST radio telescope.

Performance benefits of adaptive, multimicrophone, interference-canceling systems in everyday environments

NASA Astrophysics Data System (ADS)

Desloge, Joseph G.; Zimmer, Martin J.; Zurek, Patrick M.

2004-05-01

Adaptive multimicrophone systems are currently used for a variety of noise-cancellation applications (such as hearing aids) to preserve signals arriving from a particular (target) direction while canceling other (jammer) signals in the environment. Although the performance of these systems is known to degrade with increasing reverberation, there are few measurements of adaptive performance in everyday reverberant environments. In this study, adaptive performance was compared to that of a simple, nonadaptive cardioid microphone to determine a measure of adaptive benefit. Both systems used recordings (at an Fs of 22050 Hz) from the same two omnidirectional microphones, which were separated by 1 cm. Four classes of environment were considered: outdoors, household, parking garage, and public establishment. Sources were either environmental noises (e.g., household appliances, restaurant noise) or a controlled noise source. In all situations, no target was present (i.e., all signals were jammers) to obtain maximal jammer cancellation. Adaptive processing was based upon the Griffiths-Jim generalized sidelobe canceller using filter lengths up to 400 points. Average intelligibility-weighted adaptive benefit levels at a source distance of 1 m were, at most, 1.5 dB for public establishments, 2 dB for household rooms and the parking garage, and 3 dB outdoors. [Work supported by NIOSH.

CMOS image sensor with contour enhancement

NASA Astrophysics Data System (ADS)

Meng, Liya; Lai, Xiaofeng; Chen, Kun; Yuan, Xianghui

2010-10-01

Imitating the signal acquisition and processing of vertebrate retina, a CMOS image sensor with bionic pre-processing circuit is designed. Integration of signal-process circuit on-chip can reduce the requirement of bandwidth and precision of the subsequent interface circuit, and simplify the design of the computer-vision system. This signal pre-processing circuit consists of adaptive photoreceptor, spatial filtering resistive network and Op-Amp calculation circuit. The adaptive photoreceptor unit with a dynamic range of approximately 100 dB has a good self-adaptability for the transient changes in light intensity instead of intensity level itself. Spatial low-pass filtering resistive network used to mimic the function of horizontal cell, is composed of the horizontal resistor (HRES) circuit and OTA (Operational Transconductance Amplifier) circuit. HRES circuit, imitating dendrite of the neuron cell, comprises of two series MOS transistors operated in weak inversion region. Appending two diode-connected n-channel transistors to a simple transconductance amplifier forms the OTA Op-Amp circuit, which provides stable bias voltage for the gate of MOS transistors in HRES circuit, while serves as an OTA voltage follower to provide input voltage for the network nodes. The Op-Amp calculation circuit with a simple two-stage Op-Amp achieves the image contour enhancing. By adjusting the bias voltage of the resistive network, the smoothing effect can be tuned to change the effect of image's contour enhancement. Simulations of cell circuit and 16×16 2D circuit array are implemented using CSMC 0.5μm DPTM CMOS process.

EMD self-adaptive selecting relevant modes algorithm for FBG spectrum signal

NASA Astrophysics Data System (ADS)

Chen, Yong; Wu, Chun-ting; Liu, Huan-lin

2017-07-01

Noise may reduce the demodulation accuracy of fiber Bragg grating (FBG) sensing signal so as to affect the quality of sensing detection. Thus, the recovery of a signal from observed noisy data is necessary. In this paper, a precise self-adaptive algorithm of selecting relevant modes is proposed to remove the noise of signal. Empirical mode decomposition (EMD) is first used to decompose a signal into a set of modes. The pseudo modes cancellation is introduced to identify and eliminate false modes, and then the Mutual Information (MI) of partial modes is calculated. MI is used to estimate the critical point of high and low frequency components. Simulation results show that the proposed algorithm estimates the critical point more accurately than the traditional algorithms for FBG spectral signal. While, compared to the similar algorithms, the signal noise ratio of the signal can be improved more than 10 dB after processing by the proposed algorithm, and correlation coefficient can be increased by 0.5, so it demonstrates better de-noising effect.

Laser Calibration of an Impact Disdrometer

NASA Technical Reports Server (NTRS)

Lane, John E.; Kasparis, Takis; Metzger, Philip T.; Jones, W. Linwood

2014-01-01

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

Development of a Voice Activity Controlled Noise Canceller

PubMed Central

Abid Noor, Ali O.; Samad, Salina Abdul; Hussain, Aini

2012-01-01

In this paper, a variable threshold voice activity detector (VAD) is developed to control the operation of a two-sensor adaptive noise canceller (ANC). The VAD prohibits the reference input of the ANC from containing some strength of actual speech signal during adaptation periods. The novelty of this approach resides in using the residual output from the noise canceller to control the decisions made by the VAD. Thresholds of full-band energy and zero-crossing features are adjusted according to the residual output of the adaptive filter. Performance evaluation of the proposed approach is quoted in terms of signal to noise ratio improvements as well mean square error (MSE) convergence of the ANC. The new approach showed an improved noise cancellation performance when tested under several types of environmental noise. Furthermore, the computational power of the adaptive process is reduced since the output of the adaptive filter is efficiently calculated only during non-speech periods. PMID:22778667

Adaptation to Variance of Stimuli in Drosophila Larva Navigation

NASA Astrophysics Data System (ADS)

Wolk, Jason; Gepner, Ruben; Gershow, Marc

In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Epigenomics and human adaptation to high altitude.

PubMed

Julian, Colleen G

2017-11-01

Over the past decade, major technological and analytical advancements have propelled efforts toward identifying the molecular mechanisms that govern human adaptation to high altitude. Despite remarkable progress with respect to the identification of adaptive genomic signals that are strongly associated with the "hypoxia-tolerant" physiological characteristics of high-altitude populations, many questions regarding the fundamental biological processes underlying human adaptation remain unanswered. Vital to address these enduring questions will be determining the role of epigenetic processes, or non-sequence-based features of the genome, that are not only critical for the regulation of transcriptional responses to hypoxia but heritable across generations. This review proposes that epigenomic processes are involved in shaping patterns of adaptation to high altitude by influencing adaptive potential and phenotypic variability under conditions of limited oxygen supply. Improved understanding of the interaction between genetic, epigenetic, and environmental factors holds great promise to provide deeper insight into the mechanisms underlying human adaptive potential, and clarify its implications for biomedical research. Copyright © 2017 the American Physiological Society.

[An Extraction and Recognition Method of the Distributed Optical Fiber Vibration Signal Based on EMD-AWPP and HOSA-SVM Algorithm].

PubMed

Zhang, Yanjun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong

2016-02-01

Given that the traditional signal processing methods can not effectively distinguish the different vibration intrusion signal, a feature extraction and recognition method of the vibration information is proposed based on EMD-AWPP and HOSA-SVM, using for high precision signal recognition of distributed fiber optic intrusion detection system. When dealing with different types of vibration, the method firstly utilizes the adaptive wavelet processing algorithm based on empirical mode decomposition effect to reduce the abnormal value influence of sensing signal and improve the accuracy of signal feature extraction. Not only the low frequency part of the signal is decomposed, but also the high frequency part the details of the signal disposed better by time-frequency localization process. Secondly, it uses the bispectrum and bicoherence spectrum to accurately extract the feature vector which contains different types of intrusion vibration. Finally, based on the BPNN reference model, the recognition parameters of SVM after the implementation of the particle swarm optimization can distinguish signals of different intrusion vibration, which endows the identification model stronger adaptive and self-learning ability. It overcomes the shortcomings, such as easy to fall into local optimum. The simulation experiment results showed that this new method can effectively extract the feature vector of sensing information, eliminate the influence of random noise and reduce the effects of outliers for different types of invasion source. The predicted category identifies with the output category and the accurate rate of vibration identification can reach above 95%. So it is better than BPNN recognition algorithm and improves the accuracy of the information analysis effectively.

Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control

PubMed Central

Nachstedt, Timo; Tetzlaff, Christian; Manoonpong, Poramate

2017-01-01

Rhythmic neural signals serve as basis of many brain processes, in particular of locomotion control and generation of rhythmic movements. It has been found that specific neural circuits, named central pattern generators (CPGs), are able to autonomously produce such rhythmic activities. In order to tune, shape and coordinate the produced rhythmic activity, CPGs require sensory feedback, i.e., external signals. Nonlinear oscillators are a standard model of CPGs and are used in various robotic applications. A special class of nonlinear oscillators are adaptive frequency oscillators (AFOs). AFOs are able to adapt their frequency toward the frequency of an external periodic signal and to keep this learned frequency once the external signal vanishes. AFOs have been successfully used, for instance, for resonant tuning of robotic locomotion control. However, the choice of parameters for a standard AFO is characterized by a trade-off between the speed of the adaptation and its precision and, additionally, is strongly dependent on the range of frequencies the AFO is confronted with. As a result, AFOs are typically tuned such that they require a comparably long time for their adaptation. To overcome the problem, here, we improve the standard AFO by introducing a novel adaptation mechanism based on dynamical coupling strengths. The dynamical adaptation mechanism enhances both the speed and precision of the frequency adaptation. In contrast to standard AFOs, in this system, the interplay of dynamics on short and long time scales enables fast as well as precise adaptation of the oscillator for a wide range of frequencies. Amongst others, a very natural implementation of this mechanism is in terms of neural networks. The proposed system enables robotic applications which require fast retuning of locomotion control in order to react to environmental changes or conditions. PMID:28377710

Adaptive Filtering in the Wavelet Transform Domain Via Genetic Algorithms

DTIC Science & Technology

2004-08-01

inverse transform process. 2. BACKGROUND The image processing research conducted at the AFRL/IFTA Reconfigurable Computing Laboratory has been...coefficients from the wavelet domain back into the original signal domain. In other words, the inverse transform produces the original signal x(t) from the...coefficients for an inverse wavelet transform, such that the MSE of images reconstructed by this inverse transform is significantly less than the mean squared

Auditory fovea and Doppler shift compensation: adaptations for flutter detection in echolocating bats using CF-FM signals.

PubMed

Schnitzler, Hans-Ulrich; Denzinger, Annette

2011-05-01

Rhythmical modulations in insect echoes caused by the moving wings of fluttering insects are behaviourally relevant information for bats emitting CF-FM signals with a high duty cycle. Transmitter and receiver of the echolocation system in flutter detecting foragers are especially adapted for the processing of flutter information. The adaptations of the transmitter are indicated by a flutter induced increase in duty cycle, and by Doppler shift compensation (DSC) that keeps the carrier frequency of the insect echoes near a reference frequency. An adaptation of the receiver is the auditory fovea on the basilar membrane, a highly expanded frequency representation centred to the reference frequency. The afferent projections from the fovea lead to foveal areas with an overrepresentation of sharply tuned neurons with best frequencies near the reference frequency throughout the entire auditory pathway. These foveal neurons are very sensitive to stimuli with natural and simulated flutter information. The frequency range of the foveal areas with their flutter processing neurons overlaps exactly with the frequency range where DS compensating bats most likely receive echoes from fluttering insects. This tight match indicates that auditory fovea and DSC are adaptations for the detection and evaluation of insects flying in clutter.

Parallel Implementation of the Wideband DOA Algorithm on the IBM Cell BE Processor

DTIC Science & Technology

2010-05-01

Abstract—The Multiple Signal Classification ( MUSIC ) algorithm is a powerful technique for determining the Direction of Arrival (DOA) of signals...Broadband Engine Processor (Cell BE). The process of adapting the serial based MUSIC algorithm to the Cell BE will be analyzed in terms of parallelism and...using Multiple Signal Classification MUSIC algorithm [4] • Computation of Focus matrix • Computation of number of sources • Separation of Signal

Applications of digital processing for noise removal from plasma diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kane, R.J.; Candy, J.V.; Casper, T.A.

1985-11-11

The use of digital signal techniques for removal of noise components present in plasma diagnostic signals is discussed, particularly with reference to diamagnetic loop signals. These signals contain noise due to power supply ripple in addition to plasma characteristics. The application of noise canceling techniques, such as adaptive noise canceling and model-based estimation, will be discussed. The use of computer codes such as SIG is described. 19 refs., 5 figs.

Employment of adaptive learning techniques for the discrimination of acoustic emissions

NASA Astrophysics Data System (ADS)

Erkes, J. W.; McDonald, J. F.; Scarton, H. A.; Tam, K. C.; Kraft, R. P.

1983-11-01

The following aspects of this study on the discrimination of acoustic emissions (AE) were examined: (1) The analytical development and assessment of digital signal processing techniques for AE signal dereverberation, noise reduction, and source characterization; (2) The modeling and verification of some aspects of key selected techniques through a computer-based simulation; and (3) The study of signal propagation physics and their effect on received signal characteristics for relevant physical situations.

Simulation for noise cancellation using LMS adaptive filter

NASA Astrophysics Data System (ADS)

Lee, Jia-Haw; Ooi, Lu-Ean; Ko, Ying-Hao; Teoh, Choe-Yung

2017-06-01

In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.

GMTI Direction of Arrival Measurements from Multiple Phase Centers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin W.; Bickel, Douglas L.

2015-03-01

Ground Moving Target Indicator (GMTI) radar attempts to detect and locate targets with unknown motion. Very slow-moving targets are difficult to locate in the presence of surrounding clutter. This necessitates multiple antenna phase centers (or equivalent) to offer independent Direction of Arrival (DOA) measurements. DOA accuracy and precision generally remains dependent on target Signal-to-Noise Ratio (SNR), Clutter-toNoise Ratio (CNR), scene topography, interfering signals, and a number of antenna parameters. This is true even for adaptive techniques like Space-Time-AdaptiveProcessing (STAP) algorithms.

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2015-01-01

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

Closed-form expressions of some stochastic adapting equations for nonlinear adaptive activation function neurons.

PubMed

Fiori, Simone

2003-12-01

In recent work, we introduced nonlinear adaptive activation function (FAN) artificial neuron models, which learn their activation functions in an unsupervised way by information-theoretic adapting rules. We also applied networks of these neurons to some blind signal processing problems, such as independent component analysis and blind deconvolution. The aim of this letter is to study some fundamental aspects of FAN units' learning by investigating the properties of the associated learning differential equation systems.

Experimental demonstration of real-time adaptively modulated DDO-OFDM systems with a high spectral efficiency up to 5.76bit/s/Hz transmission over SMF links.

PubMed

Chen, Ming; He, Jing; Tang, Jin; Wu, Xian; Chen, Lin

2014-07-28

In this paper, a FPGAs-based real-time adaptively modulated 256/64/16QAM-encoded base-band OFDM transceiver with a high spectral efficiency up to 5.76bit/s/Hz is successfully developed, and experimentally demonstrated in a simple intensity-modulated direct-detection optical communication system. Experimental results show that it is feasible to transmit a raw signal bit rate of 7.19Gbps adaptively modulated real-time optical OFDM signal over 20km and 50km single mode fibers (SMFs). The performance comparison between real-time and off-line digital signal processing is performed, and the results show that there is a negligible power penalty. In addition, to obtain the best transmission performance, direct-current (DC) bias voltage for MZM and launch power into optical fiber links are explored in the real-time optical OFDM systems.

Adaptive tracking of a time-varying field with a quantum sensor

NASA Astrophysics Data System (ADS)

Bonato, Cristian; Berry, Dominic W.

2017-05-01

Sensors based on single spins can enable magnetic-field detection with very high sensitivity and spatial resolution. Previous work has concentrated on sensing of a constant magnetic field or a periodic signal. Here, we instead investigate the problem of estimating a field with nonperiodic variation described by a Wiener process. We propose and study, by numerical simulations, an adaptive tracking protocol based on Bayesian estimation. The tracking protocol updates the probability distribution for the magnetic field based on measurement outcomes and adapts the choice of sensing time and phase in real time. By taking the statistical properties of the signal into account, our protocol strongly reduces the required measurement time. This leads to a reduction of the error in the estimation of a time-varying signal by up to a factor of four compare with protocols that do not take this information into account.

Controlling gain one photon at a time

PubMed Central

Schwartz, Gregory W; Rieke, Fred

2013-01-01

Adaptation is a salient property of sensory processing. All adaptational or gain control mechanisms face the challenge of obtaining a reliable estimate of the property of the input to be adapted to and obtaining this estimate sufficiently rapidly to be useful. Here, we explore how the primate retina balances the need to change gain rapidly and reliably when photons arrive rarely at individual rod photoreceptors. We find that the weakest backgrounds that decrease the gain of the retinal output signals are similar to those that increase human behavioral threshold, and identify a novel site of gain control in the retinal circuitry. Thus, surprisingly, the gain of retinal signals begins to decrease essentially as soon as background lights are detectable; under these conditions, gain control does not rely on a highly averaged estimate of the photon count, but instead signals from individual photon absorptions trigger changes in gain. DOI: http://dx.doi.org/10.7554/eLife.00467.001 PMID:23682314

Adaptive Optical Processor

DTIC Science & Technology

1991-08-01

spatial light modulator, Dr. George Brost and I LT Edward Toughlian who helped "trouble-shoot" many of the problems that came up, Mr. Paul Repak and Mr...RADC-TR-89-226, (1989). 8. Welstead, S.T., M.J. Ward, D.M. Blanchard, G.A. Brost , S.L Halby, "Adaptive signal processing using a liquid crystal

Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: I dynamics.

PubMed

Zheng, Lei; Nikolaev, Anton; Wardill, Trevor J; O'Kane, Cahir J; de Polavieja, Gonzalo G; Juusola, Mikko

2009-01-01

Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1-R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II).

Network Adaptation Improves Temporal Representation of Naturalistic Stimuli in Drosophila Eye: I Dynamics

PubMed Central

Wardill, Trevor J.; O'Kane, Cahir J.; de Polavieja, Gonzalo G.; Juusola, Mikko

2009-01-01

Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1–R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II). PMID:19180196

Active Hearing Mechanisms Inspire Adaptive Amplification in an Acoustic Sensor System.

PubMed

Guerreiro, Jose; Reid, Andrew; Jackson, Joseph C; Windmill, James F C

2018-06-01

Over many millions of years of evolution, nature has developed some of the most adaptable sensors and sensory systems possible, capable of sensing, conditioning and processing signals in a very power- and size-effective manner. By looking into biological sensors and systems as a source of inspiration, this paper presents the study of a bioinspired concept of signal processing at the sensor level. By exploiting a feedback control mechanism between a front-end acoustic receiver and back-end neuronal based computation, a nonlinear amplification with hysteretic behavior is created. Moreover, the transient response of the front-end acoustic receiver can also be controlled and enhanced. A theoretical model is proposed and the concept is prototyped experimentally through an embedded system setup that can provide dynamic adaptations of a sensory system comprising a MEMS microphone placed in a closed-loop feedback system. It faithfully mimics the mosquito's active hearing response as a function of the input sound intensity. This is an adaptive acoustic sensor system concept that can be exploited by sensor and system designers within acoustics and ultrasonic engineering fields.

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sideris, Michael G.

2017-09-01

Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63-84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10-30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.

On recursive least-squares filtering algorithms and implementations. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Hsieh, Shih-Fu

1990-01-01

In many real-time signal processing applications, fast and numerically stable algorithms for solving least-squares problems are necessary and important. In particular, under non-stationary conditions, these algorithms must be able to adapt themselves to reflect the changes in the system and take appropriate adjustments to achieve optimum performances. Among existing algorithms, the QR-decomposition (QRD)-based recursive least-squares (RLS) methods have been shown to be useful and effective for adaptive signal processing. In order to increase the speed of processing and achieve high throughput rate, many algorithms are being vectorized and/or pipelined to facilitate high degrees of parallelism. A time-recursive formulation of RLS filtering employing block QRD will be considered first. Several methods, including a new non-continuous windowing scheme based on selectively rejecting contaminated data, were investigated for adaptive processing. Based on systolic triarrays, many other forms of systolic arrays are shown to be capable of implementing different algorithms. Various updating and downdating systolic algorithms and architectures for RLS filtering are examined and compared in details, which include Householder reflector, Gram-Schmidt procedure, and Givens rotation. A unified approach encompassing existing square-root-free algorithms is also proposed. For the sinusoidal spectrum estimation problem, a judicious method of separating the noise from the signal is of great interest. Various truncated QR methods are proposed for this purpose and compared to the truncated SVD method. Computer simulations provided for detailed comparisons show the effectiveness of these methods. This thesis deals with fundamental issues of numerical stability, computational efficiency, adaptivity, and VLSI implementation for the RLS filtering problems. In all, various new and modified algorithms and architectures are proposed and analyzed; the significance of any of the new method depends crucially on specific application.

Adaptive Filtering in the Wavelet Transform Domain via Genetic Algorithms

DTIC Science & Technology

2004-08-06

wavelet transforms. Whereas the term “evolved” pertains only to the altered wavelet coefficients used during the inverse transform process. 2...words, the inverse transform produces the original signal x(t) from the wavelet and scaling coefficients. )()( ,, tdtx nk n nk k ψ...reconstruct the original signal as accurately as possible. The inverse transform reconstructs an approximation of the original signal (Burrus

Benefits of adaptive FM systems on speech recognition in noise for listeners who use hearing aids.

PubMed

Thibodeau, Linda

2010-06-01

To compare the benefits of adaptive FM and fixed FM systems through measurement of speech recognition in noise with adults and students in clinical and real-world settings. Five adults and 5 students with moderate-to-severe hearing loss completed objective and subjective speech recognition in noise measures with the 2 types of FM processing. Sentence recognition was evaluated in a classroom for 5 competing noise levels ranging from 54 to 80 dBA while the FM microphone was positioned 6 in. from the signal loudspeaker to receive input at 84 dB SPL. The subjective measures included 2 classroom activities and 6 auditory lessons in a noisy, public aquarium. On the objective measures, adaptive FM processing resulted in significantly better speech recognition in noise than fixed FM processing for 68- and 73-dBA noise levels. On the subjective measures, all individuals preferred adaptive over fixed processing for half of the activities. Adaptive processing was also preferred by most (8-9) individuals for the remaining 4 activities. The adaptive FM processing resulted in significant improvements at the higher noise levels and was preferred by the majority of participants in most of the conditions.

Packet communications in satellites with multiple-beam antennas and signal processing

NASA Technical Reports Server (NTRS)

Davies, R.; Chethik, F.; Penick, M.

1980-01-01

A communication satellite with a multiple-beam antenna and onboard signal processing is considered for use in a 'message-switched' data relay system. The signal processor may incorporate demodulation, routing, storage, and remodulation of the data. A system user model is established and key functional elements for the signal processing are identified. With the throughput and delay requirements as the controlled variables, the hardware complexity, operational discipline, occupied bandwidth, and overall user end-to-end cost are estimated for (1) random-access packet switching; and (2) reservation-access packet switching. Other aspects of this network (eg, the adaptability to channel switched traffic requirements) are examined. For the given requirements and constraints, the reservation system appears to be the most attractive protocol.

The effect of hearing aid technologies on listening in an automobile.

PubMed

Wu, Yu-Hsiang; Stangl, Elizabeth; Bentler, Ruth A; Stanziola, Rachel W

2013-06-01

Communication while traveling in an automobile often is very difficult for hearing aid users. This is because the automobile/road noise level is usually high, and listeners/drivers often do not have access to visual cues. Since the talker of interest usually is not located in front of the listener/driver, conventional directional processing that places the directivity beam toward the listener's front may not be helpful and, in fact, could have a negative impact on speech recognition (when compared to omnidirectional processing). Recently, technologies have become available in commercial hearing aids that are designed to improve speech recognition and/or listening effort in noisy conditions where talkers are located behind or beside the listener. These technologies include (1) a directional microphone system that uses a backward-facing directivity pattern (Back-DIR processing), (2) a technology that transmits audio signals from the ear with the better signal-to-noise ratio (SNR) to the ear with the poorer SNR (Side-Transmission processing), and (3) a signal processing scheme that suppresses the noise at the ear with the poorer SNR (Side-Suppression processing). The purpose of the current study was to determine the effect of (1) conventional directional microphones and (2) newer signal processing schemes (Back-DIR, Side-Transmission, and Side-Suppression) on listener's speech recognition performance and preference for communication in a traveling automobile. A single-blinded, repeated-measures design was used. Twenty-five adults with bilateral symmetrical sensorineural hearing loss aged 44 through 84 yr participated in the study. The automobile/road noise and sentences of the Connected Speech Test (CST) were recorded through hearing aids in a standard van moving at a speed of 70 mph on a paved highway. The hearing aids were programmed to omnidirectional microphone, conventional adaptive directional microphone, and the three newer schemes. CST sentences were presented from the side and back of the hearing aids, which were placed on the ears of a manikin. The recorded stimuli were presented to listeners via earphones in a sound-treated booth to assess speech recognition performance and preference with each programmed condition. Compared to omnidirectional microphones, conventional adaptive directional processing had a detrimental effect on speech recognition when speech was presented from the back or side of the listener. Back-DIR and Side-Transmission processing improved speech recognition performance (relative to both omnidirectional and adaptive directional processing) when speech was from the back and side, respectively. The performance with Side-Suppression processing was better than with adaptive directional processing when speech was from the side. The participants' preferences for a given processing scheme were generally consistent with speech recognition results. The finding that performance with adaptive directional processing was poorer than with omnidirectional microphones demonstrates the importance of selecting the correct microphone technology for different listening situations. The results also suggest the feasibility of using hearing aid technologies to provide a better listening experience for hearing aid users in automobiles. American Academy of Audiology.

ERK activation is required for CCK-mediated pancreatic adaptive growth in mice

PubMed Central

Holtz, Bryan J.; Lodewyk, Kevin B.; Sebolt-Leopold, Judith S.; Ernst, Stephen A.

2014-01-01

High levels of cholecystokinin (CCK) can stimulate pancreatic adaptive growth in which mature acinar cells divide, leading to enhanced pancreatic mass with parallel increases in protein, DNA, RNA, and digestive enzyme content. Prolonged release of CCK can be induced by feeding trypsin inhibitor (TI) to disrupt normal feedback control. This leads to exocrine growth in a CCK-dependent manner. The extracellular signal-related kinase (ERK) pathway regulates many proliferative processes in various tissues and disease models. The aim of this study was to evaluate the role of ERK signaling in pancreatic adaptive growth using the MEK inhibitors PD-0325901 and trametinib (GSK-1120212). It was determined that PD-0325901 given two times daily by gavage or mixed into powdered chow was an effective and specific inhibitor of ERK signaling in vivo. TI-containing chow led to a robust increase in pancreatic mass, protein, DNA, and RNA content. This pancreatic adaptive growth was blocked in mice fed chow containing the MEK inhibitors. PD-0325901 blocked TI-induced ERK-regulated early response genes, cell-cycle proteins, and mitogenesis by acinar cells. It was determined that ERK signaling is necessary for the initiation of pancreatic adaptive growth but not necessary to maintain it. PD-0325901 blocked adaptive growth when given before cell-cycle initiation but not after mitogenesis had been established. Furthermore, GSK-1120212, a chemically distinct inhibitor of the ERK pathway that is now approved for clinical use, inhibited growth similar to PD-0325901. These data demonstrate that the ERK pathway is required for CCK-stimulated pancreatic adaptive growth. PMID:25104499

Demodulation signal processing in multiphoton imaging

NASA Astrophysics Data System (ADS)

Fisher, Walter G.; Wachter, Eric A.; Piston, David W.

2002-06-01

Multiphoton laser scanning microscopy offers numerous advantages, but sensitivity can be seriously affected by contamination from ambient room light. Typically, this forces experiments to be performed in an absolutely dark room. Since mode-locked lasers are used to generate detectable signals, signal-processing can be used to avoid such problems by taking advantage of the pulsed characteristics of such lasers. Demodulation of the fluorescence signal generated at the mode-locked frequency can result in significant reduction of interference from ambient noise sources. Such demodulation can be readily adapted to existing microscopes by inserting appropriate processor circuitry between the detector and data collection system, yielding a more robust microscope.

The Novel Nonlinear Adaptive Doppler Shift Estimation Technique and the Coherent Doppler Lidar System Validation Lidar

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.

2006-01-01

The signal processing aspect of a 2-m wavelength coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The lidar system is named VALIDAR (validation lidar) and its signal processing program estimates and displays various wind parameters in real-time as data acquisition occurs. The goal is to improve the quality of the current estimates such as power, Doppler shift, wind speed, and wind direction, especially in low signal-to-noise-ratio (SNR) regime. A novel Nonlinear Adaptive Doppler Shift Estimation Technique (NADSET) is developed on such behalf and its performance is analyzed using the wind data acquired over a long period of time by VALIDAR. The quality of Doppler shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates rapidly as SNR decreases. NADSET compensates such deterioration in the quality of wind parameter estimates by adaptively utilizing the statistics of Doppler shift estimate in a strong SNR range and identifying sporadic range bins where good Doppler shift estimates are found. The authenticity of NADSET is established by comparing the trend of wind parameters with and without NADSET applied to the long-period lidar return data.

Optical fiber pressure sensors for adaptive wings

NASA Astrophysics Data System (ADS)

Duncan, Paul G.; Jones, Mark E.; Shinpaugh, Kevin A.; Poland, Stephen H.; Murphy, Kent A.; Claus, Richard O.

1997-06-01

Optical fiber pressure sensors have been developed for use on a structurally-adaptive `smart wing'; further details of the design, fabrication and testing of the smart wing concept are presented in companion papers. This paper describes the design, construction, and performance of the pressure sensor and a combined optical and electronic signal processing system implemented to permit the measurement of a large number of sensors distributed over the control surfaces of a wing. Optical fiber pressure sensors were implemented due to anticipated large electromagnetic interference signals within the operational environment. The sensors utilized the principle of the extrinsic Fabry-Perot interferometer (EFPI) already developed for the measurement of strain and temperature. Here, the cavity is created inside a micromachined hollow-core tube with a silicon diaphragm at one end. The operation of the sensor is similar to that of the EFPI strain gage also discussed in several papers at this conference. The limitations placed upon the performance of the digital signal processing system were determined by the required pressure range of the sensors and the cycle time of the control system used to adaptively modify the shape of the wing. Sensor calibration and the results of testing performed are detailed.

Experiments with recursive estimation in astronomical image processing

NASA Technical Reports Server (NTRS)

Busko, I.

1992-01-01

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

Power line interference attenuation in multi-channel sEMG signals: Algorithms and analysis.

PubMed

Soedirdjo, S D H; Ullah, K; Merletti, R

2015-08-01

Electromyogram (EMG) recordings are often corrupted by power line interference (PLI) even though the skin is prepared and well-designed instruments are used. This study focuses on the analysis of some of the recent and classical existing digital signal processing approaches have been used to attenuate, if not eliminate, the power line interference from EMG signals. A comparison of the signal to interference ratio (SIR) of the output signals is presented, for four methods: classical notch filter, spectral interpolation, adaptive noise canceller with phase locked loop (ANC-PLL) and adaptive filter, applied to simulated multichannel monopolar EMG signals with different SIR. The effect of each method on the shape of the EMG signals is also analyzed. The results show that ANC-PLL method gives the best output SIR and lowest shape distortion compared to the other methods. Classical notch filtering is the simplest method but some information might be lost as it removes both the interference and the EMG signals. Thus, it is obvious that notch filter has the lowest performance and it introduces distortion into the resulting signals.

An adaptive singular spectrum analysis method for extracting brain rhythms of electroencephalography

PubMed Central

Hu, Hai; Guo, Shengxin; Liu, Ran

2017-01-01

Artifacts removal and rhythms extraction from electroencephalography (EEG) signals are important for portable and wearable EEG recording devices. Incorporating a novel grouping rule, we proposed an adaptive singular spectrum analysis (SSA) method for artifacts removal and rhythms extraction. Based on the EEG signal amplitude, the grouping rule determines adaptively the first one or two SSA reconstructed components as artifacts and removes them. The remaining reconstructed components are then grouped based on their peak frequencies in the Fourier transform to extract the desired rhythms. The grouping rule thus enables SSA to be adaptive to EEG signals containing different levels of artifacts and rhythms. The simulated EEG data based on the Markov Process Amplitude (MPA) EEG model and the experimental EEG data in the eyes-open and eyes-closed states were used to verify the adaptive SSA method. Results showed a better performance in artifacts removal and rhythms extraction, compared with the wavelet decomposition (WDec) and another two recently reported SSA methods. Features of the extracted alpha rhythms using adaptive SSA were calculated to distinguish between the eyes-open and eyes-closed states. Results showed a higher accuracy (95.8%) than those of the WDec method (79.2%) and the infinite impulse response (IIR) filtering method (83.3%). PMID:28674650

Adaptation of the hypothalamic-pituitary-adrenal axis and glucose to repeated immobilization or restraint stress is not influenced by associative signals.

PubMed

Rabasa, Cristina; Delgado-Morales, Raúl; Muñoz-Abellán, Cristina; Nadal, Roser; Armario, Antonio

2011-02-02

Repeated exposure to the same stressor very often results in a reduction of some prototypical stress responses, namely those related to the hypothalamic-pituitary-adrenal (HPA) and sympatho-medullo-adrenal (SMA) axes. This reduced response to repeated exposure to the same (homotypic) stressor (adaptation) is usually considered as a habituation-like process, and therefore, a non-associative type of learning. However, there is some evidence that contextual cues and therefore associative processes could contribute to adaptation. In the present study we demonstrated in two experiments using adult male rats that repeated daily exposure to restraint (REST) or immobilization on boards (IMO) reduced the HPA (plasma levels of ACTH and corticosterone) and glucose responses to the homotypic stressor and such reduced responses remained intact when all putative cues associated to the procedure (experimenter, way of transporting to the stress room, stress boxes, stress room and colour of the restrainer in the case of REST) were modified on the next day. Therefore, the present results do not favour the view that adaptation after repeated exposure to a stressor may involve associative processes related to signals predicting the imminence of the stressors, but more studies are needed on this issue. Copyright © 2010 Elsevier B.V. All rights reserved.

Rheb and mammalian target of rapamycin in mitochondrial homoeostasis

PubMed Central

Groenewoud, Marlous J.; Zwartkruis, Fried J. T.

2013-01-01

Mitochondrial dysfunction has been associated with various diseases, such as cancer, myopathies, neurodegeneration and obesity. Mitochondrial homoeostasis is achieved by mechanisms that adapt the number of mitochondria to that required for energy production and for the supply of metabolic intermediates necessary to sustain cell growth. Simultaneously, mitochondrial quality control mechanisms are in place to remove malfunctioning mitochondria. In the cytoplasm, the protein complex mTORC1 couples growth-promoting signals with anabolic processes, in which mitochondria play an essential role. Here, we review the involvement of mTORC1 and Rheb in mitochondrial homoeostasis. The regulatory processes downstream of mTORC1 affect the glycolytic flux and the rate of mitophagy, and include regulation of the transcription factors HIF1α and YY1/PGC-1α. We also discuss how mitochondrial function feeds back on mTORC1 via reactive oxygen species signalling to adapt metabolic processes, and highlight how mTORC1 signalling is integrated with the unfolded protein response in mitochondria, which in Caenorhabditis elegans is mediated via transcription factors such as DVE-1/UBL-5 and ATFS-1. PMID:24352740

Parametric adaptive filtering and data validation in the bar GW detector AURIGA

NASA Astrophysics Data System (ADS)

Ortolan, A.; Baggio, L.; Cerdonio, M.; Prodi, G. A.; Vedovato, G.; Vitale, S.

2002-04-01

We report on our experience gained in the signal processing of the resonant GW detector AURIGA. Signal amplitude and arrival time are estimated by means of a matched-adaptive Wiener filter. The detector noise, entering in the filter set-up, is modelled as a parametric ARMA process; to account for slow non-stationarity of the noise, the ARMA parameters are estimated on an hourly basis. A requirement of the set-up of an unbiased Wiener filter is the separation of time spans with 'almost Gaussian' noise from non-Gaussian and/or strongly non-stationary time spans. The separation algorithm consists basically of a variance estimate with the Chauvenet convergence method and a threshold on the Curtosis index. The subsequent validation of data is strictly connected with the separation procedure: in fact, by injecting a large number of artificial GW signals into the 'almost Gaussian' part of the AURIGA data stream, we have demonstrated that the effective probability distributions of the signal-to-noise ratio χ2 and the time of arrival are those that are expected.

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

PubMed Central

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

2010-01-01

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

Device and method for skull-melting depth measurement

DOEpatents

Lauf, R.J.; Heestand, R.L.

1993-02-09

A method of skull-melting comprises the steps of: (a) providing a vessel adapted for a skull-melting process, the vessel having an interior, an underside, and an orifice connecting the interior and the underside; (b) disposing a waveguide in the orifice so that the waveguide protrudes sufficiently into the interior to interact with the skull-melting process; (c) providing a signal energy transducer in signal communication with the waveguide; (d) introducing into the vessel a molten working material; (e) carrying out the skull-melting process so that a solidified skull of the working material is formed, the skull and the vessel having an interface therebetween, the skull becoming fused to the waveguide so the signal energy can be transmitted through the waveguide and the skull without interference from the interface; (f) activating the signal energy transducer so that a signal is propagated through the waveguide; and, (g) controlling at least one variable of the skull-melting process utilizing feedback information derived from the propagated signal energy.

Device and method for skull-melting depth measurement

DOEpatents

Lauf, Robert J.; Heestand, Richard L.

1993-01-01

A method of skull-melting comprises the steps of: a. providing a vessel adapted for a skull-melting process, the vessel having an interior, an underside, and an orifice in connecting the interior and the underside; b. disposing a waveguide in the orifice so that the waveguide protrudes sufficiently into the interior to interact with the skull-melting process; c. providing a signal energy transducer in signal communication with the waveguide; d. introducing into the vessel a molten working material; e. carrying out the skull-melting process so that a solidified skull of the working material is formed, the skull and the vessel having an interface therebetween, the skull becoming fused to the waveguide so the signal energy can be transmitted through the waveguide and the skull without interference from the interface; f. activating the signal energy transducer so that a signal is propagated through the waveguide; and, g. controlling at least one variable of the skull-melting process utilizing feedback information derived from the propagated signal energy.

Evaluation of Speech Intelligibility and Sound Localization Abilities with Hearing Aids Using Binaural Wireless Technology.

PubMed

Ibrahim, Iman; Parsa, Vijay; Macpherson, Ewan; Cheesman, Margaret

2013-01-02

Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance.

Mechanical Signaling for Bone Modeling and Remodeling

PubMed Central

Robling, Alexander G.; Turner, Charles H.

2012-01-01

Proper development of the skeleton in utero and during growth requires mechanical stimulation. Loading results in adaptive changes in bone that strengthen bone structure. Bone’s adaptive response is regulated by the ability of resident bone cells to perceive and translate mechanical energy into a cascade of structural and biochemical changes within the cells — a process known as mechanotransduction. Mechanotransduction pathways are among the most anabolic in bone, and consequently, there is great interest in elucidating how mechanical loading produces its observed effects, including increased bone formation, reduced bone loss, changes in bone cell differentiation and lifespan, among others. A molecular understanding of these processes is developing, and with it comes a profound new insight into the biology of bone. In this article, we review the nature of the physical stimulus to which bone cells mount an adaptive response, including the identity of the sensor cells, their attributes and physical environment, and putative mechanoreceptors they express. Particular attention is allotted to the focal adhesion and Wnt signaling, in light of their emerging role in bone mechanotransduction. The cellular mechanisms for increased bone loss during disuse, and reduced bone loss during loading are considered. Finally, we summarize the published data on bone cell accommodation, whereby bone cells stop responding to mechanical signaling events. Collectively, these data highlight the complex yet finely orchestrated process of mechanically regulated bone homeostasis. PMID:19817708

Human Language Technology: Opportunities and Challenges

DTIC Science & Technology

2005-01-01

because of the connections to and reliance on signal processing. Audio diarization critically includes indexing of speakers [12], since speaker ...to reduce inter- speaker variability in training. Standard techniques include vocal-tract length normalization, adaptation of acoustic models using...maximum likelihood linear regression (MLLR), and speaker -adaptive training based on MLLR. The acoustic models are mixtures of Gaussians, typically with

Modified DCTNet for audio signals classification

NASA Astrophysics Data System (ADS)

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Innate control of adaptive immunity: Beyond the three-signal paradigm

PubMed Central

Jain, Aakanksha; Pasare, Chandrashekhar

2017-01-01

Activation of cells in the adaptive immune system is a highly orchestrated process dictated by multiples cues from the innate immune system. Although the fundamental principles of innate control of adaptive immunity are well established, it is not fully understood how innate cells integrate qualitative pathogenic information in order to generate tailored protective adaptive immune responses. In this review, we discuss complexities involved in the innate control of adaptive immunity that extend beyond T cell receptor engagement, co-stimulation and priming cytokine production but are critical for generation of protective T cell immunity. PMID:28483987

ICC '86; Proceedings of the International Conference on Communications, Toronto, Canada, June 22-25, 1986, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Papers are presented on ISDN, mobile radio systems and techniques for digital connectivity, centralized and distributed algorithms in computer networks, communications networks, quality assurance and impact on cost, adaptive filters in communications, the spread spectrum, signal processing, video communication techniques, and digital satellite services. Topics discussed include performance evaluation issues for integrated protocols, packet network operations, the computer network theory and multiple-access, microwave single sideband systems, switching architectures, fiber optic systems, wireless local communications, modulation, coding, and synchronization, remote switching, software quality, transmission, and expert systems in network operations. Consideration is given to wide area networks, image and speech processing, office communications application protocols, multimedia systems, customer-controlled network operations, digital radio systems, channel modeling and signal processing in digital communications, earth station/on-board modems, computer communications system performance evaluation, source encoding, compression, and quantization, and adaptive communications systems.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

PubMed

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

An adaptive segment method for smoothing lidar signal based on noise estimation

NASA Astrophysics Data System (ADS)

Wang, Yuzhao; Luo, Pingping

2014-10-01

An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

Interpolation algorithm for asynchronous ADC-data

NASA Astrophysics Data System (ADS)

Bramburger, Stefan; Zinke, Benny; Killat, Dirk

2017-09-01

This paper presents a modified interpolation algorithm for signals with variable data rate from asynchronous ADCs. The Adaptive weights Conjugate gradient Toeplitz matrix (ACT) algorithm is extended to operate with a continuous data stream. An additional preprocessing of data with constant and linear sections and a weighted overlap of step-by-step into spectral domain transformed signals improve the reconstruction of the asycnhronous ADC signal. The interpolation method can be used if asynchronous ADC data is fed into synchronous digital signal processing.

Processing on weak electric signals by the autoregressive model

NASA Astrophysics Data System (ADS)

Ding, Jinli; Zhao, Jiayin; Wang, Lanzhou; Li, Qiao

2008-10-01

A model of the autoregressive model of weak electric signals in two plants was set up for the first time. The result of the AR model to forecast 10 values of the weak electric signals is well. It will construct a standard set of the AR model coefficient of the plant electric signal and the environmental factor, and can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on agricultural productions.

Robust estimators for speech enhancement in real environments

NASA Astrophysics Data System (ADS)

Sandoval-Ibarra, Yuma; Diaz-Ramirez, Victor H.; Kober, Vitaly

2015-09-01

Common statistical estimators for speech enhancement rely on several assumptions about stationarity of speech signals and noise. These assumptions may not always valid in real-life due to nonstationary characteristics of speech and noise processes. We propose new estimators based on existing estimators by incorporation of computation of rank-order statistics. The proposed estimators are better adapted to non-stationary characteristics of speech signals and noise processes. Through computer simulations we show that the proposed estimators yield a better performance in terms of objective metrics than that of known estimators when speech signals are contaminated with airport, babble, restaurant, and train-station noise.

Generation of Custom DSP Transform IP Cores: Case Study Walsh-Hadamard Transform

DTIC Science & Technology

2002-09-01

mathematics and hardware design What I know: Finite state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing...state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing Adaptive filter theory … A math guy A hardware engineer...Synthesis Technology Libary Bit-width (8) HF factor (1,2,3,6) VF factor (1,2,4, ... 32) Xilinx FPGA Place&Route Xilinx FPGA Place&Route Performance

Joint Waveform Optimization and Adaptive Processing for Random-Phase Radar Signals

DTIC Science & Technology

2014-01-01

extended targets,” IEEE Journal of Selected Topics in Signal Processing, vol. 1, no. 1, pp. 42– 55, June 2007. [2] S. Sen and A. Nehorai, “ OFDM mimo ...radar compared to traditional waveforms. I. INTRODUCTION There has been much recent interest in waveform design for multiple-input, multiple-output ( MIMO ...amplitude. When the resolution capability of the MIMO radar system is of interest, the transmit waveform can be designed to sharpen the radar ambiguity

Optimization of MLS receivers for multipath environments

NASA Technical Reports Server (NTRS)

Mcalpine, G. A.; Highfill, J. H., III

1976-01-01

The design of a microwave landing system (MLS) aircraft receiver, capable of optimal performance in multipath environments found in air terminal areas, is reported. Special attention was given to the angle tracking problem of the receiver and includes tracking system design considerations, study and application of locally optimum estimation involving multipath adaptive reception and then envelope processing, and microcomputer system design. Results show processing is competitive in this application with i-f signal processing performance-wise and is much more simple and cheaper. A summary of the signal model is given.

Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

PubMed Central

de la Rosa, Ramon; Alonso, Alonso; Carrera, Albano; Durán, Ramon; Fernández, Patricia

2010-01-01

This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals. PMID:22163515

Man-machine interface system for neuromuscular training and evaluation based on EMG and MMG signals.

PubMed

de la Rosa, Ramon; Alonso, Alonso; Carrera, Albano; Durán, Ramon; Fernández, Patricia

2010-01-01

This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.

Pipeline Processing with an Iterative, Context-based Detection Model

DTIC Science & Technology

2014-04-19

stripping the incoming data stream of repeating and irrelevant signals prior to running primary detectors , adaptive beamforming and matched field processing...framework, pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION...10 5. Teleseismic paths from earthquakes in

Probabilistic co-adaptive brain-computer interfacing

NASA Astrophysics Data System (ADS)

Bryan, Matthew J.; Martin, Stefan A.; Cheung, Willy; Rao, Rajesh P. N.

2013-12-01

Objective. Brain-computer interfaces (BCIs) are confronted with two fundamental challenges: (a) the uncertainty associated with decoding noisy brain signals, and (b) the need for co-adaptation between the brain and the interface so as to cooperatively achieve a common goal in a task. We seek to mitigate these challenges. Approach. We introduce a new approach to brain-computer interfacing based on partially observable Markov decision processes (POMDPs). POMDPs provide a principled approach to handling uncertainty and achieving co-adaptation in the following manner: (1) Bayesian inference is used to compute posterior probability distributions (‘beliefs’) over brain and environment state, and (2) actions are selected based on entire belief distributions in order to maximize total expected reward; by employing methods from reinforcement learning, the POMDP’s reward function can be updated over time to allow for co-adaptive behaviour. Main results. We illustrate our approach using a simple non-invasive BCI which optimizes the speed-accuracy trade-off for individual subjects based on the signal-to-noise characteristics of their brain signals. We additionally demonstrate that the POMDP BCI can automatically detect changes in the user’s control strategy and can co-adaptively switch control strategies on-the-fly to maximize expected reward. Significance. Our results suggest that the framework of POMDPs offers a promising approach for designing BCIs that can handle uncertainty in neural signals and co-adapt with the user on an ongoing basis. The fact that the POMDP BCI maintains a probability distribution over the user’s brain state allows a much more powerful form of decision making than traditional BCI approaches, which have typically been based on the output of classifiers or regression techniques. Furthermore, the co-adaptation of the system allows the BCI to make online improvements to its behaviour, adjusting itself automatically to the user’s changing circumstances.

SignalPlant: an open signal processing software platform.

PubMed

Plesinger, F; Jurco, J; Halamek, J; Jurak, P

2016-07-01

The growing technical standard of acquisition systems allows the acquisition of large records, often reaching gigabytes or more in size as is the case with whole-day electroencephalograph (EEG) recordings, for example. Although current 64-bit software for signal processing is able to process (e.g. filter, analyze, etc) such data, visual inspection and labeling will probably suffer from rather long latency during the rendering of large portions of recorded signals. For this reason, we have developed SignalPlant-a stand-alone application for signal inspection, labeling and processing. The main motivation was to supply investigators with a tool allowing fast and interactive work with large multichannel records produced by EEG, electrocardiograph and similar devices. The rendering latency was compared with EEGLAB and proves significantly faster when displaying an image from a large number of samples (e.g. 163-times faster for 75  ×  10(6) samples). The presented SignalPlant software is available free and does not depend on any other computation software. Furthermore, it can be extended with plugins by third parties ensuring its adaptability to future research tasks and new data formats.

Use of Adaptive Digital Signal Processing to Improve Speech Communication for Normally Hearing aand Hearing-Impaired Subjects.

ERIC Educational Resources Information Center

Harris, Richard W.; And Others

1988-01-01

A two-microphone adaptive digital noise cancellation technique improved word-recognition ability for 20 normal and 12 hearing-impaired adults by reducing multitalker speech babble and speech spectrum noise 18-22 dB. Word recognition improvements averaged 37-50 percent for normal and 27-40 percent for hearing-impaired subjects. Improvement was best…

An analysis of neural receptive field plasticity by point process adaptive filtering

PubMed Central

Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

2001-01-01

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

Auxin and the integration of environmental signals into plant root development

PubMed Central

Kazan, Kemal

2013-01-01

Background Auxin is a versatile plant hormone with important roles in many essential physiological processes. In recent years, significant progress has been made towards understanding the roles of this hormone in plant growth and development. Recent evidence also points to a less well-known but equally important role for auxin as a mediator of environmental adaptation in plants. Scope This review briefly discusses recent findings on how plants utilize auxin signalling and transport to modify their root system architecture when responding to diverse biotic and abiotic rhizosphere signals, including macro- and micro-nutrient starvation, cold and water stress, soil acidity, pathogenic and beneficial microbes, nematodes and neighbouring plants. Stress-responsive transcription factors and microRNAs that modulate auxin- and environment-mediated root development are also briefly highlighted. Conclusions The auxin pathway constitutes an essential component of the plant's biotic and abiotic stress tolerance mechanisms. Further understanding of the specific roles that auxin plays in environmental adaptation can ultimately lead to the development of crops better adapted to stressful environments. PMID:24136877

Auxin and the integration of environmental signals into plant root development.

PubMed

Kazan, Kemal

2013-12-01

Auxin is a versatile plant hormone with important roles in many essential physiological processes. In recent years, significant progress has been made towards understanding the roles of this hormone in plant growth and development. Recent evidence also points to a less well-known but equally important role for auxin as a mediator of environmental adaptation in plants. This review briefly discusses recent findings on how plants utilize auxin signalling and transport to modify their root system architecture when responding to diverse biotic and abiotic rhizosphere signals, including macro- and micro-nutrient starvation, cold and water stress, soil acidity, pathogenic and beneficial microbes, nematodes and neighbouring plants. Stress-responsive transcription factors and microRNAs that modulate auxin- and environment-mediated root development are also briefly highlighted. The auxin pathway constitutes an essential component of the plant's biotic and abiotic stress tolerance mechanisms. Further understanding of the specific roles that auxin plays in environmental adaptation can ultimately lead to the development of crops better adapted to stressful environments.

The effect of hearing aid technologies on listening in an automobile

PubMed Central

Wu, Yu-Hsiang; Stangl, Elizabeth; Bentler, Ruth A.; Stanziola, Rachel W.

2014-01-01

Background Communication while traveling in an automobile often is very difficult for hearing aid users. This is because the automobile /road noise level is usually high, and listeners/drivers often do not have access to visual cues. Since the talker of interest usually is not located in front of the driver/listener, conventional directional processing that places the directivity beam toward the listener’s front may not be helpful, and in fact, could have a negative impact on speech recognition (when compared to omnidirectional processing). Recently, technologies have become available in commercial hearing aids that are designed to improve speech recognition and/or listening effort in noisy conditions where talkers are located behind or beside the listener. These technologies include (1) a directional microphone system that uses a backward-facing directivity pattern (Back-DIR processing), (2) a technology that transmits audio signals from the ear with the better signal-to-noise ratio (SNR) to the ear with the poorer SNR (Side-Transmission processing), and (3) a signal processing scheme that suppresses the noise at the ear with the poorer SNR (Side-Suppression processing). Purpose The purpose of the current study was to determine the effect of (1) conventional directional microphones and (2) newer signal processing schemes (Back-DIR, Side-Transmission, and Side-Suppression) on listener’s speech recognition performance and preference for communication in a traveling automobile. Research design A single-blinded, repeated-measures design was used. Study Sample Twenty-five adults with bilateral symmetrical sensorineural hearing loss aged 44 through 84 years participated in the study. Data Collection and Analysis The automobile/road noise and sentences of the Connected Speech Test (CST) were recorded through hearing aids in a standard van moving at a speed of 70 miles/hour on a paved highway. The hearing aids were programmed to omnidirectional microphone, conventional adaptive directional microphone, and the three newer schemes. CST sentences were presented from the side and back of the hearing aids, which were placed on the ears of a manikin. The recorded stimuli were presented to listeners via earphones in a sound treated booth to assess speech recognition performance and preference with each programmed condition. Results Compared to omnidirectional microphones, conventional adaptive directional processing had a detrimental effect on speech recognition when speech was presented from the back or side of the listener. Back-DIR and Side-Transmission processing improved speech recognition performance (relative to both omnidirectional and adaptive directional processing) when speech was from the back and side, respectively. The performance with Side-Suppression processing was better than with adaptive directional processing when speech was from the side. The participants’ preferences for a given processing scheme were generally consistent with speech recognition results. Conclusions The finding that performance with adaptive directional processing was poorer than with omnidirectional microphones demonstrates the importance of selecting the correct microphone technology for different listening situations. The results also suggest the feasibility of using hearing aid technologies to provide a better listening experience for hearing aid users in automobiles. PMID:23886425

Chemokine Signaling in Allergic Contact Dermatitis: Toward Targeted Therapies.

PubMed

Smith, Jeffrey S; Rajagopal, Sudarshan; Atwater, Amber Reck

2018-06-22

Allergic contact dermatitis (ACD) is a common skin disease that results in significant cost and morbidity. Despite its high prevalence, therapeutic options are limited. Allergic contact dermatitis is regulated primarily by T cells within the adaptive immune system, but also by natural killer and innate lymphoid cells within the innate immune system. The chemokine receptor system, consisting of chemokine peptides and chemokine G protein-coupled receptors, is a critical regulator of inflammatory processes such as ACD. Specific chemokine signaling pathways are selectively up-regulated in ACD, most prominently CXCR3 and its endogenous chemokines CXCL9, CXCL10, and CXCL11. Recent research demonstrates that these 3 chemokines are not redundant and indeed activate distinct intracellular signaling profiles such as those activated by heterotrimeric G proteins and β-arrestin adapter proteins. Such differential signaling provides an attractive therapeutic target for novel ACD therapies and other inflammatory diseases.

Errors in the estimation method for the rejection of vibrations in adaptive optics systems

NASA Astrophysics Data System (ADS)

Kania, Dariusz

2017-06-01

In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.

Adaptive angular-velocity Vold-Kalman filter order tracking - Theoretical basis, numerical implementation and parameter investigation

NASA Astrophysics Data System (ADS)

Pan, M.-Ch.; Chu, W.-Ch.; Le, Duc-Do

2016-12-01

The paper presents an alternative Vold-Kalman filter order tracking (VKF_OT) method, i.e. adaptive angular-velocity VKF_OT technique, to extract and characterize order components in an adaptive manner for the condition monitoring and fault diagnosis of rotary machinery. The order/spectral waveforms to be tracked can be recursively solved by using Kalman filter based on the one-step state prediction. The paper comprises theoretical derivation of computation scheme, numerical implementation, and parameter investigation. Comparisons of the adaptive VKF_OT scheme with two other ones are performed through processing synthetic signals of designated order components. Processing parameters such as the weighting factor and the correlation matrix of process noise, and data conditions like the sampling frequency, which influence tracking behavior, are explored. The merits such as adaptive processing nature and computation efficiency brought by the proposed scheme are addressed although the computation was performed in off-line conditions. The proposed scheme can simultaneously extract multiple spectral components, and effectively decouple close and crossing orders associated with multi-axial reference rotating speeds.

Evaluation of Adaptive Noise Management Technologies for School-Age Children with Hearing Loss.

PubMed

Wolfe, Jace; Duke, Mila; Schafer, Erin; Jones, Christine; Rakita, Lori

2017-05-01

Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations. The objective of this study was to compare speech recognition, speech intelligibility ratings (SIRs), and sound preferences of children using hearing aids equipped with and without adaptive noise management technologies. A single-group, repeated measures design was used to evaluate performance differences obtained in four simulated environments. In each simulated environment, participants were tested in a basic listening program with minimal noise management features, a manual program designed for that scene, and the hearing instruments' adaptive operating system that steered hearing instrument parameterization based on the characteristics of the environment. Twelve children with mild to moderately severe sensorineural hearing loss. Speech recognition and SIRs were evaluated in three hearing aid programs with and without noise management technologies across two different test sessions and various listening environments. Also, the participants' perceptual hearing performance in daily real-world listening situations with two of the hearing aid programs was evaluated during a four- to six-week field trial that took place between the two laboratory sessions. On average, the use of adaptive noise management technology improved sentence recognition in noise for speech presented in front of the participant but resulted in a decrement in performance for signals arriving from behind when the participant was facing forward. However, the improvement with adaptive noise management exceeded the decrement obtained when the signal arrived from behind. Most participants reported better subjective SIRs when using adaptive noise management technologies, particularly when the signal of interest arrived from in front of the listener. In addition, most participants reported a preference for the technology with an automatically switching, adaptive directional microphone and adaptive noise reduction in real-world listening situations when compared to conventional, omnidirectional microphone use with minimal noise reduction processing. Use of the adaptive noise management technologies evaluated in this study improves school-age children's speech recognition in noise for signals arriving from the front. Although a small decrement in speech recognition in noise was observed for signals arriving from behind the listener, most participants reported a preference for use of noise management technology both when the signal arrived from in front and from behind the child. The results of this study suggest that adaptive noise management technologies should be considered for use with school-age children when listening in academic and social situations. American Academy of Audiology

General purpose graphic processing unit implementation of adaptive pulse compression algorithms

NASA Astrophysics Data System (ADS)

Cai, Jingxiao; Zhang, Yan

2017-07-01

This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: II mechanisms.

PubMed

Nikolaev, Anton; Zheng, Lei; Wardill, Trevor J; O'Kane, Cahir J; de Polavieja, Gonzalo G; Juusola, Mikko

2009-01-01

Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information.

Selection signature in domesticated animals.

PubMed

Pan, Zhang-yuan; He, Xiao-yun; Wang, Xiang-yu; Guo, Xiao-fei; Cao, Xiao-han; Hu, Wen-ping; Di, Ran; Liu, Qiu-yue; Chu, Ming-xing

2016-12-20

Domesticated animals play an important role in the life of humanity. All these domesticated animals undergo same process, first domesticated from wild animals, then after long time natural and artificial selection, formed various breeds that adapted to the local environment and human needs. In this process, domestication, natural and artificial selection will leave the selection signal in the genome. The research on these selection signals can find functional genes directly, is one of the most important strategies in screening functional genes. The current studies of selection signal have been performed in pigs, chickens, cattle, sheep, goats, dogs and other domestic animals, and found a great deal of functional genes. This paper provided an overview of the types and the detected methods of selection signal, and outlined researches of selection signal in domestic animals, and discussed the key issues in selection signal analysis and its prospects.

A novel approach for SEMG signal classification with adaptive local binary patterns.

PubMed

Ertuğrul, Ömer Faruk; Kaya, Yılmaz; Tekin, Ramazan

2016-07-01

Feature extraction plays a major role in the pattern recognition process, and this paper presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is built on the local binary pattern (LBP), which is an image processing method, and one-dimensional local binary pattern (1D-LBP). In LBP, each pixel is compared with its neighbors. Similarly, in 1D-LBP, each data in the raw is judged against its neighbors. 1D-LBP extracts feature based on local changes in the signal. Therefore, it has high a potential to be employed in medical purposes. Since, each action or abnormality, which is recorded in SEMG signals, has its own pattern, and via the 1D-LBP these (hidden) patterns may be detected. But, the positions of the neighbors in 1D-LBP are constant depending on the position of the data in the raw. Also, both LBP and 1D-LBP are very sensitive to noise. Therefore, its capacity in detecting hidden patterns is limited. To overcome these drawbacks, aLBP was proposed. In aLBP, the positions of the neighbors and their values can be assigned adaptively via the down-sampling and the smoothing coefficients. Therefore, the potential to detect (hidden) patterns, which may express an illness or an action, is really increased. To validate the proposed feature extraction approach, two different datasets were employed. Achieved accuracies by the proposed approach were higher than obtained results by employed popular feature extraction approaches and the reported results in the literature. Obtained accuracy results were brought out that the proposed method can be employed to investigate SEMG signals. In summary, this work attempts to develop an adaptive feature extraction scheme that can be utilized for extracting features from local changes in different categories of time-varying signals.

PSYCHOSOCIAL INTERVENTION EFFECTS ON ADAPTATION, DISEASE COURSE AND BIOBEHAVIORAL PROCESSES IN CANCER

PubMed Central

Antoni, Michael H.

2012-01-01

A diagnosis of cancer and subsequent treatments place demands on psychological adaptation. Behavioral research suggests the importance of cognitive, behavioral, and social factors in facilitating adaptation during active treatment and throughout cancer survivorship, which forms the rationale for the use of many psychosocial interventions in cancer patients. This cancer experience may also affect physiological adaptation systems (e.g., neuroendocrine) in parallel with psychological adaptation changes (negative affect). Changes in adaptation may alter tumor growth-promoting processes (increased angiogenesis, migration and invasion, and inflammation) and tumor defense processes (decreased cellular immunity) relevant for cancer progression and the quality of life of cancer patients. Some evidence suggests that psychosocial intervention can improve psychological and physiological adaptation indicators in cancer patients. However, less is known about whether these interventions can influence tumor activity and tumor growth-promoting processes and whether changes in these processes could explain the psychosocial intervention effects on recurrence and survival documented to date. Documenting that psychosocial interventions can modulate molecular activities (e.g., transcriptional indicators of cell signaling) that govern tumor promoting and tumor defense processes on the one hand, and clinical disease course on the other is a key challenge for biobehavioral oncology research. This mini-review will summarize current knowledge on psychological and physiological adaptation processes affected throughout the stress of the cancer experience, and the effects of psychosocial interventions on psychological adaptation, cancer disease progression, and changes in stress-related biobehavioral processes that may mediate intervention effects on clinical cancer outcomes. Very recent intervention work in breast cancer will be used to illuminate emerging trends in molecular probes of interest in the hope of highlighting future paths that could move the field of biobehavioral oncology intervention research forward. PMID:22627072

Psychosocial intervention effects on adaptation, disease course and biobehavioral processes in cancer.

PubMed

Antoni, Michael H

2013-03-01

A diagnosis of cancer and subsequent treatments place demands on psychological adaptation. Behavioral research suggests the importance of cognitive, behavioral, and social factors in facilitating adaptation during active treatment and throughout cancer survivorship, which forms the rationale for the use of many psychosocial interventions in cancer patients. This cancer experience may also affect physiological adaptation systems (e.g., neuroendocrine) in parallel with psychological adaptation changes (negative affect). Changes in adaptation may alter tumor growth-promoting processes (increased angiogenesis, migration and invasion, and inflammation) and tumor defense processes (decreased cellular immunity) relevant for cancer progression and the quality of life of cancer patients. Some evidence suggests that psychosocial intervention can improve psychological and physiological adaptation indicators in cancer patients. However, less is known about whether these interventions can influence tumor activity and tumor growth-promoting processes and whether changes in these processes could explain the psychosocial intervention effects on recurrence and survival documented to date. Documenting that psychosocial interventions can modulate molecular activities (e.g., transcriptional indicators of cell signaling) that govern tumor promoting and tumor defense processes on the one hand, and clinical disease course on the other is a key challenge for biobehavioral oncology research. This mini-review will summarize current knowledge on psychological and physiological adaptation processes affected throughout the stress of the cancer experience, and the effects of psychosocial interventions on psychological adaptation, cancer disease progression, and changes in stress-related biobehavioral processes that may mediate intervention effects on clinical cancer outcomes. Very recent intervention work in breast cancer will be used to illuminate emerging trends in molecular probes of interest in the hope of highlighting future paths that could move the field of biobehavioral oncology intervention research forward. Copyright © 2012 Elsevier Inc. All rights reserved.

Retrograde Signals: Integrators of Interorganellar Communication and Orchestrators of Plant Development.

PubMed

de Souza, Amancio; Wang, Jin-Zheng; Dehesh, Katayoon

2017-04-28

Interorganellar cooperation maintained via exquisitely controlled retrograde-signaling pathways is an evolutionary necessity for maintenance of cellular homeostasis. This signaling feature has therefore attracted much research attention aimed at improving understanding of the nature of these communication signals, how the signals are sensed, and ultimately the mechanism by which they integrate targeted processes that collectively culminate in organellar cooperativity. The answers to these questions will provide insight into how retrograde-signal-mediated regulatory mechanisms are recruited and which biological processes are targeted, and will advance our understanding of how organisms balance metabolic investments in growth against adaptation to environmental stress. This review summarizes the present understanding of the nature and the functional complexity of retrograde signals as integrators of interorganellar communication and orchestrators of plant development, and offers a perspective on the future of this critical and dynamic area of research.

Wright's Shifting Balance Theory and the Diversification of Aposematic Signals

PubMed Central

Chouteau, Mathieu; Angers, Bernard

2012-01-01

Despite accumulating evidence for selection within natural systems, the importance of random genetic drift opposing Wright's and Fisher's views of evolution continue to be a subject of controversy. The geographical diversification of aposematic signals appears to be a suitable system to assess the factors involved in the process of adaptation since both theories were independently proposed to explain this phenomenon. In the present study, the effects of drift and selection were assessed from population genetics and predation experiments on poison-dart frogs, Ranitomaya imitator, of Northern Peru. We specifically focus on the transient zone between two distinct aposematic signals. In contrast to regions where high predation maintains a monomorphic aposematic signal, the transient zones are characterized by lowered selection and a high phenotypic diversity. As a result, the diversification of phenotypes may occur via genetic drift without a significant loss of fitness. These new phenotypes may then colonize alternative habitats if successfully recognized and avoided by predators. This study highlights the interplay between drift and selection as determinant processes in the adaptive diversification of aposematic signals. Results are consistent with the expectations of the Wright's shifting balance theory and represent, to our knowledge, the first empirical demonstration of this highly contested theory in a natural system. PMID:22470509

Evaluation of Speech Intelligibility and Sound Localization Abilities with Hearing Aids Using Binaural Wireless Technology

PubMed Central

Ibrahim, Iman; Parsa, Vijay; Macpherson, Ewan; Cheesman, Margaret

2012-01-01

Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance. PMID:26557339

Integrated Sensing and Processing (ISP) Phase II: Demonstration and Evaluation for Distributed Sensor Netowrks and Missile Seeker Systems

DTIC Science & Technology

2007-02-28

Shah, D. Waagen, H. Schmitt, S. Bellofiore, A. Spanias, and D. Cochran, 32nd International Conference on Acoustics, Speech , and Signal Processing...Information Exploitation Office kNN k-Nearest Neighbor LEAN Laplacian Eigenmap Adaptive Neighbor LIP Linear Integer Programming ISP

Adaptive OFDM Waveform Design for Spatio-Temporal-Sparsity Exploited STAP Radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sen, Satyabrata

In this chapter, we describe a sparsity-based space-time adaptive processing (STAP) algorithm to detect a slowly moving target using an orthogonal frequency division multiplexing (OFDM) radar. The motivation of employing an OFDM signal is that it improves the target-detectability from the interfering signals by increasing the frequency diversity of the system. However, due to the addition of one extra dimension in terms of frequency, the adaptive degrees-of-freedom in an OFDM-STAP also increases. Therefore, to avoid the construction a fully adaptive OFDM-STAP, we develop a sparsity-based STAP algorithm. We observe that the interference spectrum is inherently sparse in the spatio-temporal domain,more » as the clutter responses occupy only a diagonal ridge on the spatio-temporal plane and the jammer signals interfere only from a few spatial directions. Hence, we exploit that sparsity to develop an efficient STAP technique that utilizes considerably lesser number of secondary data compared to the other existing STAP techniques, and produces nearly optimum STAP performance. In addition to designing the STAP filter, we optimally design the transmit OFDM signals by maximizing the output signal-to-interference-plus-noise ratio (SINR) in order to improve the STAP performance. The computation of output SINR depends on the estimated value of the interference covariance matrix, which we obtain by applying the sparse recovery algorithm. Therefore, we analytically assess the effects of the synthesized OFDM coefficients on the sparse recovery of the interference covariance matrix by computing the coherence measure of the sparse measurement matrix. Our numerical examples demonstrate the achieved STAP-performance due to sparsity-based technique and adaptive waveform design.« less

The recognition signal hypothesis for the adaptive evolution of religion : a phylogenetic test with Christian denominations.

PubMed

Matthews, Luke J

2012-06-01

Recent research on the evolution of religion has focused on whether religion is an unselected by-product of evolutionary processes or if it is instead an adaptation by natural selection. Adaptive hypotheses for religion include direct fitness benefits from improved health and indirect fitness benefits mediated by costly signals and/or cultural group selection. Herein, I propose that religious denominations achieve indirect fitness gains for members through the use of ecologically arbitrary beliefs, rituals, and moral rules that function as recognition markers of cultural inheritance analogous to kin and species recognition of genetic inheritance in biology. This recognition signal hypotheses could act in concert with either costly signaling or cultural group selection to produce evolutionarily altruistic behaviors within denominations. Using a cultural phylogenetic analysis, I show that a large set of religious behaviors among extant Christian denominations supports the prediction of the recognition signal hypothesis that characters change more frequently near historical schisms. By incorporating demographic data into the model, I show that more-distinctive denominations, as measured through dissimilar characteristics, appear to be protected from intrusion by nonmembers in mixed-denomination households, and that they may be experiencing greater biological growth of their populations even in the present day.

Adaptive Benefits of Storage Strategy and Dual AMPK/TOR Signaling in Metabolic Stress Response

PubMed Central

Pfeuty, Benjamin; Thommen, Quentin

2016-01-01

Cellular metabolism must ensure that supply of nutrient meets the biosynthetic and bioenergetic needs. Cells have therefore developed sophisticated signaling and regulatory pathways in order to cope with dynamic fluctuations of both resource and demand and to regulate accordingly diverse anabolic and catabolic processes. Intriguingly, these pathways are organized around a relatively small number of regulatory hubs, such as the highly conserved AMPK and TOR kinase families in eukaryotic cells. Here, the global metabolic adaptations upon dynamic environment are investigated using a prototypical model of regulated metabolism. In this model, the optimal enzyme profiles as well as the underlying regulatory architecture are identified by combining perturbation and evolutionary methods. The results reveal the existence of distinct classes of adaptive strategies, which differ in the management of storage reserve depending on the intensity of the stress and in the regulation of ATP-producing reaction depending on the nature of the stress. The regulatory architecture that optimally implements these adaptive features is characterized by a crosstalk between two specialized signaling pathways, which bears close similarities with the sensing and regulatory properties of AMPK and TOR pathways. PMID:27505075

Motion sickness and development of synergy within the spatial orientation system. A hypothetical unifying concept

NASA Technical Reports Server (NTRS)

Guedry, F. E.; Rupert, A. R.; Reschke, M. F.

1998-01-01

Adaptation to research paradigms such as rotating rooms and optical alteration of visual feedback during movement results in development of perceptual-motor programs that provide the reflexive assistance that is necessary to skilled control of movement and balance. The discomfort and stomach awareness that occur during the adaptation process has been attributed to conflicting sensory information about the state of motion. Vestibular signals depend on the kinematics of head movements irrespective of the presence or absence of signals from other senses. We propose that sensory conflict when vestibular signals are at least one component of the conflict are innately disturbing and unpleasant. This innate reaction is part of a continuum that operates early in life to prevent development of inefficient perceptual-motor programs. This reaction operates irrespective of and in addition to reward and punishment from parental guidance or goal attainment to yield efficient control of whole body movement in the operating environment of the individual. The same mechanism is involved in adapting the spatial orientation system to strange environments. This conceptual model "explains" why motion sickness is associated with adaptation to novel environments and is in general consistent with motion sickness literature.

Prostaglandin E2 promotes intestinal repair through an adaptive cellular response of the epithelium.

PubMed

Miyoshi, Hiroyuki; VanDussen, Kelli L; Malvin, Nicole P; Ryu, Stacy H; Wang, Yi; Sonnek, Naomi M; Lai, Chin-Wen; Stappenbeck, Thaddeus S

2017-01-04

Adaptive cellular responses are often required during wound repair. Following disruption of the intestinal epithelium, wound-associated epithelial (WAE) cells form the initial barrier over the wound. Our goal was to determine the critical factor that promotes WAE cell differentiation. Using an adaptation of our in vitro primary epithelial cell culture system, we found that prostaglandin E2 (PGE 2 ) signaling through one of its receptors, Ptger4, was sufficient to drive a differentiation state morphologically and transcriptionally similar to in vivo WAE cells. WAE cell differentiation was a permanent state and dominant over enterocyte differentiation in plasticity experiments. WAE cell differentiation was triggered by nuclear β-catenin signaling independent of canonical Wnt signaling. Creation of WAE cells via the PGE 2 -Ptger4 pathway was required in vivo, as mice with loss of Ptger4 in the intestinal epithelium did not produce WAE cells and exhibited impaired wound repair. Our results demonstrate a mechanism by which WAE cells are formed by PGE 2 and suggest a process of adaptive cellular reprogramming of the intestinal epithelium that occurs to ensure proper repair to injury. © 2016 The Authors.

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

PubMed Central

Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

PubMed

Wu, Hau-Tieng; Wu, Han-Kuei; Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

Proteomic changes in a childhood acute lymphoblastic leukemia cell line during the adaptation to vincristine.

PubMed

Guzmán-Ortiz, Ana Laura; Aparicio-Ozores, Gerardo; Valle-Rios, Ricardo; Medina-Contreras, Oscar; Patiño-López, Genaro; Quezada, Héctor

Relapse occurs in approximately 20% of Mexican patients with childhood acute lymphoblastic leukemia (ALL). In this group, chemoresistance may be one of the biggest challenges. An overview of complex cellular processes like drug tolerance can be achieved with proteomic studies. The B-lineage pediatric ALL cell line CCRF-SB was gradually exposed to the chemotherapeutic vincristine until proliferation was observed at 6nM, control cells were cultured in the absence of vincristine. The proteome from each group was analyzed by nanoHPLC coupled to an ESI-ion trap mass spectrometer. The identified proteins were grouped into overrepresented functional categories with the PANTHER classification system. We found 135 proteins exclusively expressed in the presence of vincristine. The most represented functional categories were: Toll receptor signaling pathway, Ras Pathway, B and T cell activation, CCKR signaling map, cytokine-mediated signaling pathway, and oxidative phosphorylation. Our study indicates that signal transduction and mitochondrial ATP production are essential during adaptation of leukemic cells to vincristine, these processes represent potential therapeutic targets. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Directional dual-tree complex wavelet packet transforms for processing quadrature signals.

PubMed

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2016-03-01

Quadrature signals containing in-phase and quadrature-phase components are used in many signal processing applications in every field of science and engineering. Specifically, Doppler ultrasound systems used to evaluate cardiovascular disorders noninvasively also result in quadrature format signals. In order to obtain directional blood flow information, the quadrature outputs have to be preprocessed using methods such as asymmetrical and symmetrical phasing filter techniques. These resultant directional signals can be employed in order to detect asymptomatic embolic signals caused by small emboli, which are indicators of a possible future stroke, in the cerebral circulation. Various transform-based methods such as Fourier and wavelet were frequently used in processing embolic signals. However, most of the times, the Fourier and discrete wavelet transforms are not appropriate for the analysis of embolic signals due to their non-stationary time-frequency behavior. Alternatively, discrete wavelet packet transform can perform an adaptive decomposition of the time-frequency axis. In this study, directional discrete wavelet packet transforms, which have the ability to map directional information while processing quadrature signals and have less computational complexity than the existing wavelet packet-based methods, are introduced. The performances of proposed methods are examined in detail by using single-frequency, synthetic narrow-band, and embolic quadrature signals.

Development of an Advanced, Automatic, Ultrasonic NDE Imaging System via Adaptive Learning Network Signal Processing Techniques

DTIC Science & Technology

1981-03-13

UNCLASSIFIED SECURITY CLAS,:FtfC ’i OF TH*!’ AGC W~ct P- A* 7~9r1) 0. ABSTRACT (continued) onuing in concert with a sophisticated detector has...and New York, 1969. Whalen, M.F., L.J. O’Brien, and A.N. Mucciardi, "Application of Adaptive Learning Netowrks for the Characterization of Two

Asymmetric Dual-Band Tracking Technique for Optimal Joint Processing of BDS B1I and B1C Signals

PubMed Central

Wang, Chuhan; Cui, Xiaowei; Ma, Tianyi; Lu, Mingquan

2017-01-01

Along with the rapid development of the Global Navigation Satellite System (GNSS), satellite navigation signals have become more diversified, complex, and agile in adapting to increasing market demands. Various techniques have been developed for processing multiple navigation signals to achieve better performance in terms of accuracy, sensitivity, and robustness. This paper focuses on a technique for processing two signals with separate but adjacent center frequencies, such as B1I and B1C signals in the BeiDou global system. The two signals may differ in modulation scheme, power, and initial phase relation and can be processed independently by user receivers; however, the propagation delays of the two signals from a satellite are nearly identical as they are modulated on adjacent frequencies, share the same reference clock, and undergo nearly identical propagation paths to the receiver, resulting in strong coherence between the two signals. Joint processing of these signals can achieve optimal measurement performance due to the increased Gabor bandwidth and power. In this paper, we propose a universal scheme of asymmetric dual-band tracking (ASYM-DBT) to take advantage of the strong coherence, the increased Gabor bandwidth, and power of the two signals in achieving much-reduced thermal noise and more accurate ranging results when compared with the traditional single-band algorithm. PMID:29035350

Asymmetric Dual-Band Tracking Technique for Optimal Joint Processing of BDS B1I and B1C Signals.

PubMed

Wang, Chuhan; Cui, Xiaowei; Ma, Tianyi; Zhao, Sihao; Lu, Mingquan

2017-10-16

Along with the rapid development of the Global Navigation Satellite System (GNSS), satellite navigation signals have become more diversified, complex, and agile in adapting to increasing market demands. Various techniques have been developed for processing multiple navigation signals to achieve better performance in terms of accuracy, sensitivity, and robustness. This paper focuses on a technique for processing two signals with separate but adjacent center frequencies, such as B1I and B1C signals in the BeiDou global system. The two signals may differ in modulation scheme, power, and initial phase relation and can be processed independently by user receivers; however, the propagation delays of the two signals from a satellite are nearly identical as they are modulated on adjacent frequencies, share the same reference clock, and undergo nearly identical propagation paths to the receiver, resulting in strong coherence between the two signals. Joint processing of these signals can achieve optimal measurement performance due to the increased Gabor bandwidth and power. In this paper, we propose a universal scheme of asymmetric dual-band tracking (ASYM-DBT) to take advantage of the strong coherence, the increased Gabor bandwidth, and power of the two signals in achieving much-reduced thermal noise and more accurate ranging results when compared with the traditional single-band algorithm.

Reducing Speckle In One-Look SAR Images

NASA Technical Reports Server (NTRS)

Nathan, K. S.; Curlander, J. C.

1990-01-01

Local-adaptive-filter algorithm incorporated into digital processing of synthetic-aperture-radar (SAR) echo data to reduce speckle in resulting imagery. Involves use of image statistics in vicinity of each picture element, in conjunction with original intensity of element, to estimate brightness more nearly proportional to true radar reflectance of corresponding target. Increases ratio of signal to speckle noise without substantial degradation of resolution common to multilook SAR images. Adapts to local variations of statistics within scene, preserving subtle details. Computationally simple. Lends itself to parallel processing of different segments of image, making possible increased throughput.

The research of PSD location method in micro laser welding fields

NASA Astrophysics Data System (ADS)

Zhang, Qiue; Zhang, Rong; Dong, Hua

2010-11-01

In the field of micro laser welding, besides the special requirement in the parameter of lasers, the locating in welding points accurately is very important. The article adopt position sensitive detector (PSD) as hard core, combine optic system, electric circuits and PC and software processing, confirm the location of welding points. The signal detection circuits adopt the special integrate circuit H-2476 to process weak signal. It is an integrated circuit for high-speed, high-sensitivity optical range finding, which has stronger noiseproof feature, combine digital filter arithmetic, carry out repair the any non-ideal factors, increasing the measure precision. The amplifier adopt programmable amplifier LTC6915. The system adapt two dimension stepping motor drive the workbench, computer and corresponding software processing, make sure the location of spot weld. According to different workpieces to design the clamps. The system on-line detect PSD 's output signal in the moving processing. At the workbench moves in the X direction, the filaments offset is detected dynamic. Analyze the X axes moving sampling signal direction could be estimate the Y axes moving direction, and regulate the Y axes moving values. The workbench driver adopt A3979, it is a stepping motor driver with insert transducer and operate easily. It adapts the requirement of location in micro laser welding fields, real-time control to adjust by computer. It can be content up 20 μm's laser micro welding requirement on the whole. Using laser powder cladding technology achieve inter-penetration welding of high quality and reliability.

Short-term saccadic adaptation in the macaque monkey: a binocular mechanism

PubMed Central

Schultz, K. P.

2013-01-01

Saccadic eye movements are rapid transfers of gaze between objects of interest. Their duration is too short for the visual system to be able to follow their progress in time. Adaptive mechanisms constantly recalibrate the saccadic responses by detecting how close the landings are to the selected targets. The double-step saccadic paradigm is a common method to simulate alterations in saccadic gain. While the subject is responding to a first target shift, a second shift is introduced in the middle of this movement, which masks it from visual detection. The error in landing introduced by the second shift is interpreted by the brain as an error in the programming of the initial response, with gradual gain changes aimed at compensating the apparent sensorimotor mismatch. A second shift applied dichoptically to only one eye introduces disconjugate landing errors between the two eyes. A monocular adaptive system would independently modify only the gain of the eye exposed to the second shift in order to reestablish binocular alignment. Our results support a binocular mechanism. A version-based saccadic adaptive process detects postsaccadic version errors and generates compensatory conjugate gain alterations. A vergence-based saccadic adaptive process detects postsaccadic disparity errors and generates corrective nonvisual disparity signals that are sent to the vergence system to regain binocularity. This results in striking dynamical similarities between visually driven combined saccade-vergence gaze transfers, where the disparity is given by the visual targets, and the double-step adaptive disconjugate responses, where an adaptive disparity signal is generated internally by the saccadic system. PMID:23076111

Reduced error signalling in medication-naive children with ADHD: associations with behavioural variability and post-error adaptations

PubMed Central

Plessen, Kerstin J.; Allen, Elena A.; Eichele, Heike; van Wageningen, Heidi; Høvik, Marie Farstad; Sørensen, Lin; Worren, Marius Kalsås; Hugdahl, Kenneth; Eichele, Tom

2016-01-01

Background We examined the blood-oxygen level–dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). Methods We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8–12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations. Results We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. Limitations Our study was limited by the modest sample size and imperfect matching across groups. Conclusion Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD. PMID:26441332

Optimization of an organic memristor as an adaptive memory element

NASA Astrophysics Data System (ADS)

Berzina, Tatiana; Smerieri, Anteo; Bernabò, Marco; Pucci, Andrea; Ruggeri, Giacomo; Erokhin, Victor; Fontana, M. P.

2009-06-01

The combination of memory and signal handling characteristics of a memristor makes it a promising candidate for adaptive bioinspired information processing systems. This poses stringent requirements on the basic device, such as stability and reproducibility over a large number of training/learning cycles, and a large anisotropy in the fundamental control material parameter, in our case the electrical conductivity. In this work we report results on the improved performance of electrochemically controlled polymeric memristors, where optimization of a conducting polymer (polyaniline) in the active channel and better environmental control of fabrication methods led to a large increase both in the absolute values of the conductivity in the partially oxydized state of polyaniline and of the on-off conductivity ratio. These improvements are crucial for the application of the organic memristor to adaptive complex signal handling networks.

Photorefractive Integrators and Correlators

DTIC Science & Technology

1992-12-01

The use of photorefractive crystals as optically addressed time integrating spatial light modulators in acousto - optic signal processing applications...adaptive acousto - optic processor. These results demonstrated the feasibility of using photorefractives for such applications.... Photorefractive, Acousto - optic processor.

The T-cell-specific adapter protein family: TSAd, ALX, and SH2D4A/SH2D4B.

PubMed

Lapinski, Philip E; Oliver, Jennifer A; Bodie, Jennifer N; Marti, Francesc; King, Philip D

2009-11-01

Adapter proteins play key roles in intracellular signal transduction through complex formation with catalytically active signaling molecules. In T lymphocytes, the role of several different types of adapter proteins in T-cell antigen receptor signal transduction is well established. An exception to this is the family of T-cell-specific adapter (TSAd) proteins comprising of TSAd, adapter protein of unknown function (ALX), SH2D4A, and SH2D4B. Only recently has the function of these adapters in T-cell signal transduction been explored. Here, we discuss advances in our understanding of the role of this family of adapter proteins in T cells. Their function as regulators of signal transduction in other cell types is also discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierre, John W.; Wies, Richard; Trudnowski, Daniel

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacificmore » Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements.« less

Towards a Cognitive Radar: Canada's Third-Generation High Frequency Surface Wave Radar (HFSWR) for Surveillance of the 200 Nautical Mile Exclusive Economic Zone.

PubMed

Ponsford, Anthony; McKerracher, Rick; Ding, Zhen; Moo, Peter; Yee, Derek

2017-07-07

Canada's third-generation HFSWR forms the foundation of a maritime domain awareness system that provides enforcement agencies with real-time persistent surveillance out to and beyond the 200 nautical mile exclusive economic zone (EEZ). Cognitive sense-and-adapt technology and dynamic spectrum management ensures robust and resilient operation in the highly congested High Frequency (HF) band. Dynamic spectrum access enables the system to simultaneously operate on two frequencies on a non-interference and non-protected basis, without impacting other spectrum users. Sense-and-adapt technologies ensure that the system instantaneously switches to a new vacant channel on the detection of another user or unwanted jamming signal. Adaptive signal processing techniques mitigate against electrical noise, interference and clutter. Sense-and-adapt techniques applied at the detector and tracker stages maximize the probability of track initiation whilst minimizing the probability of false or otherwise erroneous track data.

Coordinated dynamic encoding in the retina using opposing forms of plasticity

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2011-01-01

The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice, and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization—a persistent elevated sensitivity following a strong stimulus. This novel dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals, and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails. PMID:21909086

Towards a Cognitive Radar: Canada’s Third-Generation High Frequency Surface Wave Radar (HFSWR) for Surveillance of the 200 Nautical Mile Exclusive Economic Zone

PubMed Central

Ponsford, Anthony; McKerracher, Rick; Ding, Zhen; Moo, Peter; Yee, Derek

2017-01-01

Canada’s third-generation HFSWR forms the foundation of a maritime domain awareness system that provides enforcement agencies with real-time persistent surveillance out to and beyond the 200 nautical mile exclusive economic zone (EEZ). Cognitive sense-and-adapt technology and dynamic spectrum management ensures robust and resilient operation in the highly congested High Frequency (HF) band. Dynamic spectrum access enables the system to simultaneously operate on two frequencies on a non-interference and non-protected basis, without impacting other spectrum users. Sense-and-adapt technologies ensure that the system instantaneously switches to a new vacant channel on the detection of another user or unwanted jamming signal. Adaptive signal processing techniques mitigate against electrical noise, interference and clutter. Sense-and-adapt techniques applied at the detector and tracker stages maximize the probability of track initiation whilst minimizing the probability of false or otherwise erroneous track data. PMID:28686198

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

Spatially adaptive migration tomography for multistatic GPR imaging

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2013-08-13

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.

PubMed

McFarland, Dennis J; Krusienski, Dean J; Wolpaw, Jonathan R

2006-01-01

The Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.

Challenges and Recent Developments in Hearing Aids: Part I. Speech Understanding in Noise, Microphone Technologies and Noise Reduction Algorithms

PubMed Central

Chung, King

2004-01-01

This review discusses the challenges in hearing aid design and fitting and the recent developments in advanced signal processing technologies to meet these challenges. The first part of the review discusses the basic concepts and the building blocks of digital signal processing algorithms, namely, the signal detection and analysis unit, the decision rules, and the time constants involved in the execution of the decision. In addition, mechanisms and the differences in the implementation of various strategies used to reduce the negative effects of noise are discussed. These technologies include the microphone technologies that take advantage of the spatial differences between speech and noise and the noise reduction algorithms that take advantage of the spectral difference and temporal separation between speech and noise. The specific technologies discussed in this paper include first-order directional microphones, adaptive directional microphones, second-order directional microphones, microphone matching algorithms, array microphones, multichannel adaptive noise reduction algorithms, and synchrony detection noise reduction algorithms. Verification data for these technologies, if available, are also summarized. PMID:15678225

Distinct brain networks for adaptive and stable task control in humans

PubMed Central

Dosenbach, Nico U. F.; Fair, Damien A.; Miezin, Francis M.; Cohen, Alexander L.; Wenger, Kristin K.; Dosenbach, Ronny A. T.; Fox, Michael D.; Snyder, Abraham Z.; Vincent, Justin L.; Raichle, Marcus E.; Schlaggar, Bradley L.; Petersen, Steven E.

2007-01-01

Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms. PMID:17576922

Adaptive sleep-wake discrimination for wearable devices.

PubMed

Karlen, Walter; Floreano, Dario

2011-04-01

Sleep/wake classification systems that rely on physiological signals suffer from intersubject differences that make accurate classification with a single, subject-independent model difficult. To overcome the limitations of intersubject variability, we suggest a novel online adaptation technique that updates the sleep/wake classifier in real time. The objective of the present study was to evaluate the performance of a newly developed adaptive classification algorithm that was embedded on a wearable sleep/wake classification system called SleePic. The algorithm processed ECG and respiratory effort signals for the classification task and applied behavioral measurements (obtained from accelerometer and press-button data) for the automatic adaptation task. When trained as a subject-independent classifier algorithm, the SleePic device was only able to correctly classify 74.94 ± 6.76% of the human-rated sleep/wake data. By using the suggested automatic adaptation method, the mean classification accuracy could be significantly improved to 92.98 ± 3.19%. A subject-independent classifier based on activity data only showed a comparable accuracy of 90.44 ± 3.57%. We demonstrated that subject-independent models used for online sleep-wake classification can successfully be adapted to previously unseen subjects without the intervention of human experts or off-line calibration.

Development of a Real Time Sparse Non-Negative Matrix Factorization Module for Cochlear Implants by Using xPC Target

PubMed Central

Hu, Hongmei; Krasoulis, Agamemnon; Lutman, Mark; Bleeck, Stefan

2013-01-01

Cochlear implants (CIS) require efficient speech processing to maximize information transmission to the brain, especially in noise. A novel CI processing strategy was proposed in our previous studies, in which sparsity-constrained non-negative matrix factorization (NMF) was applied to the envelope matrix in order to improve the CI performance in noisy environments. It showed that the algorithm needs to be adaptive, rather than fixed, in order to adjust to acoustical conditions and individual characteristics. Here, we explore the benefit of a system that allows the user to adjust the signal processing in real time according to their individual listening needs and their individual hearing capabilities. In this system, which is based on MATLAB®, SIMULINK® and the xPC Target™ environment, the input/outupt (I/O) boards are interfaced between the SIMULINK blocks and the CI stimulation system, such that the output can be controlled successfully in the manner of a hardware-in-the-loop (HIL) simulation, hence offering a convenient way to implement a real time signal processing module that does not require any low level language. The sparsity constrained parameter of the algorithm was adapted online subjectively during an experiment with normal-hearing subjects and noise vocoded speech simulation. Results show that subjects chose different parameter values according to their own intelligibility preferences, indicating that adaptive real time algorithms are beneficial to fully explore subjective preferences. We conclude that the adaptive real time systems are beneficial for the experimental design, and such systems allow one to conduct psychophysical experiments with high ecological validity. PMID:24129021

Development of a real time sparse non-negative matrix factorization module for cochlear implants by using xPC target.

PubMed

Hu, Hongmei; Krasoulis, Agamemnon; Lutman, Mark; Bleeck, Stefan

2013-10-14

Cochlear implants (CIs) require efficient speech processing to maximize information transmission to the brain, especially in noise. A novel CI processing strategy was proposed in our previous studies, in which sparsity-constrained non-negative matrix factorization (NMF) was applied to the envelope matrix in order to improve the CI performance in noisy environments. It showed that the algorithm needs to be adaptive, rather than fixed, in order to adjust to acoustical conditions and individual characteristics. Here, we explore the benefit of a system that allows the user to adjust the signal processing in real time according to their individual listening needs and their individual hearing capabilities. In this system, which is based on MATLAB®, SIMULINK® and the xPC Target™ environment, the input/outupt (I/O) boards are interfaced between the SIMULINK blocks and the CI stimulation system, such that the output can be controlled successfully in the manner of a hardware-in-the-loop (HIL) simulation, hence offering a convenient way to implement a real time signal processing module that does not require any low level language. The sparsity constrained parameter of the algorithm was adapted online subjectively during an experiment with normal-hearing subjects and noise vocoded speech simulation. Results show that subjects chose different parameter values according to their own intelligibility preferences, indicating that adaptive real time algorithms are beneficial to fully explore subjective preferences. We conclude that the adaptive real time systems are beneficial for the experimental design, and such systems allow one to conduct psychophysical experiments with high ecological validity.

Principles of Adaptive Array Processing

DTIC Science & Technology

2006-09-01

ACE with and without tapering (homogeneous case). These analytical results are less suited to predict the detection performance of a real system ...Nickel: Adaptive Beamforming for Phased Array Radars. Proc. Int. Radar Symposium IRS’98 (Munich, Sept. 1998), DGON and VDE /ITG, pp. 897-906.(Reprint also...strategies for airborne radar. Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, CA, 1998, IEEE Cat.Nr. 0-7803-5148-7/98, pp. 1327-1331. [17

Interactions between motion and form processing in the human visual system.

PubMed

Mather, George; Pavan, Andrea; Bellacosa Marotti, Rosilari; Campana, Gianluca; Casco, Clara

2013-01-01

The predominant view of motion and form processing in the human visual system assumes that these two attributes are handled by separate and independent modules. Motion processing involves filtering by direction-selective sensors, followed by integration to solve the aperture problem. Form processing involves filtering by orientation-selective and size-selective receptive fields, followed by integration to encode object shape. It has long been known that motion signals can influence form processing in the well-known Gestalt principle of common fate; texture elements which share a common motion property are grouped into a single contour or texture region. However, recent research in psychophysics and neuroscience indicates that the influence of form signals on motion processing is more extensive than previously thought. First, the salience and apparent direction of moving lines depends on how the local orientation and direction of motion combine to match the receptive field properties of motion-selective neurons. Second, orientation signals generated by "motion-streaks" influence motion processing; motion sensitivity, apparent direction and adaptation are affected by simultaneously present orientation signals. Third, form signals generated by human body shape influence biological motion processing, as revealed by studies using point-light motion stimuli. Thus, form-motion integration seems to occur at several different levels of cortical processing, from V1 to STS.

Interactions between motion and form processing in the human visual system

PubMed Central

Mather, George; Pavan, Andrea; Bellacosa Marotti, Rosilari; Campana, Gianluca; Casco, Clara

2013-01-01

The predominant view of motion and form processing in the human visual system assumes that these two attributes are handled by separate and independent modules. Motion processing involves filtering by direction-selective sensors, followed by integration to solve the aperture problem. Form processing involves filtering by orientation-selective and size-selective receptive fields, followed by integration to encode object shape. It has long been known that motion signals can influence form processing in the well-known Gestalt principle of common fate; texture elements which share a common motion property are grouped into a single contour or texture region. However, recent research in psychophysics and neuroscience indicates that the influence of form signals on motion processing is more extensive than previously thought. First, the salience and apparent direction of moving lines depends on how the local orientation and direction of motion combine to match the receptive field properties of motion-selective neurons. Second, orientation signals generated by “motion-streaks” influence motion processing; motion sensitivity, apparent direction and adaptation are affected by simultaneously present orientation signals. Third, form signals generated by human body shape influence biological motion processing, as revealed by studies using point-light motion stimuli. Thus, form-motion integration seems to occur at several different levels of cortical processing, from V1 to STS. PMID:23730286

Whipworm kinomes reflect a unique biology and adaptation to the host animal.

PubMed

Stroehlein, Andreas J; Young, Neil D; Korhonen, Pasi K; Chang, Bill C H; Nejsum, Peter; Pozio, Edoardo; La Rosa, Giuseppe; Sternberg, Paul W; Gasser, Robin B

2017-11-01

Roundworms belong to a diverse phylum (Nematoda) which is comprised of many parasitic species including whipworms (genus Trichuris). These worms have adapted to a biological niche within the host and exhibit unique morphological characteristics compared with other nematodes. Although these adaptations are known, the underlying molecular mechanisms remain elusive. The availability of genomes and transcriptomes of some whipworms now enables detailed studies of their molecular biology. Here, we defined and curated the full complement of an important class of enzymes, the protein kinases (kinomes) of two species of Trichuris, using an advanced and integrated bioinformatic pipeline. We investigated the transcription of Trichuris suis kinase genes across developmental stages, sexes and tissues, and reveal that selectively transcribed genes can be linked to central roles in developmental and reproductive processes. We also classified and functionally annotated the curated kinomes by integrating evidence from structural modelling and pathway analyses, and compared them with other curated kinomes of phylogenetically diverse nematode species. Our findings suggest unique adaptations in signalling processes governing worm morphology and biology, and provide an important resource that should facilitate experimental investigations of kinases and the biology of signalling pathways in nematodes. Copyright © 2017 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

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.

Terabit bandwidth-adaptive transmission using low-complexity format-transparent digital signal processing.

PubMed

Zhuge, Qunbi; Morsy-Osman, Mohamed; Chagnon, Mathieu; Xu, Xian; Qiu, Meng; Plant, David V

2014-02-10

In this paper, we propose a low-complexity format-transparent digital signal processing (DSP) scheme for next generation flexible and energy-efficient transceiver. It employs QPSK symbols as the training and pilot symbols for the initialization and tracking stage of the receiver-side DSP, respectively, for various modulation formats. The performance is numerically and experimentally evaluated in a dual polarization (DP) 11 Gbaud 64QAM system. Employing the proposed DSP scheme, we conduct a system-level study of Tb/s bandwidth-adaptive superchannel transmissions with flexible modulation formats including QPSK, 8QAM and 16QAM. The spectrum bandwidth allocation is realized in the digital domain instead of turning on/off sub-channels, which improves the performance of higher order QAM. Various transmission distances ranging from 240 km to 6240 km are demonstrated with a colorless detection for hardware complexity reduction.

Receptoral and postreceptoral visual processes in recovery from chromatic adaptation.

PubMed Central

Jameson, D; Hurvich, L M; Varner, F D

1979-01-01

The time course of recovery from chromatic adaptation in human vision was tracked by determining the wavelength of light that appears uniquely yellow (neither red nor green) both before and after exposure to yellowish green and yellowish red adapting lights. Recovery is complete within 5 min after steady light exposure. After exposure to the alternating repeated sequence 10-sec light/10-sec dark, the initial magnitude of the aftereffect is reduced but recovery is retarded. The results are interpreted in terms of two processes located at different levels in the hierarchical organization of the visual system. One is a change in the balance of cone receptor sensitivities; the second is a shift in the equilibrium baseline between opposite-signed responses of the red/green channel at the opponent-process neural level. The baseline-shift mechanism is effective in the condition in which repeated input signals originating at the receptors are of sufficient strength to activate the system effectively. Hence, this process is revealed in the alternating adaptation condition when the receptors undergo partial recovery after each light exposure, but receptor adaptation during continued steady light exposure effectively protects the subsequent neural systems from continued strong activation. PMID:288087

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, Tianyou; Jia, Yao; Wang, Hong

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperaturemore » are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.« less

Plants under Stress: Involvement of Auxin and Cytokinin

PubMed Central

Bielach, Agnieszka; Hrtyan, Monika; Tognetti, Vanesa B.

2017-01-01

Plant growth and development are critically influenced by unpredictable abiotic factors. To survive fluctuating changes in their environments, plants have had to develop robust adaptive mechanisms. The dynamic and complementary actions of the auxin and cytokinin pathways regulate a plethora of developmental processes, and their ability to crosstalk makes them ideal candidates for mediating stress-adaptation responses. Other crucial signaling molecules responsible for the tremendous plasticity observed in plant morphology and in response to abiotic stress are reactive oxygen species (ROS). Proper temporal and spatial distribution of ROS and hormone gradients is crucial for plant survival in response to unfavorable environments. In this regard, the convergence of ROS with phytohormone pathways acts as an integrator of external and developmental signals into systemic responses organized to adapt plants to their environments. Auxin and cytokinin signaling pathways have been studied extensively. Nevertheless, we do not yet understand the impact on plant stress tolerance of the sophisticated crosstalk between the two hormones. Here, we review current knowledge on the function of auxin and cytokinin in redirecting growth induced by abiotic stress in order to deduce their potential points of crosstalk. PMID:28677656

Plants under Stress: Involvement of Auxin and Cytokinin.

PubMed

Bielach, Agnieszka; Hrtyan, Monika; Tognetti, Vanesa B

2017-07-04

Plant growth and development are critically influenced by unpredictable abiotic factors. To survive fluctuating changes in their environments, plants have had to develop robust adaptive mechanisms. The dynamic and complementary actions of the auxin and cytokinin pathways regulate a plethora of developmental processes, and their ability to crosstalk makes them ideal candidates for mediating stress-adaptation responses. Other crucial signaling molecules responsible for the tremendous plasticity observed in plant morphology and in response to abiotic stress are reactive oxygen species (ROS). Proper temporal and spatial distribution of ROS and hormone gradients is crucial for plant survival in response to unfavorable environments. In this regard, the convergence of ROS with phytohormone pathways acts as an integrator of external and developmental signals into systemic responses organized to adapt plants to their environments. Auxin and cytokinin signaling pathways have been studied extensively. Nevertheless, we do not yet understand the impact on plant stress tolerance of the sophisticated crosstalk between the two hormones. Here, we review current knowledge on the function of auxin and cytokinin in redirecting growth induced by abiotic stress in order to deduce their potential points of crosstalk.

Neurotrophin and FGF Signaling Adapter Proteins, FRS2 and FRS3, Regulate Dentate Granule Cell Maturation and Excitatory Synaptogenesis.

PubMed

Nandi, Sayan; Alviña, Karina; Lituma, Pablo J; Castillo, Pablo E; Hébert, Jean M

2018-01-15

Dentate granule cells (DGCs) play important roles in cognitive processes. Knowledge about how growth factors such as FGFs and neurotrophins contribute to the maturation and synaptogenesis of DGCs is limited. Here, using brain-specific and germline mouse mutants we show that a module of neurotrophin and FGF signaling, the FGF Receptor Substrate (FRS) family of intracellular adapters, FRS2 and FRS3, are together required for postnatal brain development. In the hippocampus, FRS promotes dentate gyrus morphogenesis and DGC maturation during developmental neurogenesis, similar to previously published functions for both neurotrophins and FGFs. Consistent with a role in DGC maturation, two-photon imaging revealed that Frs2,3-double mutants have reduced numbers of dendritic branches and spines in DGCs. Functional analysis further showed that double-mutant mice exhibit fewer excitatory synaptic inputs onto DGCs. These observations reveal roles for FRS adapters in DGC maturation and synaptogenesis and suggest that FRS proteins may act as an important node for FGF and neurotrophin signaling in postnatal hippocampal development. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

A comparative evaluation of adaptive noise cancellation algorithms for minimizing motion artifacts in a forehead-mounted wearable pulse oximeter.

PubMed

Comtois, Gary; Mendelson, Yitzhak; Ramuka, Piyush

2007-01-01

Wearable physiological monitoring using a pulse oximeter would enable field medics to monitor multiple injuries simultaneously, thereby prioritizing medical intervention when resources are limited. However, a primary factor limiting the accuracy of pulse oximetry is poor signal-to-noise ratio since photoplethysmographic (PPG) signals, from which arterial oxygen saturation (SpO2) and heart rate (HR) measurements are derived, are compromised by movement artifacts. This study was undertaken to quantify SpO2 and HR errors induced by certain motion artifacts utilizing accelerometry-based adaptive noise cancellation (ANC). Since the fingers are generally more vulnerable to motion artifacts, measurements were performed using a custom forehead-mounted wearable pulse oximeter developed for real-time remote physiological monitoring and triage applications. This study revealed that processing motion-corrupted PPG signals by least mean squares (LMS) and recursive least squares (RLS) algorithms can be effective to reduce SpO2 and HR errors during jogging, but the degree of improvement depends on filter order. Although both algorithms produced similar improvements, implementing the adaptive LMS algorithm is advantageous since it requires significantly less operations.

Signal processing methodologies for an acoustic fetal heart rate monitor

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III; Stoughton, John W.

1992-01-01

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Electroencephalographic compression based on modulated filter banks and wavelet transform.

PubMed

Bazán-Prieto, Carlos; Cárdenas-Barrera, Julián; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando

2011-01-01

Due to the large volume of information generated in an electroencephalographic (EEG) study, compression is needed for storage, processing or transmission for analysis. In this paper we evaluate and compare two lossy compression techniques applied to EEG signals. It compares the performance of compression schemes with decomposition by filter banks or wavelet Packets transformation, seeking the best value for compression, best quality and more efficient real time implementation. Due to specific properties of EEG signals, we propose a quantization stage adapted to the dynamic range of each band, looking for higher quality. The results show that the compressor with filter bank performs better than transform methods. Quantization adapted to the dynamic range significantly enhances the quality.

Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

NASA Astrophysics Data System (ADS)

Yang, Jian; Yang, Feng; Xi, Hong-Sheng; Guo, Wei; Sheng, Yanmin

2007-12-01

We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

Roles of mitochondrial energy dissipation systems in plant development and acclimation to stress.

PubMed

Pu, Xiaojun; Lv, Xin; Tan, Tinghong; Fu, Faqiong; Qin, Gongwei; Lin, Honghui

2015-09-01

Plants are sessile organisms that have the ability to integrate external cues into metabolic and developmental signals. The cues initiate specific signal cascades that can enhance the tolerance of plants to stress, and these mechanisms are crucial to the survival and fitness of plants. The adaption of plants to stresses is a complex process that involves decoding stress inputs as energy-deficiency signals. The process functions through vast metabolic and/or transcriptional reprogramming to re-establish the cellular energy balance. Members of the mitochondrial energy dissipation pathway (MEDP), alternative oxidases (AOXs) and uncoupling proteins (UCPs), act as energy mediators and might play crucial roles in the adaption of plants to stresses. However, their roles in plant growth and development have been relatively less explored. This review summarizes current knowledge about the role of members of the MEDP in plant development as well as recent advances in identifying molecular components that regulate the expression of AOXs and UCPs. Highlighted in particular is a comparative analysis of the expression, regulation and stress responses between AOXs and UCPs when plants are exposed to stresses, and a possible signal cross-talk that orchestrates the MEDP, reactive oxygen species (ROS), calcium signalling and hormone signalling. The MEDP might act as a cellular energy/metabolic mediator that integrates ROS signalling, energy signalling and hormone signalling with plant development and stress accumulation. However, the regulation of MEDP members is complex and occurs at transcriptional, translational, post-translational and metabolic levels. How this regulation is linked to actual fluxes through the AOX/UCP in vivo remains elusive. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An FPGA-based High Speed Parallel Signal Processing System for Adaptive Optics Testbed

NASA Astrophysics Data System (ADS)

Kim, H.; Choi, Y.; Yang, Y.

In this paper a state-of-the-art FPGA (Field Programmable Gate Array) based high speed parallel signal processing system (SPS) for adaptive optics (AO) testbed with 1 kHz wavefront error (WFE) correction frequency is reported. The AO system consists of Shack-Hartmann sensor (SHS) and deformable mirror (DM), tip-tilt sensor (TTS), tip-tilt mirror (TTM) and an FPGA-based high performance SPS to correct wavefront aberrations. The SHS is composed of 400 subapertures and the DM 277 actuators with Fried geometry, requiring high speed parallel computing capability SPS. In this study, the target WFE correction speed is 1 kHz; therefore, it requires massive parallel computing capabilities as well as strict hard real time constraints on measurements from sensors, matrix computation latency for correction algorithms, and output of control signals for actuators. In order to meet them, an FPGA based real-time SPS with parallel computing capabilities is proposed. In particular, the SPS is made up of a National Instrument's (NI's) real time computer and five FPGA boards based on state-of-the-art Xilinx Kintex 7 FPGA. Programming is done with NI's LabView environment, providing flexibility when applying different algorithms for WFE correction. It also facilitates faster programming and debugging environment as compared to conventional ones. One of the five FPGA's is assigned to measure TTS and calculate control signals for TTM, while the rest four are used to receive SHS signal, calculate slops for each subaperture and correction signal for DM. With this parallel processing capabilities of the SPS the overall closed-loop WFE correction speed of 1 kHz has been achieved. System requirements, architecture and implementation issues are described; furthermore, experimental results are also given.

Improved signal recovery for flow cytometry based on ‘spatially modulated emission’

NASA Astrophysics Data System (ADS)

Quint, S.; Wittek, J.; Spang, P.; Levanon, N.; Walther, T.; Baßler, M.

2017-09-01

Recently, the technique of ‘spatially modulated emission’ has been introduced (Baßler et al 2008 US Patent 0080181827A1; Kiesel et al 2009 Appl. Phys. Lett. 94 041107; Kiesel et al 2011 Cytometry A 79A 317-24) improving the signal-to-noise ratio (SNR) for detecting bio-particles in the field of flow cytometry. Based on this concept, we developed two advanced signal processing methods which further enhance the SNR and selectivity for cell detection. The improvements are achieved by adapting digital filtering methods from RADAR technology and mainly address inherent offset elimination, increased signal dynamics and moreover reduction of erroneous detections due to processing artifacts. We present a comprehensive theory on SNR gain and provide experimental results of our concepts.

Phylogenetic context determines the role of competition in adaptive radiation

PubMed Central

Tan, Jiaqi; Slattery, Matthew R.; Yang, Xian; Jiang, Lin

2016-01-01

Understanding ecological mechanisms regulating the evolution of biodiversity is of much interest to ecologists and evolutionary biologists. Adaptive radiation constitutes an important evolutionary process that generates biodiversity. Competition has long been thought to influence adaptive radiation, but the directionality of its effect and associated mechanisms remain ambiguous. Here, we report a rigorous experimental test of the role of competition on adaptive radiation using the rapidly evolving bacterium Pseudomonas fluorescens SBW25 interacting with multiple bacterial species that differed in their phylogenetic distance to the diversifying bacterium. We showed that the inhibitive effect of competitors on the adaptive radiation of P. fluorescens decreased as their phylogenetic distance increased. To explain this phylogenetic dependency of adaptive radiation, we linked the phylogenetic distance between P. fluorescens and its competitors to their niche and competitive fitness differences. Competitive fitness differences, which showed weak phylogenetic signal, reduced P. fluorescens abundance and thus diversification, whereas phylogenetically conserved niche differences promoted diversification. These results demonstrate the context dependency of competitive effects on adaptive radiation, and highlight the importance of past evolutionary history for ongoing evolutionary processes. PMID:27335414

Radiation-hardened fast acquisition/weak signal tracking system and method

NASA Technical Reports Server (NTRS)

Winternitz, Luke (Inventor); Boegner, Gregory J. (Inventor); Sirotzky, Steve (Inventor)

2009-01-01

A global positioning system (GPS) receiver and method of acquiring and tracking GPS signals comprises an antenna adapted to receive GPS signals; an analog radio frequency device operatively connected to the antenna and adapted to convert the GPS signals from an analog format to a digital format; a plurality of GPS signal tracking correlators operatively connected to the analog RF device; a GPS signal acquisition component operatively connected to the analog RF device and the plurality of GPS signal tracking correlators, wherein the GPS signal acquisition component is adapted to calculate a maximum vector on a databit correlation grid; and a microprocessor operatively connected to the plurality of GPS signal tracking correlators and the GPS signal acquisition component, wherein the microprocessor is adapted to compare the maximum vector with a predetermined correlation threshold to allow the GPS signal to be fully acquired and tracked.

Development of nanoscale structure in LAT-based signaling complexes

PubMed Central

2016-01-01

ABSTRACT The adapter molecule linker for activation of T cells (LAT) plays a crucial role in forming signaling complexes induced by stimulation of the T cell receptor (TCR). These multi-molecular complexes are dynamic structures that activate highly regulated signaling pathways. Previously, we have demonstrated nanoscale structure in LAT-based complexes where the adapter SLP-76 (also known as LCP2) localizes to the periphery of LAT clusters. In this study, we show that initially LAT and SLP-76 are randomly dispersed throughout the clusters that form upon TCR engagement. The segregation of LAT and SLP-76 develops near the end of the spreading process. The local concentration of LAT also increases at the same time. Both changes require TCR activation and an intact actin cytoskeleton. These results demonstrate that the nanoscale organization of LAT-based signaling complexes is dynamic and indicates that different kinds of LAT-based complexes appear at different times during T cell activation. PMID:27875277

Anxiety dissociates the adaptive functions of sensory and motor response enhancements to social threats

PubMed Central

El Zein, Marwa; Wyart, Valentin; Grèzes, Julie

2015-01-01

Efficient detection and reaction to negative signals in the environment is essential for survival. In social situations, these signals are often ambiguous and can imply different levels of threat for the observer, thereby making their recognition susceptible to contextual cues – such as gaze direction when judging facial displays of emotion. However, the mechanisms underlying such contextual effects remain poorly understood. By computational modeling of human behavior and electrical brain activity, we demonstrate that gaze direction enhances the perceptual sensitivity to threat-signaling emotions – anger paired with direct gaze, and fear paired with averted gaze. This effect arises simultaneously in ventral face-selective and dorsal motor cortices at 200 ms following face presentation, dissociates across individuals as a function of anxiety, and does not reflect increased attention to threat-signaling emotions. These findings reveal that threat tunes neural processing in fast, selective, yet attention-independent fashion in sensory and motor systems, for different adaptive purposes. DOI: http://dx.doi.org/10.7554/eLife.10274.001 PMID:26712157

VLC-beacon detection with an under-sampled ambient light sensor

NASA Astrophysics Data System (ADS)

Green, Jacob; Pérez-Olivas, Huetzin; Martínez-Díaz, Saúl; García-Márquez, Jorge; Domínguez-González, Carlos; Santiago-Montero, Raúl; Guan, Hongyu; Rozenblat, Marc; Topsu, Suat

2017-08-01

LEDs will replace in a near future the current worldwide lighting mainly due to their low production-cost and energy-saving assets. Visible light communications (VLC) will turn gradually the existing lighting network into a communication network. Nowadays VLC transceivers can be found in some commercial centres in Europe; some of them broadcast continuously an identification tag that contains its coordinate position. In such a case, the transceiver acts as a geolocation beacon. Nevertheless, mobile transceivers represent a challenge in the VLC communication chain, as smartphones have not integrated yet a VLC customized detection stage. In order to make current smartphones capable to detect VLC broadcasted signals, their Ambient Light Sensor (ALS) is adapted as a VLC detector. For this to be achieved, lighting transceivers need to adapt their modulation scheme. For instance, frequencies representing start bit, 1, and 0 logic values can be set to avoid flicker from illumination and to permit detecting the under-sampled signal. Decoding the signal requires a multiple steps real-time signal processing as shown here.

Focused cognitive control in dishonesty: Evidence for predominantly transient conflict adaptation.

PubMed

Foerster, Anna; Pfister, Roland; Schmidts, Constantin; Dignath, David; Wirth, Robert; Kunde, Wilfried

2018-04-01

Giving a dishonest response to a question entails cognitive conflict due to an initial activation of the truthful response. Following conflict monitoring theory, dishonest responding could therefore elicit transient and sustained control adaptation processes to mitigate such conflict, and the current experiments take on the scope and specificity of such conflict adaptation in dishonesty. Transient adaptation reduces differences between honest and dishonest responding following a recent dishonest response. Sustained adaptation has a similar behavioral signature but is driven by the overall frequency of dishonest responding. Both types of adaptation to recent and frequent dishonest responses have been separately documented, leaving open whether control processes in dishonest responding can flexibly adapt to transient and sustained conflict signals of dishonest and other actions. This was the goal of the present experiments which studied (dis)honest responding to autobiographical yes/no questions. Experiment 1 showed robust transient adaptation to recent dishonest responses whereas sustained control adaptation failed to exert an influence on behavior. It further revealed that transient effects may create a spurious impression of sustained adaptation in typical experimental settings. Experiments 2 and 3 examined whether dishonest responding can profit from transient and sustained adaption processes triggered by other behavioral conflicts. This was clearly not the case: Dishonest responding adapted markedly to recent (dis)honest responses but not to any context of other conflicts. These findings indicate that control adaptation in dishonest responding is strong but surprisingly focused and they point to a potential trade-off between transient and sustained adaptation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The adaptor molecule RIAM integrates signaling events critical for integrin-mediated control of immune function and cancer progression.

PubMed

Patsoukis, Nikolaos; Bardhan, Kankana; Weaver, Jessica D; Sari, Duygu; Torres-Gomez, Alvaro; Li, Lequn; Strauss, Laura; Lafuente, Esther M; Boussiotis, Vassiliki A

2017-08-22

Lymphocyte activation requires adhesion to antigen-presenting cells. This is a critical event linking innate and adaptive immunity. Lymphocyte adhesion is accomplished through LFA-1, which must be activated by a process referred to as inside-out integrin signaling. Among the few signaling molecules that have been implicated in inside-out integrin activation in hematopoietic cells are the small guanosine triphosphatase (GTPase) Rap1 and its downstream effector Rap1-interacting molecule (RIAM), a multidomain protein that defined the Mig10-RIAM-lamellipodin (MRL) class of adaptor molecules. Through its various domains, RIAM is a critical node of signal integration for activation of T cells, recruits monomeric and polymerized actin to drive actin remodeling and cytoskeletal reorganization, and promotes inside-out integrin signaling in T cells. As a regulator of inside-out integrin activation, RIAM affects multiple functions of innate and adaptive immunity. The effects of RIAM on cytoskeletal reorganization and integrin activation have implications in cell migration and trafficking of cancer cells. We provide an overview of the structure and interactions of RIAM, and we discuss the implications of RIAM functions in innate and adaptive immunity and cancer. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Frequency Domain Multiplexing for Use With NaI[Tl] Detectors

NASA Astrophysics Data System (ADS)

Belling, Samuel; Coherent Collaboration

2017-09-01

A process used in many forms of signal communication known as multiplexing is adapted for the purpose of combining signals from NaI[Tl] detectors so that fewer digitizer channels can be used to process the signal information from large experiments within the COHERENT collaboration. Each signal is passed through a ringing circuit to modulate it with a characteristic frequency. Information about the signal can be extracted from its amplitude, frequency, and phase. Simulations in LTSpice show that an operational amplifier circuit with a parallel LRC feedback loop can serve as the modulating circuit. Several such circuits can be constructed and housed compactly in a unit, and fed to an inverting, summing amplifier with tunable gain, such that the signals are carried by one cable. The signals are analyzed based on a Fourier transform after being digitized. The results show that the energy, channel, and time of the original interaction can be recovered by this process. In some cases it is possible through filtering and deconvolution to recover the shape of the original signal. The effort is ongoing, but with the design presented it is possible to multiplex 10 detectors into a single digitizer channel. NSF REU Program at Duke University.

Stimulus relevance modulates contrast adaptation in visual cortex

PubMed Central

Keller, Andreas J; Houlton, Rachael; Kampa, Björn M; Lesica, Nicholas A; Mrsic-Flogel, Thomas D; Keller, Georg B; Helmchen, Fritjof

2017-01-01

A general principle of sensory processing is that neurons adapt to sustained stimuli by reducing their response over time. Most of our knowledge on adaptation in single cells is based on experiments in anesthetized animals. How responses adapt in awake animals, when stimuli may be behaviorally relevant or not, remains unclear. Here we show that contrast adaptation in mouse primary visual cortex depends on the behavioral relevance of the stimulus. Cells that adapted to contrast under anesthesia maintained or even increased their activity in awake naïve mice. When engaged in a visually guided task, contrast adaptation re-occurred for stimuli that were irrelevant for solving the task. However, contrast adaptation was reversed when stimuli acquired behavioral relevance. Regulation of cortical adaptation by task demand may allow dynamic control of sensory-evoked signal flow in the neocortex. DOI: http://dx.doi.org/10.7554/eLife.21589.001 PMID:28130922

Online Denoising Based on the Second-Order Adaptive Statistics Model.

PubMed

Yi, Sheng-Lun; Jin, Xue-Bo; Su, Ting-Li; Tang, Zhen-Yun; Wang, Fa-Fa; Xiang, Na; Kong, Jian-Lei

2017-07-20

Online denoising is motivated by real-time applications in the industrial process, where the data must be utilizable soon after it is collected. Since the noise in practical process is usually colored, it is quite a challenge for denoising techniques. In this paper, a novel online denoising method was proposed to achieve the processing of the practical measurement data with colored noise, and the characteristics of the colored noise were considered in the dynamic model via an adaptive parameter. The proposed method consists of two parts within a closed loop: the first one is to estimate the system state based on the second-order adaptive statistics model and the other is to update the adaptive parameter in the model using the Yule-Walker algorithm. Specifically, the state estimation process was implemented via the Kalman filter in a recursive way, and the online purpose was therefore attained. Experimental data in a reinforced concrete structure test was used to verify the effectiveness of the proposed method. Results show the proposed method not only dealt with the signals with colored noise, but also achieved a tradeoff between efficiency and accuracy.

Overload-mediated skeletal muscle hypertrophy is not impaired by loss of myofiber STAT3.

PubMed

Pérez-Schindler, Joaquín; Esparza, Mary C; McKendry, James; Breen, Leigh; Philp, Andrew; Schenk, Simon

2017-09-01

Although the signal pathways mediating muscle protein synthesis and degradation are well characterized, the transcriptional processes modulating skeletal muscle mass and adaptive growth are poorly understood. Recently, studies in mouse models of muscle wasting or acutely exercised human muscle have suggested a potential role for the transcription factor signal transducer and activator of transcription 3 (STAT3), in adaptive growth. Hence, in the present study we sought to define the contribution of STAT3 to skeletal muscle adaptive growth. In contrast to previous work, two different resistance exercise protocols did not change STAT3 phosphorylation in human skeletal muscle. To directly address the role of STAT3 in load-induced (i.e., adaptive) growth, we studied the anabolic effects of 14 days of synergist ablation (SA) in skeletal muscle-specific STAT3 knockout (mKO) mice and their floxed, wild-type (WT) littermates. Plantaris muscle weight and fiber area in the nonoperated leg (control; CON) was comparable between genotypes. As expected, SA significantly increased plantaris weight, muscle fiber cross-sectional area, and anabolic signaling in WT mice, although interestingly, this induction was not impaired in STAT3 mKO mice. Collectively, these data demonstrate that STAT3 is not required for overload-mediated hypertrophy in mouse skeletal muscle. Copyright © 2017 the American Physiological Society.

Hydrogen Sulfide: A Signal Molecule in Plant Cross-Adaptation

PubMed Central

Li, Zhong-Guang; Min, Xiong; Zhou, Zhi-Hao

2016-01-01

For a long time, hydrogen sulfide (H2S) has been considered as merely a toxic by product of cell metabolism, but nowadays is emerging as a novel gaseous signal molecule, which participates in seed germination, plant growth and development, as well as the acquisition of stress tolerance including cross-adaptation in plants. Cross-adaptation, widely existing in nature, is the phenomenon in which plants expose to a moderate stress can induce the resistance to other stresses. The mechanism of cross-adaptation is involved in a complex signal network consisting of many second messengers such as Ca2+, abscisic acid, hydrogen peroxide and nitric oxide, as well as their crosstalk. The cross-adaptation signaling is commonly triggered by moderate environmental stress or exogenous application of signal molecules or their donors, which in turn induces cross-adaptation by enhancing antioxidant system activity, accumulating osmolytes, synthesizing heat shock proteins, as well as maintaining ion and nutrient balance. In this review, based on the current knowledge on H2S and cross-adaptation in plant biology, H2S homeostasis in plant cells under normal growth conditions; H2S signaling triggered by abiotic stress; and H2S-induced cross-adaptation to heavy metal, salt, drought, cold, heat, and flooding stress were summarized, and concluded that H2S might be a candidate signal molecule in plant cross-adaptation. In addition, future research direction also has been proposed. PMID:27833636

Motion-form interactions beyond the motion integration level: evidence for interactions between orientation and optic flow signals.

PubMed

Pavan, Andrea; Marotti, Rosilari Bellacosa; Mather, George

2013-05-31

Motion and form encoding are closely coupled in the visual system. A number of physiological studies have shown that neurons in the striate and extrastriate cortex (e.g., V1 and MT) are selective for motion direction parallel to their preferred orientation, but some neurons also respond to motion orthogonal to their preferred spatial orientation. Recent psychophysical research (Mather, Pavan, Bellacosa, & Casco, 2012) has demonstrated that the strength of adaptation to two fields of transparently moving dots is modulated by simultaneously presented orientation signals, suggesting that the interaction occurs at the level of motion integrating receptive fields in the extrastriate cortex. In the present psychophysical study, we investigated whether motion-form interactions take place at a higher level of neural processing where optic flow components are extracted. In Experiment 1, we measured the duration of the motion aftereffect (MAE) generated by contracting or expanding dot fields in the presence of either radial (parallel) or concentric (orthogonal) counterphase pedestal gratings. To tap the stage at which optic flow is extracted, we measured the duration of the phantom MAE (Weisstein, Maguire, & Berbaum, 1977) in which we adapted and tested different parts of the visual field, with orientation signals presented either in the adapting (Experiment 2) or nonadapting (Experiments 3 and 4) sectors. Overall, the results showed that motion adaptation is suppressed most by orientation signals orthogonal to optic flow direction, suggesting that motion-form interactions also take place at the global motion level where optic flow is extracted.

Signal Processing Applied to the Dolphin-Based Sonar System

DTIC Science & Technology

2003-09-01

4] H.L. Roitblat , P.W.B. Moore, D.A. Helweg and P.E. Nachtigall, “Representation and processing of acoustic information in a biomimetic neural...network,” in Animals to Animats 2: Simulation of Adaptive Behavior, J.-A. Meyer, H. L. Roitblat , and S. W. Wilson, Eds. MIT Press, pp.1-10, 1993. [5

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.

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sen, Satyabrata

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratiomore » (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.« less

Fast digital zooming system using directionally adaptive image interpolation and restoration.

PubMed

Kang, Wonseok; Jeon, Jaehwan; Yu, Soohwan; Paik, Joonki

2014-01-01

This paper presents a fast digital zooming system for mobile consumer cameras using directionally adaptive image interpolation and restoration methods. The proposed interpolation algorithm performs edge refinement along the initially estimated edge orientation using directionally steerable filters. Either the directionally weighted linear or adaptive cubic-spline interpolation filter is then selectively used according to the refined edge orientation for removing jagged artifacts in the slanted edge region. A novel image restoration algorithm is also presented for removing blurring artifacts caused by the linear or cubic-spline interpolation using the directionally adaptive truncated constrained least squares (TCLS) filter. Both proposed steerable filter-based interpolation and the TCLS-based restoration filters have a finite impulse response (FIR) structure for real time processing in an image signal processing (ISP) chain. Experimental results show that the proposed digital zooming system provides high-quality magnified images with FIR filter-based fast computational structure.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

PubMed

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-12-13

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

PubMed Central

Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

2016-01-01

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods. PMID:27983577

Campylobacter jejuni transducer like proteins: Chemotaxis and beyond

PubMed Central

Chandrashekhar, Kshipra; Kassem, Issmat I.; Rajashekara, Gireesh

2017-01-01

ABSTRACT Chemotaxis, a process that mediates directional motility toward or away from chemical stimuli (chemoeffectors/ligands that can be attractants or repellents) in the environment, plays an important role in the adaptation of Campylobacter jejuni to disparate niches. The chemotaxis system consists of core signal transduction proteins and methyl-accepting-domain-containing Transducer like proteins (Tlps). Ligands binding to Tlps relay a signal to chemotaxis proteins in the cytoplasm which initiate a signal transduction cascade, culminating into a directional flagellar movement. Tlps facilitate substrate-specific chemotaxis in C. jejuni, which plays an important role in the pathogen's adaptation, pathobiology and colonization of the chicken gastrointestinal tract. However, the role of Tlps in C. jejuni's host tissue specific colonization, physiology and virulence remains not completely understood. Based on recent studies, it can be predicted that Tlps might be important targets for developing strategies to control C. jejuni via vaccines and antimicrobials. PMID:28080213

Campylobacter jejuni transducer like proteins: Chemotaxis and beyond.

PubMed

Chandrashekhar, Kshipra; Kassem, Issmat I; Rajashekara, Gireesh

2017-07-04

Chemotaxis, a process that mediates directional motility toward or away from chemical stimuli (chemoeffectors/ligands that can be attractants or repellents) in the environment, plays an important role in the adaptation of Campylobacter jejuni to disparate niches. The chemotaxis system consists of core signal transduction proteins and methyl-accepting-domain-containing Transducer like proteins (Tlps). Ligands binding to Tlps relay a signal to chemotaxis proteins in the cytoplasm which initiate a signal transduction cascade, culminating into a directional flagellar movement. Tlps facilitate substrate-specific chemotaxis in C. jejuni, which plays an important role in the pathogen's adaptation, pathobiology and colonization of the chicken gastrointestinal tract. However, the role of Tlps in C. jejuni's host tissue specific colonization, physiology and virulence remains not completely understood. Based on recent studies, it can be predicted that Tlps might be important targets for developing strategies to control C. jejuni via vaccines and antimicrobials.

Redox signaling in skeletal muscle: role of aging and exercise.

PubMed

Ji, Li Li

2015-12-01

Skeletal muscle contraction is associated with the production of ROS due to altered O2 distribution and flux in the cell. Despite a highly efficient antioxidant defense, a small surplus of ROS, such as hydrogen peroxide and nitric oxide, may serve as signaling molecules to stimulate cellular adaptation to reach new homeostasis largely due to the activation of redox-sensitive signaling pathways. Recent research has highlighted the important role of NF-κB, MAPK, and peroxisome proliferator-activated receptor-γ coactivator-1α, along with other newly discovered signaling pathways, in some of the most vital biological functions, such as mitochondrial biogenesis, antioxidant defense, inflammation, protein turnover, apoptosis, and autophagy. There is evidence that the inability of the cell to maintain proper redox signaling underlies some basic mechanisms of biological aging, during which inflammatory and catabolic pathways eventually predominate. Physical exercise has been shown to activate various redox signaling pathways that control the adaptation and remodeling process. Although this stimulatory effect of exercise declines with aging, it is not completed abolished. Thus, aged people can still benefit from regular physical activity in the appropriate forms and at proper intensity to preserve muscle function. Copyright © 2015 The American Physiological Society.

Opinion: Interactions of innate and adaptive lymphocytes

PubMed Central

Gasteiger, Georg; Rudensky, Alexander Y.

2015-01-01

Innate lymphocytes, including natural killer (NK) cells and the recently discovered innate lymphoid cells (ILCs) have crucial roles during infection, tissue injury and inflammation. Innate signals regulate the activation and homeostasis of innate lymphocytes. Less well understood is the contribution of the adaptive immune system to the orchestration of innate lymphocyte responses. We review our current understanding of the interactions between adaptive and innate lymphocytes, and propose a model in which adaptive T cells function as antigen-specific sensors for the activation of innate lymphocytes to amplify and instruct local immune responses. We highlight the potential role of regulatory and helper T cells in these processes and discuss major questions in the emerging area of crosstalk between adaptive and innate lymphocytes. PMID:25132095

The influence of approach-avoidance motivational orientation on conflict adaptation.

PubMed

Hengstler, Maikel; Holland, Rob W; van Steenbergen, Henk; van Knippenberg, Ad

2014-06-01

To deal effectively with a continuously changing environment, our cognitive system adaptively regulates resource allocation. Earlier findings showed that an avoidance orientation (induced by arm extension), relative to an approach orientation (induced by arm flexion), enhanced sustained cognitive control. In avoidance conditions, performance on a cognitive control task was enhanced, as indicated by a reduced congruency effect, relative to approach conditions. Extending these findings, in the present behavioral studies we investigated dynamic adaptations in cognitive control-that is, conflict adaptation. We proposed that an avoidance state recruits more resources in response to conflicting signals, and thereby increases conflict adaptation. Conversely, in an approach state, conflict processing diminishes, which consequently weakens conflict adaptation. As predicted, approach versus avoidance arm movements affected both behavioral congruency effects and conflict adaptation: As compared to approach, avoidance movements elicited reduced congruency effects and increased conflict adaptation. These results are discussed in line with a possible underlying neuropsychological model.

Inertia-Wheel Vibration-Damping System

NASA Technical Reports Server (NTRS)

Fedor, Joseph V.

1990-01-01

Proposed electromechanical system would damp vibrations in large, flexible structure. In active vibration-damping system motors and reaction wheels at tips of appendages apply reaction torques in response to signals from accelerometers. Velocity signal for vibrations about one axis processes into control signal to oppose each of n vibrational modes. Various modes suppressed one at a time. Intended primarily for use in spacecraft that has large, flexible solar panels and science-instrument truss assembly, embodies principle of control interesting in its own right and adaptable to terrestrial structures, vehicles, and instrument platforms.

The osteocyte: key player in regulating bone turnover

PubMed Central

Goldring, Steven R

2015-01-01

Osteocytes are the most abundant cell type in bone and are distributed throughout the mineralised bone matrix forming an interconnected network that ideally positions them to sense and to respond to local biomechanical and systemic stimuli to regulate bone remodelling and adaptation. The adaptive process is dependent on the coordinated activity of osteoclasts and osteoblasts that form a so called bone multicellular unit that remodels cortical and trabecular bone through a process of osteoclast-mediated bone resorption, followed by a phase of bone formation mediated by osteoblasts. Osteocytes mediate their effects on bone remodelling via both cell–cell interactions with osteoclasts and osteoblasts, but also via signaling through the release of soluble mediators. The remodelling process provides a mechanism for adapting the skeleton to local biomechanical factors and systemic hormonal influences and for replacing bone that has undergone damage from repetitive mechanical loading. PMID:26557372

Do antioxidant supplements interfere with skeletal muscle adaptation to exercise training?

PubMed Central

Ristow, Michael

2016-01-01

Abstract A popular belief is that reactive oxygen species (ROS) and reactive nitrogen species (RNS) produced during exercise by the mitochondria and other subcellular compartments ubiquitously cause skeletal muscle damage, fatigue and impair recovery. However, the importance of ROS and RNS as signals in the cellular adaptation process to stress is now evident. In an effort to combat the perceived deleterious effects of ROS and RNS it has become common practice for active individuals to ingest supplements with antioxidant properties, but interfering with ROS/RNS signalling in skeletal muscle during acute exercise may blunt favourable adaptation. There is building evidence that antioxidant supplementation can attenuate endurance training‐induced and ROS/RNS‐mediated enhancements in antioxidant capacity, mitochondrial biogenesis, cellular defence mechanisms and insulin sensitivity. However, this is not a universal finding, potentially indicating that there is redundancy in the mechanisms controlling skeletal muscle adaptation to exercise, meaning that in some circumstances the negative impact of antioxidants on acute exercise response can be overcome by training. Antioxidant supplementation has been more consistently reported to have deleterious effects on the response to overload stress and high‐intensity training, suggesting that remodelling of skeletal muscle following resistance and high‐intensity exercise is more dependent on ROS/RNS signalling. Importantly there is no convincing evidence to suggest that antioxidant supplementation enhances exercise‐training adaptions. Overall, ROS/RNS are likely to exhibit a non‐linear (hormetic) pattern on exercise adaptations, where physiological doses are beneficial and high exposure (which would seldom be achieved during normal exercise training) may be detrimental. PMID:26638792

Conflict adaptation in prefrontal cortex: now you see it, now you don't.

PubMed

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2014-01-01

Daily life requires people to monitor and resolve conflict arising from distracting information irrelevant to current goals. The highly influential conflict monitoring theory (CMT) holds that the anterior cingulate cortex (ACC) detects conflict and subsequently triggers the dorsolateral prefrontal cortex (DLPFC) to regulate that conflict. Multiple lines of evidence have provided support for CMT. For example, performance is faster on incongruent trials that follow other incongruent trials (iI), and is accompanied by reduced ACC and increased DLPFC activation (the conflict adaptation effect). In this fMRI study, we explored whether ACC-DLPFC conflict signaling can result in behavioral adjustments beyond on-line contexts. Participants completed a modified version of the Stroop conflict adaptation paradigm which tested for conflict adaptation effects on the current (N) trial associated with not only the immediately preceding (N - 1) trial, but also 2-back (N - 2) trials. Results demonstrated evidence for direct relationships between ACC activity on N - 2 trials and both N trial DLPFC activity and behavioral adjustment when intervening trials were congruent (i.e., icI). In contrast, when N - 1 trials were incongruent (i.e., iiI), ACC-DLPFC signaling failed and conflict adaptation was absent. These results provide new evidence demonstrating that the conflict monitor-controller maintains previously experienced conflict in the service of subsequent behavioral adjustment. However, the processing of multiple, temporally proximal conflict signals takes a toll on the working memory (WM) system, which appears to require resetting in order to adapt our behavior to frequently changing environmental demands. Copyright © 2013 Elsevier Ltd. All rights reserved.

Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients †

PubMed Central

Fidan, Barış; Umay, Ilknur

2015-01-01

Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. PMID:26690441

Calcium Signals: The Lead Currency of Plant Information Processing

PubMed Central

Kudla, Jörg; Batistič, Oliver; Hashimoto, Kenji

2010-01-01

Ca2+ signals are core transducers and regulators in many adaptation and developmental processes of plants. Ca2+ signals are represented by stimulus-specific signatures that result from the concerted action of channels, pumps, and carriers that shape temporally and spatially defined Ca2+ elevations. Cellular Ca2+ signals are decoded and transmitted by a toolkit of Ca2+ binding proteins that relay this information into downstream responses. Major transduction routes of Ca2+ signaling involve Ca2+-regulated kinases mediating phosphorylation events that orchestrate downstream responses or comprise regulation of gene expression via Ca2+-regulated transcription factors and Ca2+-responsive promoter elements. Here, we review some of the remarkable progress that has been made in recent years, especially in identifying critical components functioning in Ca2+ signal transduction, both at the single-cell and multicellular level. Despite impressive progress in our understanding of the processing of Ca2+ signals during the past years, the elucidation of the exact mechanistic principles that underlie the specific recognition and conversion of the cellular Ca2+ currency into defined changes in protein–protein interaction, protein phosphorylation, and gene expression and thereby establish the specificity in stimulus response coupling remain to be explored. PMID:20354197

Processing oscillatory signals by incoherent feedforward loops

NASA Astrophysics Data System (ADS)

Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

Processing Oscillatory Signals by Incoherent Feedforward Loops

PubMed Central

Zhang, Carolyn; You, Lingchong

2016-01-01

From the timing of amoeba development to the maintenance of stem cell pluripotency, many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression. While the networks underlying this signal decoding are diverse, many are built around a common motif, the incoherent feedforward loop (IFFL), where an input simultaneously activates an output and an inhibitor of the output. With appropriate parameters, this motif can exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input signals with varying temporal profiles. Here, we use quantitative modeling to examine another property of IFFLs—the ability to process oscillatory signals. Our results indicate that the system’s ability to translate pulsatile dynamics is limited by two constraints. The kinetics of the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal “counting”. We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. PMID:27623175

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex.

PubMed

McLelland, Douglas; Baker, Pamela M; Ahmed, Bashir; Kohn, Adam; Bair, Wyeth

2015-07-15

A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components. Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales. Copyright © 2015 the authors 0270-6474/15/3510268-13$15.00/0.

Multi-channel time-reversal receivers for multi and 1-bit implementations

DOEpatents

Candy, James V.; Chambers, David H.; Guidry, Brian L.; Poggio, Andrew J.; Robbins, Christopher L.

2008-12-09

A communication system for transmitting a signal through a channel medium comprising digitizing the signal, time-reversing the digitized signal, and transmitting the signal through the channel medium. In one embodiment a transmitter is adapted to transmit the signal, a multiplicity of receivers are adapted to receive the signal, a digitizer digitizes the signal, and a time-reversal signal processor is adapted to time-reverse the digitized signal. An embodiment of the present invention includes multi bit implementations. Another embodiment of the present invention includes 1-bit implementations. Another embodiment of the present invention includes a multiplicity of receivers used in the step of transmitting the signal through the channel medium.

Extracellular signal-regulated protein kinases 1 and 2 activation by addictive drugs: a signal toward pathological adaptation.

PubMed

Pascoli, Vincent; Cahill, Emma; Bellivier, Frank; Caboche, Jocelyne; Vanhoutte, Peter

2014-12-15

Addiction is a chronic and relapsing psychiatric disorder that is thought to occur in vulnerable individuals. Synaptic plasticity evoked by drugs of abuse in the so-called neuronal circuits of reward has been proposed to underlie behavioral adaptations that characterize addiction. By increasing dopamine in the striatum, addictive drugs alter the balance of dopamine and glutamate signals converging onto striatal medium-sized spiny neurons (MSNs) and activate intracellular events involved in long-term behavioral alterations. Our laboratory contributed to the identification of salient molecular changes induced by administration of addictive drugs to rodents. We pioneered the observation that a common feature of addictive drugs is to activate, by a double tyrosine/threonine phosphorylation, the extracellular signal-regulated kinases 1 and 2 (ERK1/2) in the striatum, which control a plethora of substrates, some of them being critically involved in cocaine-mediated molecular and behavioral adaptations. Herein, we review how the interplay between dopamine and glutamate signaling controls cocaine-induced ERK1/2 activation in MSNs. We emphasize the key role of N-methyl-D-aspartate receptor potentiation by D1 receptor to trigger ERK1/2 activation and its subsequent nuclear translocation where it modulates both epigenetic and genetic processes engaged by cocaine. We discuss how cocaine-induced long-term synaptic and structural plasticity of MSNs, as well as behavioral adaptations, are influenced by ERK1/2-controlled targets. We conclude that a better knowledge of molecular mechanisms underlying ERK1/2 activation by drugs of abuse and/or its role in long-term neuronal plasticity in the striatum may provide a new route for therapeutic treatment in addiction. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Novel multireceiver communication systems configurations based on optimal estimation theory

NASA Technical Reports Server (NTRS)

Kumar, Rajendra

1992-01-01

A novel multireceiver configuration for carrier arraying and/or signal arraying is presented. The proposed configuration is obtained by formulating the carrier and/or signal arraying problem as an optimal estimation problem, and it consists of two stages. The first stage optimally estimates various phase processes received at different receivers with coupled phase-locked loops wherein the individual loops acquire and track their respective receivers' phase processes but are aided by each other in an optimal manner via LF error signals. The proposed configuration results in the minimization of the the effective radio loss at the combiner output, and thus maximization of energy per bit to noise power spectral density ratio is achieved. A novel adaptive algorithm for the estimator of the signal model parameters when these are not known a priori is also presented.

Registration of surface structures using airborne focused ultrasound.

PubMed

Sundström, N; Börjesson, P O; Holmer, N G; Olsson, L; Persson, H W

1991-01-01

A low-cost measuring system, based on a personal computer combined with standard equipment for complex measurements and signal processing, has been assembled. Such a system increases the possibilities for small hospitals and clinics to finance advanced measuring equipment. A description of equipment developed for airborne ultrasound together with a personal computer-based system for fast data acquisition and processing is given. Two air-adapted ultrasound transducers with high lateral resolution have been developed. Furthermore, a few results for fast and accurate estimation of signal arrival time are presented. The theoretical estimation models developed are applied to skin surface profile registrations.

Bacterial Serine/Threonine Protein Kinases in Host-Pathogen Interactions*

PubMed Central

Canova, Marc J.; Molle, Virginie

2014-01-01

In bacterial pathogenesis, monitoring and adapting to the dynamically changing environment in the host and an ability to disrupt host immune responses are critical. The virulence determinants of pathogenic bacteria include the sensor/signaling proteins of the serine/threonine protein kinase (STPK) family that have a dual role of sensing the environment and subverting specific host defense processes. STPKs can sense a wide range of signals and coordinate multiple cellular processes to mount an appropriate response. Here, we review some of the well studied bacterial STPKs that are essential virulence factors and that modify global host responses during infection. PMID:24554701

Bacterial serine/threonine protein kinases in host-pathogen interactions.

PubMed

Canova, Marc J; Molle, Virginie

2014-04-04

In bacterial pathogenesis, monitoring and adapting to the dynamically changing environment in the host and an ability to disrupt host immune responses are critical. The virulence determinants of pathogenic bacteria include the sensor/signaling proteins of the serine/threonine protein kinase (STPK) family that have a dual role of sensing the environment and subverting specific host defense processes. STPKs can sense a wide range of signals and coordinate multiple cellular processes to mount an appropriate response. Here, we review some of the well studied bacterial STPKs that are essential virulence factors and that modify global host responses during infection.

Effects of masker frequency and duration in forward masking: further evidence for the influence of peripheral nonlinearity.

PubMed

Oxenham, A J; Plack, C J

2000-12-01

Forward masking has often been thought of in terms of neural adaptation, with nonlinearities in the growth and decay of forward masking being accounted for by the nonlinearities inherent in adaptation. In contrast, this study presents further evidence for the hypothesis that forward masking can be described as a linear process, once peripheral, mechanical nonlinearities are taken into account. The first experiment compares the growth of masking for on- and off-frequency maskers. Signal thresholds were measured as a function of masker level for three masker-signal intervals of 0, 10, and 30 ms. The brief 4-kHz sinusoidal signal was masked by a 200-ms sinusoidal forward masker which had a frequency of either 2.4 kHz (off-frequency) or 4 kHz (on-frequency). As in previous studies, for the on-frequency condition, the slope of the function relating signal threshold to masker level became shallower as the delay between the masker and signal was increased. In contrast, the slopes for the off-frequency condition were independent of masker-signal delay and had a value of around unity, indicating linear growth of masking for all masker-signal delays. In the second experiment, a broadband Gaussian noise forward masker was used to mask a brief 6-kHz sinusoidal signal. The spectrum level of the masker was either 0 or 40 dB (re: 20 microPa). The gap between the masker and signal was either 0 or 20 ms. Signal thresholds were measured for masker durations from 5 to 200 ms. The effect of masker duration was found to depend more on signal level than on gap duration or masker level. Overall, the results support the idea that forward masking can be modeled as a linear process, preceded by a static nonlinearity resembling that found on the basilar membrane.

Potentiation in the first visual synapse of the fly compound eye.

PubMed

Uusitalo, R O; Weckström, M

2000-04-01

In the first visual synapse of the insect compound eye, both the presynaptic and postsynaptic signals are graded, nonspiking changes in membrane voltage. The synapse exhibits tonic transmitter release (even in dark) and strong adaptation to long-lasting light backgrounds, leading to changes also in the dynamics of signal transmission. We have studied these adaptational properties of the first visual synapse of the blowfly Calliphora vicina. Investigations were done in situ by intracellular recordings from the presynaptic photoreceptors, photoreceptor axon terminals, and the postsynaptic first order visual interneurons (LMCs). The dark recovery, the shifts in intensity dependence, and the underlying processes were studied by stimulating the visual system with various adapting stimuli while observing the recovery (i.e., dark adaptation). The findings show a transient potentiation in the postsynaptic responses after intense light adaptation, and the underlying mechanisms seem to be the changes in the equilibrium potential of the transmitter-gated conductance (chloride) of the postsynaptic neurons. The potentiation by itself serves as a mechanism that after light adaptation rapidly recovers the sensitivity loss of the visual system. However, this kind of mechanism, being an intrinsic property of graded potential transmission, may be quite widespread among graded synapses, and the phenomenon demonstrates that functional plasticity is also a property of graded synaptic transmission.

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Ramanujan sums for signal processing of low-frequency noise.

PubMed

Planat, Michel; Rosu, Haret; Perrine, Serge

2002-11-01

An aperiodic (low-frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as Möbius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low-frequency regime. In place we introduce a different signal processing tool based on the Ramanujan sums c(q)(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasiperiodic versus the time n and aperiodic versus the order q of the resonance. Different results arise from the use of this Ramanujan-Fourier transform in the context of arithmetical and experimental signals.

Ramanujan sums for signal processing of low-frequency noise

NASA Astrophysics Data System (ADS)

Planat, Michel; Rosu, Haret; Perrine, Serge

2002-11-01

An aperiodic (low-frequency) spectrum may originate from the error term in the mean value of an arithmetical function such as Möbius function or Mangoldt function, which are coding sequences for prime numbers. In the discrete Fourier transform the analyzing wave is periodic and not well suited to represent the low-frequency regime. In place we introduce a different signal processing tool based on the Ramanujan sums cq(n), well adapted to the analysis of arithmetical sequences with many resonances p/q. The sums are quasiperiodic versus the time n and aperiodic versus the order q of the resonance. Different results arise from the use of this Ramanujan-Fourier transform in the context of arithmetical and experimental signals.

Relative Wave Energy based Adaptive Neuro-Fuzzy Inference System model for the Estimation of Depth of Anaesthesia.

PubMed

Benzy, V K; Jasmin, E A; Koshy, Rachel Cherian; Amal, Frank; Indiradevi, K P

2018-01-01

The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent modeling techniques. The neurophysiological signal that reflects cognitive state of anaesthetic drugs is the electroencephalogram signal. The information available on electroencephalogram signals during anaesthesia are drawn by extracting relative wave energy features from the anaesthetic electroencephalogram signals. Discrete wavelet transform is used to decomposes the electroencephalogram signals into four levels and then relative wave energy is computed from approximate and detail coefficients of sub-band signals. Relative wave energy is extracted to find out the degree of importance of different electroencephalogram frequency bands associated with different anaesthetic phases awake, induction, maintenance and recovery. The Kruskal-Wallis statistical test is applied on the relative wave energy features to check the discriminating capability of relative wave energy features as awake, light anaesthesia, moderate anaesthesia and deep anaesthesia. A novel depth of anaesthesia index is generated by implementing a Adaptive neuro-fuzzy inference system based fuzzy c-means clustering algorithm which uses relative wave energy features as inputs. Finally, the generated depth of anaesthesia index is compared with a commercially available depth of anaesthesia monitor Bispectral index.

Mode-field adapter for tapered-fiber-bundle signal and pump combiners.

PubMed

Koška, Pavel; Baravets, Yauhen; Peterka, Pavel; Bohata, Jan; Písařík, Michael

2015-02-01

We report on a novel mode-field adapter that is proposed to be incorporated inside tapered fused-fiber-bundle pump and signal combiners for high-power double-clad fiber lasers. Such an adapter allows optimization of signal-mode-field matching on the input and output fibers. Correspondingly, losses of the combiner signal branch are significantly reduced. The mode-field adapter optimization procedure is demonstrated on a combiner based on commercially available fibers. Signal wavelengths of 1.55 and 2 μm are considered. The losses can be further improved by using specially designed intermediate fiber and by dopant diffusion during splicing as confirmed by preliminary experimental results.

NeuroPigPen: A Scalable Toolkit for Processing Electrophysiological Signal Data in Neuroscience Applications Using Apache Pig.

PubMed

Sahoo, Satya S; Wei, Annan; Valdez, Joshua; Wang, Li; Zonjy, Bilal; Tatsuoka, Curtis; Loparo, Kenneth A; Lhatoo, Samden D

2016-01-01

The recent advances in neurological imaging and sensing technologies have led to rapid increase in the volume, rate of data generation, and variety of neuroscience data. This "neuroscience Big data" represents a significant opportunity for the biomedical research community to design experiments using data with greater timescale, large number of attributes, and statistically significant data size. The results from these new data-driven research techniques can advance our understanding of complex neurological disorders, help model long-term effects of brain injuries, and provide new insights into dynamics of brain networks. However, many existing neuroinformatics data processing and analysis tools were not built to manage large volume of data, which makes it difficult for researchers to effectively leverage this available data to advance their research. We introduce a new toolkit called NeuroPigPen that was developed using Apache Hadoop and Pig data flow language to address the challenges posed by large-scale electrophysiological signal data. NeuroPigPen is a modular toolkit that can process large volumes of electrophysiological signal data, such as Electroencephalogram (EEG), Electrocardiogram (ECG), and blood oxygen levels (SpO2), using a new distributed storage model called Cloudwave Signal Format (CSF) that supports easy partitioning and storage of signal data on commodity hardware. NeuroPigPen was developed with three design principles: (a) Scalability-the ability to efficiently process increasing volumes of data; (b) Adaptability-the toolkit can be deployed across different computing configurations; and (c) Ease of programming-the toolkit can be easily used to compose multi-step data processing pipelines using high-level programming constructs. The NeuroPigPen toolkit was evaluated using 750 GB of electrophysiological signal data over a variety of Hadoop cluster configurations ranging from 3 to 30 Data nodes. The evaluation results demonstrate that the toolkit is highly scalable and adaptable, which makes it suitable for use in neuroscience applications as a scalable data processing toolkit. As part of the ongoing extension of NeuroPigPen, we are developing new modules to support statistical functions to analyze signal data for brain connectivity research. In addition, the toolkit is being extended to allow integration with scientific workflow systems. NeuroPigPen is released under BSD license at: https://sites.google.com/a/case.edu/neuropigpen/.

Adaptable Transponder for Multiple Telemetry Systems

NASA Technical Reports Server (NTRS)

Sims, William Herbert, III (Inventor); Varnavas, Kosta A. (Inventor)

2014-01-01

The present invention is a stackable telemetry circuit board for use in telemetry systems for satellites and other purposes. The present invention incorporates previously-qualified interchangeable circuit boards, or "decks," that perform functions such as power, signal receiving and transmission, and processing. Each deck is adapted to serve a range of telemetry applications. This provides flexibility in the construction of the stackable telemetry circuit board and significantly reduces the cost and time necessary to develop a telemetry system.

Space-Time Adaptive Processing for Airborne Radar

DTIC Science & Technology

1994-12-13

horizontal plane Uniform linear antenna array (possibly columns of a planar array) Identical element patterns 13 14 15 9 7 7,33 7 7 Target Model ...Parameters for Example Scenario 31 3 Assumptions Made for Radar System and Signal Model 52 4 Platform and Interference Scenario for Baseline Scenario. 61 5...pulses, is addressed first. Fully adaptive STAP requires the solution to a system of linear equations of size MN, where N is the number of array

Comparing Binaural Pre-processing Strategies II: Speech Intelligibility of Bilateral Cochlear Implant Users.

PubMed

Baumgärtel, Regina M; Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-12-30

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. © The Author(s) 2015.

Comparing Binaural Pre-processing Strategies II

PubMed Central

Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-01-01

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. PMID:26721921

Adverse Outcome Pathway (AOP) framework for embryonic vascular disruption and developmental defects (SOT)

EPA Science Inventory

Vascular development commences with de novo assembly of a primary capillary plexus (vasculogenesis) followed by its expansion (angiogenesis) and maturation (angio-adaptation) into a hierarchical system of arteries and veins. These processes are tightly regulated by genetic signal...

Sparse time-frequency decomposition based on dictionary adaptation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. © 2016 The Author(s).

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 effectiveness of the system on the 140 ft telescope at Green Bank Observatory.

Corruption of coronary collateral growth in metabolic syndrome: Role of oxidative stress

PubMed Central

Pung, Yuh Fen; Chilian, William M

2010-01-01

The myocardium adapts to ischemic insults in a variety of ways. One adaptation is the phenomenon of acute preconditioning, which can greatly ameliorate ischemic damage. However, this effect wanes within a few hours and does not confer chronic protection. A more chronic adaptation is the so-called second window of preconditioning, which enables protection for a few days. The most potent adaptation invoked by the myocardium to minimize the effects of ischemia is the growth of blood vessels in the heart, angiogenesis and arteriogenesis (collateral growth), which prevent the development of ischemia by enabling flow to a jeopardized region of the heart. This brief review examines the mechanisms underlying angiogenesis and arteriogenesis in the heart. The concept of a redox window, which is an optimal redox state for vascular growth, is discussed along with signaling mechanisms invoked by reactive oxygen species that are stimulated during ischemia-reperfusion. Finally, the review discusses of some of the pathologies, especially the metabolic syndrome, that negatively affect collateral growth through the corruption of redox signaling processes. PMID:21191543

Inactivation of Semicircular Canals Causes Adaptive Increases in Otolith-driven Tilt Responses

NASA Technical Reports Server (NTRS)

Angelaki, Dora E.; Newlands, Shawn D.; Dickman, J. David

2002-01-01

Growing experimental and theoretical evidence suggests a functional synergy in the processing of otolith and semicircular canal signals for the generation of the vestibulo-ocular reflexes (VORs). In this study we have further tested this functional interaction by quantifying the adaptive changes in the otolith-ocular system during both rotational and translational movements after surgical inactivation of the semicircular canals. For 0.1- 0.5 Hz (stimuli for which there is no recovery of responses from the plugged canals), pitch and roll VOR gains recovered during earth- horizontal (but not earth-vertical) axis rotations. Corresponding changes were also observed in eye movements elicited by translational motion (0.1 - 5 Hz). Specifically, torsional eye movements increased during lateral motion, whereas vertical eye movements increased during fore-aft motion. The findings indicate that otolith signals can be adapted according to compromised strategy that leads to improved gaze stabilization during motion. Because canal-plugged animals permanently lose the ability to discriminate gravitoinertial accelerations, adapted animals can use the presence of gravity through otolith-driven tilt responses to assist gaze stabilization during earth-horizontal axis rotations.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient formore » the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.« less

Adaptive Signal Timing Comparison Between the InSync and QuicTrac Adaptive Signal Systems Installed in Colorado

DOT National Transportation Integrated Search

2012-07-01

The FHWAs Every Day Counts (EDC) initiative identifies adaptive signal control as a tool for local agencies to deploy : innovation. In an effort to achieve the goals of the EDC initiative, the traffic sections of the Colorado Department of : Trans...

Future Technology Themes: 2030 to 2060

DTIC Science & Technology

2013-07-01

Rocket-Based Combined Cycle RF Radio Frequency RNA Ribonucleic Acid SA Situational Awareness SEAD Suppression of Enemy Air Defences SME...and re-routing light in information processing and optical communications ; or for processing radio signals in mobile phones [44]. UNCLASSIFIED DSTO...make use of network polymorphism technologies from 2020 onwards to create frequency -agile and adaptive14 communications links that would change network

Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation, Amplification, and Co-attraction in Collective Guidance

PubMed Central

Camley, Brian A.; Zimmermann, Juliane; Levine, Herbert; Rappel, Wouter-Jan

2016-01-01

Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of “collective guidance” computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the cluster’s size—clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals; both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion. PMID:27367541

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Otolith-Canal Convergence in Vestibular Nuclei Neurons

NASA Technical Reports Server (NTRS)

Dickman, J. David

1996-01-01

During manned spaceflight, acute vestibular disturbances often occur, leading to physical duress and a loss of performance. Vestibular adaptation to the weightless environment follows within two to three days yet the mechanisms responsible for the disturbance and subsequent adaptation are still unknown In order to understand vestibular system function in space and normal earth conditions the basic physiological mechanisms of vestibular information co coding must be determined. Information processing regarding head movement and head position with respect to gravity takes place in the vestibular nuclei neurons that receive signals From the semicircular canals and otolith organs in the vestibular labyrinth. These neurons must synthesize the information into a coded output signal that provides for the head and eye movement reflexes as well as the conscious perception of the body in three-dimensional space The current investigation will for the first time. determine how the vestibular nuclei neurons quantitatively synthesize afferent information from the different linear and angular acceleration receptors in the vestibular labyrinths into an integrated output signal. During the second year of funding, progress on the current project has been focused on the anatomical orientation of semicircular canals and the spatial orientation of the innervating afferent responses. This information is necessary in order to understand how vestibular nuclei neurons process the incoming afferent spatial signals particularly with the convergent otolith afferent signals that are also spatially distributed Since information from the vestibular nuclei is presented to different brain regions associated with differing reflexive and sensory functions it is important to understand the computational mechanisms used by vestibular neurons to produce the appropriate output signal.

Population resequencing reveals candidate genes associated with salinity adaptation of the Pacific oyster Crassostrea gigas.

PubMed

She, Zhicai; Li, Li; Meng, Jie; Jia, Zhen; Que, Huayong; Zhang, Guofan

2018-06-06

The Pacific oyster Crassostrea gigas is an important cultivated shellfish. As a euryhaline species, it has evolved adaptive mechanisms responding to the complex and changeable intertidal environment that it inhabits. To investigate the genetic basis of this salinity adaptation mechanism, we conducted a genome-wide association study using phenotypically differentiated populations (hyposalinity and hypersalinity adaptation populations, and control population), and confirmed our results using an independent population, high-resolution melting, and mRNA expression analysis. For the hyposalinity adaptation, we determined 24 genes, including Cg_CLCN7 (chloride channel protein 7) and Cg_AP1 (apoptosis 1 inhibitor), involved in the ion/water channel and transporter mechanisms, free amino acid and reactive oxygen species metabolism, immune responses, and chemical defence. Three SNPs located on these two genes were significantly differentiated between groups, as was Cg_CLCN7. For the hypersalinity adaptation, the biological process for positive regulating the developmental process was enriched. Enriched gene functions were focused on transcriptional regulation, signal transduction, and cell growth and differentiation, including calmodulin (Cg_CaM) and ficolin-2 (Cg_FCN2). These genes and polymorphisms possibly play an important role in oyster hyposalinity and hypersalinity adaptation. They not only further our understanding of salinity adaptation mechanisms but also provide markers for highly adaptable oyster strains suitable for breeding.

Performance optimization of PM-16QAM transmission system enabled by real-time self-adaptive coding.

PubMed

Qu, Zhen; Li, Yao; Mo, Weiyang; Yang, Mingwei; Zhu, Shengxiang; Kilper, Daniel C; Djordjevic, Ivan B

2017-10-15

We experimentally demonstrate self-adaptive coded 5×100  Gb/s WDM polarization multiplexed 16 quadrature amplitude modulation transmission over a 100 km fiber link, which is enabled by a real-time control plane. The real-time optical signal-to-noise ratio (OSNR) is measured using an optical performance monitoring device. The OSNR measurement is processed and fed back using control plane logic and messaging to the transmitter side for code adaptation, where the binary data are adaptively encoded with three types of low-density parity-check (LDPC) codes with code rates of 0.8, 0.75, and 0.7 of large girth. The total code-adaptation latency is measured to be 2273 ms. Compared with transmission without adaptation, average net capacity improvements of 102%, 36%, and 7.5% are obtained, respectively, by adaptive LDPC coding.

Exercise-Induced Skeletal Muscle Remodeling and Metabolic Adaptation: Redox Signaling and Role of Autophagy

PubMed Central

Giammarioli, Anna Maria; Chiandotto, Sergio; Spoletini, Ilaria

2014-01-01

Abstract Significance: Skeletal muscle is a highly plastic tissue. Exercise evokes signaling pathways that strongly modify myofiber metabolism and physiological and contractile properties of skeletal muscle. Regular physical activity is beneficial for health and is highly recommended for the prevention of several chronic conditions. In this review, we have focused our attention on the pathways that are known to mediate physical training-induced plasticity. Recent Advances: An important role for redox signaling has recently been proposed in exercise-mediated muscle remodeling and peroxisome proliferator-activated receptor γ (PPARγ) coactivator-1α (PGC-1α) activation. Still more currently, autophagy has also been found to be involved in metabolic adaptation to exercise. Critical Issues: Both redox signaling and autophagy are processes with ambivalent effects; they can be detrimental and beneficial, depending on their delicate balance. As such, understanding their role in the chain of events induced by exercise and leading to skeletal muscle remodeling is a very complicated matter. Moreover, the study of the signaling induced by exercise is made even more difficult by the fact that exercise can be performed with several different modalities, with this having different repercussions on adaptation. Future Directions: Unraveling the complexity of the molecular signaling triggered by exercise on skeletal muscle is crucial in order to define the therapeutic potentiality of physical training and to identify new pharmacological compounds that are able to reproduce some beneficial effects of exercise. In evaluating the effect of new “exercise mimetics,” it will also be necessary to take into account the involvement of reactive oxygen species, reactive nitrogen species, and autophagy and their controversial effects. Antioxid. Redox Signal. 21, 154–176. PMID:24450966

Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses

PubMed Central

Baddeley, Michelle; Tobler, Philippe N.; Schultz, Wolfram

2016-01-01

Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment. SIGNIFICANCE STATEMENT Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result in loss of precise representation (e.g., when the avoidance of a loss in a loss-context is coded the same as receipt of a gain in a gain-context). We investigated an intermediate form of adaptation that is efficient while maintaining information about received gains and avoided losses. We found that frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Importantly, adaptation was intermediate, in line with influential models of reference dependence in behavioral economics. PMID:27683899

Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.

PubMed

Conzelmann, Holger; Gilles, Ernst-Dieter

2008-01-01

Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.

Odorant-Dependent Generation of Nitric Oxide in Mammalian Olfactory Sensory Neurons

PubMed Central

Brunert, Daniela; Kurtenbach, Stefan; Isik, Sonnur; Benecke, Heike; Gisselmann, Günter; Schuhmann, Wolfgang; Hatt, Hanns; Wetzel, Christian H.

2009-01-01

The gaseous signalling molecule nitric oxide (NO) is involved in various physiological processes including regulation of blood pressure, immunocytotoxicity and neurotransmission. In the mammalian olfactory bulb (OB), NO plays a role in the formation of olfactory memory evoked by pheromones as well as conventional odorants. While NO generated by the neuronal isoform of NO synthase (nNOS) regulates neurogenesis in the olfactory epithelium, NO has not been implicated in olfactory signal transduction. We now show the expression and function of the endothelial isoform of NO synthase (eNOS) in mature olfactory sensory neurons (OSNs) of adult mice. Using NO-sensitive micro electrodes, we show that stimulation liberates NO from isolated wild-type OSNs, but not from OSNs of eNOS deficient mice. Integrated electrophysiological recordings (electro-olfactograms or EOGs) from the olfactory epithelium of these mice show that NO plays a significant role in modulating adaptation. Evidence for the presence of eNOS in mature mammalian OSNs and its involvement in odorant adaptation implicates NO as an important new element involved in olfactory signal transduction. As a diffusible messenger, NO could also have additional functions related to cross adaptation, regeneration, and maintenance of MOE homeostasis. PMID:19430528

Research to Operations of Ionospheric Scintillation Detection and Forecasting

NASA Astrophysics Data System (ADS)

Jones, J.; Scro, K.; Payne, D.; Ruhge, R.; Erickson, B.; Andorka, S.; Ludwig, C.; Karmann, J.; Ebelhar, D.

Ionospheric Scintillation refers to random fluctuations in phase and amplitude of electromagnetic waves caused by a rapidly varying refractive index due to turbulent features in the ionosphere. Scintillation of transionospheric UHF and L-Band radio frequency signals is particularly troublesome since this phenomenon can lead to degradation of signal strength and integrity that can negatively impact satellite communications and navigation, radar, or radio signals from other systems that traverse or interact with the ionosphere. Although ionospheric scintillation occurs in both the equatorial and polar regions of the Earth, the focus of this modeling effort is on equatorial scintillation. The ionospheric scintillation model is data-driven in a sense that scintillation observations are used to perform detection and characterization of scintillation structures. These structures are then propagated to future times using drift and decay models to represent the natural evolution of ionospheric scintillation. The impact on radio signals is also determined by the model and represented in graphical format to the user. A frequency scaling algorithm allows for impact analysis on frequencies other than the observation frequencies. The project began with lab-grade software and through a tailored Agile development process, deployed operational-grade code to a DoD operational center. The Agile development process promotes adaptive promote adaptive planning, evolutionary development, early delivery, continuous improvement, regular collaboration with the customer, and encourage rapid and flexible response to customer-driven changes. The Agile philosophy values individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a rigid plan. The end result was an operational capability that met customer expectations. Details of the model and the process of operational integration are discussed as well as lessons learned to improve performance on future projects.

Flexible Software Architecture for Visualization and Seismic Data Analysis

NASA Astrophysics Data System (ADS)

Petunin, S.; Pavlov, I.; Mogilenskikh, D.; Podzyuban, D.; Arkhipov, A.; Baturuin, N.; Lisin, A.; Smith, A.; Rivers, W.; Harben, P.

2007-12-01

Research in the field of seismology requires software and signal processing utilities for seismogram manipulation and analysis. Seismologists and data analysts often encounter a major problem in the use of any particular software application specific to seismic data analysis: the tuning of commands and windows to the specific waveforms and hot key combinations so as to fit their familiar informational environment. The ability to modify the user's interface independently from the developer requires an adaptive code structure. An adaptive code structure also allows for expansion of software capabilities such as new signal processing modules and implementation of more efficient algorithms. Our approach is to use a flexible "open" architecture for development of geophysical software. This report presents an integrated solution for organizing a logical software architecture based on the Unix version of the Geotool software implemented on the Microsoft NET 2.0 platform. Selection of this platform greatly expands the variety and number of computers that can implement the software, including laptops that can be utilized in field conditions. It also facilitates implementation of communication functions for seismic data requests from remote databases through the Internet. The main principle of the new architecture for Geotool is that scientists should be able to add new routines for digital waveform analysis via software plug-ins that utilize the basic Geotool display for GUI interaction. The use of plug-ins allows the efficient integration of diverse signal-processing software, including software still in preliminary development, into an organized platform without changing the fundamental structure of that platform itself. An analyst's use of Geotool is tracked via a metadata file so that future studies can reconstruct, and alter, the original signal processing operations. The work has been completed in the framework of a joint Russian- American project.

Two-component signal transduction in Corynebacterium glutamicum and other corynebacteria: on the way towards stimuli and targets.

PubMed

Bott, Michael; Brocker, Melanie

2012-06-01

In bacteria, adaptation to changing environmental conditions is often mediated by two-component signal transduction systems. In the prototypical case, a specific stimulus is sensed by a membrane-bound histidine kinase and triggers autophosphorylation of a histidine residue. Subsequently, the phosphoryl group is transferred to an aspartate residue of the cognate response regulator, which then becomes active and mediates a specific response, usually by activating and/or repressing a set of target genes. In this review, we summarize the current knowledge on two-component signal transduction in Corynebacterium glutamicum. This Gram-positive soil bacterium is used for the large-scale biotechnological production of amino acids and can also be applied for the synthesis of a wide variety of other products, such as organic acids, biofuels, or proteins. Therefore, C. glutamicum has become an important model organism in industrial biotechnology and in systems biology. The type strain ATCC 13032 possesses 13 two-component systems and the role of five has been elucidated in recent years. They are involved in citrate utilization (CitAB), osmoregulation and cell wall homeostasis (MtrAB), adaptation to phosphate starvation (PhoSR), adaptation to copper stress (CopSR), and heme homeostasis (HrrSA). As C. glutamicum does not only face changing conditions in its natural environment, but also during cultivation in industrial bioreactors of up to 500 m(3) volume, adaptability can also be crucial for good performance in biotechnological production processes. Detailed knowledge on two-component signal transduction and regulatory networks therefore will contribute to both the application and the systemic understanding of C. glutamicum and related species.

Motion-form interactions beyond the motion integration level: Evidence for interactions between orientation and optic flow signals

PubMed Central

Pavan, Andrea; Marotti, Rosilari Bellacosa; Mather, George

2013-01-01

Motion and form encoding are closely coupled in the visual system. A number of physiological studies have shown that neurons in the striate and extrastriate cortex (e.g., V1 and MT) are selective for motion direction parallel to their preferred orientation, but some neurons also respond to motion orthogonal to their preferred spatial orientation. Recent psychophysical research (Mather, Pavan, Bellacosa, & Casco, 2012) has demonstrated that the strength of adaptation to two fields of transparently moving dots is modulated by simultaneously presented orientation signals, suggesting that the interaction occurs at the level of motion integrating receptive fields in the extrastriate cortex. In the present psychophysical study, we investigated whether motion-form interactions take place at a higher level of neural processing where optic flow components are extracted. In Experiment 1, we measured the duration of the motion aftereffect (MAE) generated by contracting or expanding dot fields in the presence of either radial (parallel) or concentric (orthogonal) counterphase pedestal gratings. To tap the stage at which optic flow is extracted, we measured the duration of the phantom MAE (Weisstein, Maguire, & Berbaum, 1977) in which we adapted and tested different parts of the visual field, with orientation signals presented either in the adapting (Experiment 2) or nonadapting (Experiments 3 and 4) sectors. Overall, the results showed that motion adaptation is suppressed most by orientation signals orthogonal to optic flow direction, suggesting that motion-form interactions also take place at the global motion level where optic flow is extracted. PMID:23729767

An Adaptive INS-Aided PLL Tracking Method for GNSS Receivers in Harsh Environments.

PubMed

Cong, Li; Li, Xin; Jin, Tian; Yue, Song; Xue, Rui

2016-01-23

As the weak link in global navigation satellite system (GNSS) signal processing, the phase-locked loop (PLL) is easily influenced with frequent cycle slips and loss of lock as a result of higher vehicle dynamics and lower signal-to-noise ratios. With inertial navigation system (INS) aid, PLLs' tracking performance can be improved. However, for harsh environments with high dynamics and signal attenuation, the traditional INS-aided PLL with fixed loop parameters has some limitations to improve the tracking adaptability. In this paper, an adaptive INS-aided PLL capable of adjusting its noise bandwidth and coherent integration time has been proposed. Through theoretical analysis, the relation between INS-aided PLL phase tracking error and carrier to noise density ratio (C/N₀), vehicle dynamics, aiding information update time, noise bandwidth, and coherent integration time has been built. The relation formulae are used to choose the optimal integration time and bandwidth for a given application under the minimum tracking error criterion. Software and hardware simulation results verify the correctness of the theoretical analysis, and demonstrate that the adaptive tracking method can effectively improve the PLL tracking ability and integrated GNSS/INS navigation performance. For harsh environments, the tracking sensitivity is increased by 3 to 5 dB, velocity errors are decreased by 36% to 50% and position errors are decreased by 6% to 24% when compared with other INS-aided PLL methods.

Blood pressure reprogramming adapter assists signal recording

NASA Technical Reports Server (NTRS)

Vick, H. A.

1967-01-01

Blood pressure reprogramming adapter separates the two components of a blood pressure signal, a dc pressure signal and an ac Korotkoff sounds signal, so that the Korotkoff sounds are recorded on one channel as received while the dc pressure signal is converted to FM and recorded on a second channel.

Systems and methods for self-synchronized digital sampling

NASA Technical Reports Server (NTRS)

Samson, Jr., John R. (Inventor)

2008-01-01

Systems and methods for self-synchronized data sampling are provided. In one embodiment, a system for capturing synchronous data samples is provided. The system includes an analog to digital converter adapted to capture signals from one or more sensors and convert the signals into a stream of digital data samples at a sampling frequency determined by a sampling control signal; and a synchronizer coupled to the analog to digital converter and adapted to receive a rotational frequency signal from a rotating machine, wherein the synchronizer is further adapted to generate the sampling control signal, and wherein the sampling control signal is based on the rotational frequency signal.

Characterizing Speech Intelligibility in Noise After Wide Dynamic Range Compression.

PubMed

Rhebergen, Koenraad S; Maalderink, Thijs H; Dreschler, Wouter A

The effects of nonlinear signal processing on speech intelligibility in noise are difficult to evaluate. Often, the effects are examined by comparing speech intelligibility scores with and without processing measured at fixed signal to noise ratios (SNRs) or by comparing the adaptive measured speech reception thresholds corresponding to 50% intelligibility (SRT50) with and without processing. These outcome measures might not be optimal. Measuring at fixed SNRs can be affected by ceiling or floor effects, because the range of relevant SNRs is not know in advance. The SRT50 is less time consuming, has a fixed performance level (i.e., 50% correct), but the SRT50 could give a limited view, because we hypothesize that the effect of most nonlinear signal processing algorithms at the SRT50 cannot be generalized to other points of the psychometric function. In this article, we tested the value of estimating the entire psychometric function. We studied the effect of wide dynamic range compression (WDRC) on speech intelligibility in stationary, and interrupted speech-shaped noise in normal-hearing subjects, using a fast method-based local linear fitting approach and by two adaptive procedures. The measured performance differences for conditions with and without WDRC for the psychometric functions in stationary noise and interrupted speech-shaped noise show that the effects of WDRC on speech intelligibility are SNR dependent. We conclude that favorable and unfavorable effects of WDRC on speech intelligibility can be missed if the results are presented in terms of SRT50 values only.

Regulation of N-formyl peptide receptor signaling and trafficking by individual carboxyl-terminal serine and threonine residues.

PubMed

Potter, Ross M; Maestas, Diane C; Cimino, Daniel F; Prossnitz, Eric R

2006-05-01

Adaptation, defined as the diminution of receptor signaling in the presence of continued or repeated stimulation, is critical to cellular function. G protein-coupled receptors (GPCRs) undergo multiple adaptive processes, including desensitization and internalization, through phosphorylation of cytoplasmic serine and threonine residues. However, the relative importance of individual and combined serine and threonine residues to these processes is not well understood. We examined this mechanism in the context of the N-formyl peptide receptor (FPR), a well-characterized member of the chemoattractant/chemokine family of GPCRs critical to neutrophil function. To evaluate the contributions of individual and combinatorial serine and threonine residues to internalization, desensitization, and arrestin2 binding, 30 mutant forms of the FPR, expressed in the human promyelocytic U937 cell line, were characterized. We found that residues Ser(328), Ser(332), and Ser(338) are individually critical, and indeed sufficient, for internalization, desensitization, and arrestin2 binding, but that the presence of neighboring threonine residues can inhibit these processes. Additionally, we observed no absolute correlation between arrestin binding and either internalization or desensitization, suggesting the existence of arrestin-independent mechanisms for these processes. Our results suggest C-terminal serine and threonine residues of the FPR represent a combinatorial code, capable of both positively and negatively regulating signaling and trafficking. This study is among the first detailed analyses of a complex regulatory site in a GPCR, and provides insight into GPCR regulatory mechanisms.

Signal coupling to embedded pitch adapters in silicon sensors

NASA Astrophysics Data System (ADS)

Artuso, M.; Betancourt, C.; Bezshyiko, I.; Blusk, S.; Bruendler, R.; Bugiel, S.; Dasgupta, R.; Dendek, A.; Dey, B.; Ely, S.; Lionetto, F.; Petruzzo, M.; Polyakov, I.; Rudolph, M.; Schindler, H.; Steinkamp, O.; Stone, S.

2018-01-01

We have examined the effects of embedded pitch adapters on signal formation in n-substrate silicon microstrip sensors with data from beam tests and simulation. According to simulation, the presence of the pitch adapter metal layer changes the electric field inside the sensor, resulting in slowed signal formation on the nearby strips and a pick-up effect on the pitch adapter. This can result in an inefficiency to detect particles passing through the pitch adapter region. All these effects have been observed in the beam test data.

SMI adaptive antenna arrays for weak interfering signals. [Sample Matrix Inversion

NASA Technical Reports Server (NTRS)

Gupta, Inder J.

1986-01-01

The performance of adaptive antenna arrays in the presence of weak interfering signals (below thermal noise) is studied. It is shown that a conventional adaptive antenna array sample matrix inversion (SMI) algorithm is unable to suppress such interfering signals. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is redefined such that the effect of thermal noise on the weights of adaptive arrays is reduced. Thus, the weights are dictated by relatively weak signals. It is shown that the modified algorithm provides the desired interference protection.

Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.

PubMed

Melas, Ioannis N; Mitsos, Alexander; Messinis, Dimitris E; Weiss, Thomas S; Rodriguez, Julio-Saez; Alexopoulos, Leonidas G

2012-04-01

Construction of large and cell-specific signaling pathways is essential to understand information processing under normal and pathological conditions. On this front, gene-based approaches offer the advantage of large pathway exploration whereas phosphoproteomic approaches offer a more reliable view of pathway activities but are applicable to small pathway sizes. In this paper, we demonstrate an experimentally adaptive approach to construct large signaling pathways from phosphoproteomic data within a 3-day time frame. Our approach--taking advantage of the fast turnaround time of the xMAP technology--is carried out in four steps: (i) screen optimal pathway inducers, (ii) select the responsive ones, (iii) combine them in a combinatorial fashion to construct a phosphoproteomic dataset, and (iv) optimize a reduced generic pathway via an Integer Linear Programming formulation. As a case study, we uncover novel players and their corresponding pathways in primary human hepatocytes by interrogating the signal transduction downstream of 81 receptors of interest and constructing a detailed model for the responsive part of the network comprising 177 species (of which 14 are measured) and 365 interactions.

Cis and trans RET signaling control the survival and central projection growth of rapidly adapting mechanoreceptors

PubMed Central

Fleming, Michael S; Vysochan, Anna; Paixão, Sόnia; Niu, Jingwen; Klein, Rüdiger; Savitt, Joseph M; Luo, Wenqin

2015-01-01

RET can be activated in cis or trans by its co-receptors and ligands in vitro, but the physiological roles of trans signaling are unclear. Rapidly adapting (RA) mechanoreceptors in dorsal root ganglia (DRGs) express Ret and the co-receptor Gfrα2 and depend on Ret for survival and central projection growth. Here, we show that Ret and Gfrα2 null mice display comparable early central projection deficits, but Gfrα2 null RA mechanoreceptors recover later. Loss of Gfrα1, the co-receptor implicated in activating RET in trans, causes no significant central projection or cell survival deficit, but Gfrα1;Gfrα2 double nulls phenocopy Ret nulls. Finally, we demonstrate that GFRα1 produced by neighboring DRG neurons activates RET in RA mechanoreceptors. Taken together, our results suggest that trans and cis RET signaling could function in the same developmental process and that the availability of both forms of activation likely enhances but not diversifies outcomes of RET signaling. DOI: http://dx.doi.org/10.7554/eLife.06828.001 PMID:25838128

The role of astrocytes in the hypothalamic response and adaptation to metabolic signals.

PubMed

Chowen, Julie A; Argente-Arizón, Pilar; Freire-Regatillo, Alejandra; Frago, Laura M; Horvath, Tamas L; Argente, Jesús

2016-09-01

The hypothalamus is crucial in the regulation of homeostatic functions in mammals, with the disruption of hypothalamic circuits contributing to chronic conditions such as obesity, diabetes mellitus, hypertension, and infertility. Metabolic signals and hormonal inputs drive functional and morphological changes in the hypothalamus in attempt to maintain metabolic homeostasis. However, the dramatic increase in the incidence of obesity and its secondary complications, such as type 2 diabetes, have evidenced the need to better understand how this system functions and how it can go awry. Growing evidence points to a critical role of astrocytes in orchestrating the hypothalamic response to metabolic cues by participating in processes of synaptic transmission, synaptic plasticity and nutrient sensing. These glial cells express receptors for important metabolic signals, such as the anorexigenic hormone leptin, and determine the type and quantity of nutrients reaching their neighboring neurons. Understanding the mechanisms by which astrocytes participate in hypothalamic adaptations to changes in dietary and metabolic signals is fundamental for understanding the neuroendocrine control of metabolism and key in the search for adequate treatments of metabolic diseases. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed Central

2014-01-01

Background Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. Methods We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Results Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min −1 (0.3 min −1) and -0.7 bpm (1.7 bpm) (compared to -0.2 min −1 (0.4 min −1) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed for the Kalman filters is under 25% of the total signal length rendering it possible to perform the filtering in real-time. Conclusions It is possible to measure in real-time heart and breathing rates using an adaptive Kalman filter approach. Adapting the Kalman filter matrices improves the estimation results and makes the filter universally deployable when measuring cardiorespiratory signals. PMID:24886253

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

PubMed

Foussier, Jerome; Teichmann, Daniel; Jia, Jing; Misgeld, Berno; Leonhardt, Steffen

2014-05-09

Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min(-1) (0.3 min(-1)) and -0.7 bpm (1.7 bpm) (compared to -0.2 min(-1) (0.4 min(-1)) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed for the Kalman filters is under 25% of the total signal length rendering it possible to perform the filtering in real-time. It is possible to measure in real-time heart and breathing rates using an adaptive Kalman filter approach. Adapting the Kalman filter matrices improves the estimation results and makes the filter universally deployable when measuring cardiorespiratory signals.

Psychophysical chromatic mechanisms in macaque monkey.

PubMed

Stoughton, Cleo M; Lafer-Sousa, Rosa; Gagin, Galina; Conway, Bevil R

2012-10-24

Chromatic mechanisms have been studied extensively with psychophysical techniques in humans, but the number and nature of the mechanisms are still controversial. Appeals to monkey neurophysiology are often used to sort out the competing claims and to test hypotheses arising from the experiments in humans, but psychophysical chromatic mechanisms have never been assessed in monkeys. Here we address this issue by measuring color-detection thresholds in monkeys before and after chromatic adaptation, employing a standard approach used to determine chromatic mechanisms in humans. We conducted separate experiments using adaptation configured as either flickering full-field colors or heterochromatic gratings. Full-field colors would favor activity within the visual system at or before the arrival of retinal signals to V1, before the spatial transformation of color signals by the cortex. Conversely, gratings would favor activity within the cortex where neurons are often sensitive to spatial chromatic structure. Detection thresholds were selectively elevated for the colors of full-field adaptation when it modulated along either of the two cardinal chromatic axes that define cone-opponent color space [L vs M or S vs (L + M)], providing evidence for two privileged cardinal chromatic mechanisms implemented early in the visual-processing hierarchy. Adaptation with gratings produced elevated thresholds for colors of the adaptation regardless of its chromatic makeup, suggesting a cortical representation comprised of multiple higher-order mechanisms each selective for a different direction in color space. The results suggest that color is represented by two cardinal channels early in the processing hierarchy and many chromatic channels in brain regions closer to perceptual readout.

Visuomotor adaptation needs a validation of prediction error by feedback error

PubMed Central

Gaveau, Valérie; Prablanc, Claude; Laurent, Damien; Rossetti, Yves; Priot, Anne-Emmanuelle

2014-01-01

The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly attenuated. PMID:25408644

Immune signaling by RIG-I-like receptors

PubMed Central

Loo, Yueh-Ming; Gale, Michael

2011-01-01

The RIG-I-like receptors (RLRs) RIG-I, MDA5, and LGP2 play a major role in pathogen sensing of RNA virus infection to initiate and modulate antiviral immunity. The RLRs detect viral RNA ligands or processed self RNA in the cytoplasm to triggers innate immunity and inflammation and to impart gene expression that serves to control infection. Importantly, RLRs cooperate in signaling crosstalk networks with Toll-like receptors and other factors to impart innate immunity and to modulate the adaptive immune response. RLR regulation occurs at a variety of levels ranging from autoregulation to ligand and co-factor interactions and post-translational modifications. Abberant RLR signaling or dysregulation of RLR expression is now implicated in the development of autoimmune diseases. Understanding the processes of RLR signaling and response will provide insights to guide RLR-targeted therapeutics for antiviral and immune modifying applications. PMID:21616437

In vivo evaluation of mastication noise reduction for dual channel implantable microphone.

PubMed

Woo, SeongTak; Jung, EuiSung; Lim, HyungGyu; Lee, Jang Woo; Seong, Ki Woong; Won, Chul Ho; Kim, Myoung Nam; Cho, Jin Ho; Lee, Jyung Hyun

2014-01-01

Input for fully implantable hearing devices (FIHDs) is provided by an implantable microphone under the skin of the temporal bone. However, the implanted microphone can be affected when the FIHDs user chews. In this paper, a dual implantable microphone was designed that can filter out the noise from mastication. For the in vivo experiment, a fabricated microphone was implanted in a rabbit. Pure-tone sounds of 1 kHz through a standard speaker were applied to the rabbit, which was given food simultaneously. To evaluate noise reduction, the measured signals were processed using a MATLAB program based adaptive filter. To verify the proposed method, the correlation coefficients and signal to-noise ratio before and after signal processing were calculated. By comparing the results, signal-to-noise ratio and correlation coefficients are enhanced by 6.07dB and 0.529 respectively.

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

PubMed Central

Zhu, Bohui; Ding, Yongsheng; Hao, Kuangrong

2013-01-01

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias. PMID:23690875

Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging.

PubMed

Edifizi, Diletta; Schumacher, Björn

2017-11-04

DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process.

Omics Approaches for Identifying Physiological Adaptations to Genome Instability in Aging

PubMed Central

Edifizi, Diletta; Schumacher, Björn

2017-01-01

DNA damage causally contributes to aging and age-related diseases. The declining functioning of tissues and organs during aging can lead to the increased risk of succumbing to aging-associated diseases. Congenital syndromes that are caused by heritable mutations in DNA repair pathways lead to cancer susceptibility and accelerated aging, thus underlining the importance of genome maintenance for withstanding aging. High-throughput mass-spectrometry-based approaches have recently contributed to identifying signalling response networks and gaining a more comprehensive understanding of the physiological adaptations occurring upon unrepaired DNA damage. The insulin-like signalling pathway has been implicated in a DNA damage response (DDR) network that includes epidermal growth factor (EGF)-, AMP-activated protein kinases (AMPK)- and the target of rapamycin (TOR)-like signalling pathways, which are known regulators of growth, metabolism, and stress responses. The same pathways, together with the autophagy-mediated proteostatic response and the decline in energy metabolism have also been found to be similarly regulated during natural aging, suggesting striking parallels in the physiological adaptation upon persistent DNA damage due to DNA repair defects and long-term low-level DNA damage accumulation occurring during natural aging. These insights will be an important starting point to study the interplay between signalling networks involved in progeroid syndromes that are caused by DNA repair deficiencies and to gain new understanding of the consequences of DNA damage in the aging process. PMID:29113067

Adaptive electric potential sensors for smart signal acquisition and processing

NASA Astrophysics Data System (ADS)

Prance, R. J.; Beardsmore-Rust, S.; Prance, H.; Harland, C. J.; Stiffell, P. B.

2007-07-01

Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly.

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

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.

A low-cost biomedical signal transceiver based on a Bluetooth wireless system.

PubMed

Fazel-Rezai, Reza; Pauls, Mark; Slawinski, David

2007-01-01

Most current wireless biomedical signal transceivers use range-limiting communication. This work presents a low-cost biomedical signal transceiver that uses Bluetooth wireless technology. The design is implemented in a modular form to be adaptable to different types of biomedical signals. The signal front end obtains and processes incoming signals, which are then transmitted via a microcontroller and wireless module. Near real-time receive software in LabVIEW was developed to demonstrate the system capability. The completed transmitter prototype successfully transmits ECG signals, and is able to simultaneously send multiple signals. The sampling rate of the transmitter is fast enough to send up to thirteen ECG signals simultaneously, with an error rate below 0.1% for transmission exceeding 65 meters. A low-cost wireless biomedical transceiver has many applications, such as real-time monitoring of patients with a known condition in non-clinical settings.

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

Research in Stochastic Processes and their Applications

DTIC Science & Technology

1993-01-01

goal is to learn how Gaussian and linear signal processing methodologies should be adapted to deal with non-Gaussian regimes. Part III continues the... smoothi fmictions in /I, ami we have a chain C ... C tir C ... C /I’) C 11_ C ... C 1t_, C_ ... C ¢’, 10 4o = fH,; H =H;, H, (Hilbert space). 4ý is a Fr

Mathematical Sciences Division 1992 Programs

DTIC Science & Technology

1992-10-01

statistical theory that underlies modern signal analysis . There is a strong emphasis on stochastic processes and time series , particularly those which...include optimal resource planning and real- time scheduling of stochastic shop-floor processes. Scheduling systems will be developed that can adapt to...make forecasts for the length-of-service time series . Protocol analysis of these sessions will be used to idenify relevant contextual features and to

Distributed Fusion in Sensor Networks with Information Genealogy

DTIC Science & Technology

2011-06-28

image processing [2], acoustic and speech recognition [3], multitarget tracking [4], distributed fusion [5], and Bayesian inference [6-7]. For...Adaptation for Distant-Talking Speech Recognition." in Proc Acoustics. Speech , and Signal Processing, 2004 |4| Y Bar-Shalom and T 1-. Fortmann...used in speech recognition and other classification applications [8]. But their use in underwater mine classification is limited. In this paper, we

Digital equalization of time-delay array receivers on coherent laser communications.

PubMed

Belmonte, Aniceto

2017-01-15

Field conjugation arrays use adaptive combining techniques on multi-aperture receivers to improve the performance of coherent laser communication links by mitigating the consequences of atmospheric turbulence on the down-converted coherent power. However, this motivates the use of complex receivers as optical signals collected by different apertures need to be adaptively processed, co-phased, and scaled before they are combined. Here, we show that multiple apertures, coupled with optical delay lines, combine retarded versions of a signal at a single coherent receiver, which uses digital equalization to obtain diversity gain against atmospheric fading. We found in our analysis that, instead of field conjugation arrays, digital equalization of time-delay multi-aperture receivers is a simpler and more versatile approach to accomplish reduction of atmospheric fading.

Low-cost, high-fidelity, adaptive cancellation of periodic 60 Hz noise.

PubMed

Wesson, Kyle D; Ochshorn, Robert M; Land, Bruce R

2009-12-15

A common method to eliminate unwanted power line interference in neurobiology laboratories where sensitive electronic signals are measured is with a notch filter. However a fixed-frequency notch filter cannot remove all power line noise contamination since inherent frequency and phase variations exist in the contaminating signal. One way to overcome the limitations of a fixed-frequency notch filter is with adaptive noise cancellation. Adaptive noise cancellation is an active approach that uses feedback to create a signal that when summed with the contaminated signal destructively interferes with the noise component leaving only the desired signal. We have implemented an optimized least mean square adaptive noise cancellation algorithm on a low-cost 16 MHz, 8-bit microcontroller to adaptively cancel periodic 60 Hz noise. In our implementation, we achieve between 20 and 25 dB of cancellation of the fundamental 60 Hz noise component.

Relating brain signal variability to knowledge representation.

PubMed

Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

2012-11-15

We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

Uniform, optimal signal processing of mapped deep-sequencing data.

PubMed

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

Signal coding in cockroach photoreceptors is tuned to dim environments.

PubMed

Heimonen, K; Immonen, E-V; Frolov, R V; Salmela, I; Juusola, M; Vähäsöyrinki, M; Weckström, M

2012-11-01

In dim light, scarcity of photons typically leads to poor vision. Nonetheless, many animals show visually guided behavior with dim environments. We investigated the signaling properties of photoreceptors of the dark active cockroach (Periplaneta americana) using intracellular and whole-cell patch-clamp recordings to determine whether they show selective functional adaptations to dark. Expectedly, dark-adapted photoreceptors generated large and slow responses to single photons. However, when light adapted, responses of both phototransduction and the nontransductive membrane to white noise (WN)-modulated stimuli remained slow with corner frequencies ~20 Hz. This promotes temporal integration of light inputs and maintains high sensitivity of vision. Adaptive changes in dynamics were limited to dim conditions. Characteristically, both step and frequency responses stayed effectively unchanged for intensities >1,000 photons/s/photoreceptor. A signal-to-noise ratio (SNR) of the light responses was transiently higher at frequencies <5 Hz for ~5 s after light onset but deteriorated to a lower value upon longer stimulation. Naturalistic light stimuli, as opposed to WN, evoked markedly larger responses with higher SNRs at low frequencies. This allowed realistic estimates of information transfer rates, which saturated at ~100 bits/s at low-light intensities. We found, therefore, selective adaptations beneficial for vision in dim environments in cockroach photoreceptors: large amplitude of single-photon responses, constant high level of temporal integration of light inputs, saturation of response properties at low intensities, and only transiently efficient encoding of light contrasts. The results also suggest that the sources of the large functional variability among different photoreceptors reside mostly in phototransduction processes and not in the properties of the nontransductive membrane.

Multi-element array signal reconstruction with adaptive least-squares algorithms

NASA Technical Reports Server (NTRS)

Kumar, R.

1992-01-01

Two versions of the adaptive least-squares algorithm are presented for combining signals from multiple feeds placed in the focal plane of a mechanical antenna whose reflector surface is distorted due to various deformations. Coherent signal combining techniques based on the adaptive least-squares algorithm are examined for nearly optimally and adaptively combining the outputs of the feeds. The performance of the two versions is evaluated by simulations. It is demonstrated for the example considered that both of the adaptive least-squares algorithms are capable of offsetting most of the loss in the antenna gain incurred due to reflector surface deformations.

MECHANISTIC PATHWAYS AND BIOLOGICAL ROLES FOR RECEPTOR-INDEPENDENT ACTIVATORS OF G-PROTEIN SIGNALING

PubMed Central

Blumer, Joe B.; Smrcka, Alan V.; Lanier, S.M.

2007-01-01

Signal processing via heterotrimeric G-proteins in response to cell surface receptors is a central and much investigated aspect of how cells integrate cellular stimuli to produce coordinated biological responses. The system is a target of numerous therapeutic agents, plays an important role in adaptive processes of organs, and aberrant processing of signals through these transducing systems is a component of various disease states. In addition to GPCR-mediated activation of G-protein signaling, nature has evolved creative ways to manipulate and utilize the Gαβγ heterotrimer or Gα and Gαβγ subunits independent of the cell surface receptor stimuli. In such situations, the G-protein subunits (Gα and Gαβγ) may actually be complexed with alternative binding partners independent of the typical heterotrimeric Gαβγ. Such regulatory accessory proteins include the family of RGS proteins that accelerate the GTPase activity of Gα and various entities that influence nucleotide binding properties and/or subunit interaction. The latter group of proteins includes receptor independent activators of G-protein signaling or AGS proteins that play surprising roles in signal processing. This review provides an overview of our current knowledge regarding AGS proteins. AGS proteins are indicative of a growing number of accessory proteins that influence signal propagation, facilitate cross talk between various types of signaling pathways and provide a platform for diverse functions of both the heterotrimeric Gαβγ and the individual Gα and Gαβγ subunits. PMID:17240454

Development of a scalable generic platform for adaptive optics real time control

NASA Astrophysics Data System (ADS)

Surendran, Avinash; Burse, Mahesh P.; Ramaprakash, A. N.; Parihar, Padmakar

2015-06-01

The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an Adaptive Optics (AO) system, the generation of the Deformable Mirror (DM) control voltages from the Wavefront Sensor (WFS) measurements is usually through the multiplication of the wavefront slopes with a predetermined reconstructor matrix. The ability to access several hundred hard multipliers and memories concurrently in an FPGA allows performance far beyond that of a modern CPU or GPU for tasks with a well-defined structure such as Adaptive Optics control. The target of the current project is to generate a signal for a real time wavefront correction, from the signals coming from a Wavefront Sensor, wherein the system would be flexible to accommodate all the current Wavefront Sensing techniques and also the different methods which are used for wavefront compensation. The system should also accommodate for different data transmission protocols (like Ethernet, USB, IEEE 1394 etc.) for transmitting data to and from the FPGA device, thus providing a more flexible platform for Adaptive Optics control. Preliminary simulation results for the formulation of the platform, and a design of a fully scalable slope computer is presented.

Adaptive noise cancelling and time-frequency techniques for rail surface defect detection

NASA Astrophysics Data System (ADS)

Liang, B.; Iwnicki, S.; Ball, A.; Young, A. E.

2015-03-01

Adaptive noise cancelling (ANC) is a technique which is very effective to remove additive noises from the contaminated signals. It has been widely used in the fields of telecommunication, radar and sonar signal processing. However it was seldom used for the surveillance and diagnosis of mechanical systems before late of 1990s. As a promising technique it has gradually been exploited for the purpose of condition monitoring and fault diagnosis. Time-frequency analysis is another useful tool for condition monitoring and fault diagnosis purpose as time-frequency analysis can keep both time and frequency information simultaneously. This paper presents an ANC and time-frequency application for railway wheel flat and rail surface defect detection. The experimental results from a scaled roller test rig show that this approach can significantly reduce unwanted interferences and extract the weak signals from strong background noises. The combination of ANC and time-frequency analysis may provide us one of useful tools for condition monitoring and fault diagnosis of railway vehicles.

A case study of evolutionary computation of biochemical adaptation

NASA Astrophysics Data System (ADS)

François, Paul; Siggia, Eric D.

2008-06-01

Simulations of evolution have a long history, but their relation to biology is questioned because of the perceived contingency of evolution. Here we provide an example of a biological process, adaptation, where simulations are argued to approach closer to biology. Adaptation is a common feature of sensory systems, and a plausible component of other biochemical networks because it rescales upstream signals to facilitate downstream processing. We create random gene networks numerically, by linking genes with interactions that model transcription, phosphorylation and protein-protein association. We define a fitness function for adaptation in terms of two functional metrics, and show that any reasonable combination of them will yield the same adaptive networks after repeated rounds of mutation and selection. Convergence to these networks is driven by positive selection and thus fast. There is always a path in parameter space of continuously improving fitness that leads to perfect adaptation, implying that the actual mutation rates we use in the simulation do not bias the results. Our results imply a kinetic view of evolution, i.e., it favors gene networks that can be learned quickly from the random examples supplied by mutation. This formulation allows for deductive predictions of the networks realized in nature.

SisPorto 4.0 - computer analysis following the 2015 FIGO Guidelines for intrapartum fetal monitoring.

PubMed

Ayres-de-Campos, Diogo; Rei, Mariana; Nunes, Inês; Sousa, Paulo; Bernardes, João

2017-01-01

SisPorto 4.0 is the most recent version of a program for the computer analysis of cardiotocographic (CTG) signals and ST events, which has been adapted to the 2015 International Federation of Gynaecology and Obstetrics (FIGO) guidelines for intrapartum foetal monitoring. This paper provides a detailed description of the analysis performed by the system, including the signal-processing algorithms involved in identification of basic CTG features and the resulting real-time alerts.

twzPEA: A Topology and Working Zone Based Pathway Enrichment Analysis Framework

USDA-ARS?s Scientific Manuscript database

Sensitive detection of involvement and adaptation of key signaling, regulatory, and metabolic pathways holds the key to deciphering molecular mechanisms such as those in the biomass-to-biofuel conversion process in yeast. Typical gene set enrichment analyses often do not use topology information in...

A labview-based GUI for the measurement of otoacoustic emissions.

PubMed

Wu, Ye; McNamara, D M; Ziarani, A K

2006-01-01

This paper presents the outcome of a software development project aimed at creating a stand-alone user-friendly signal processing algorithm for the estimation of distortion product otoacoustic emission (OAE) signals. OAE testing is one of the most commonly used methods of first screening of newborns' hearing. Most of the currently available commercial devices rely upon averaging long strings of data and subsequent discrete Fourier analysis to estimate low level OAE signals from within the background noise in the presence of the strong stimuli. The main shortcoming of the presently employed technology is the need for long measurement time and its low noise immunity. The result of the software development project presented here is a graphical user interface (GUI) module that implements a recently introduced adaptive technique of OAE signal estimation. This software module is easy to use and is freely disseminated on the Internet for the use of the hearing research community. This GUI module allows loading of the a priori recorded OAE signals into the workspace, and provides the user with interactive instructions for the OAE signal estimation. Moreover, the user can generate simulated OAE signals to objectively evaluate the performance capability of the implemented signal processing technique.

Collective motion in animal groups from a neurobiological perspective: the adaptive benefits of dynamic sensory loads and selective attention.

PubMed

Lemasson, B H; Anderson, J J; Goodwin, R A

2009-12-21

We explore mechanisms associated with collective animal motion by drawing on the neurobiological bases of sensory information processing and decision-making. The model uses simplified retinal processes to translate neighbor movement patterns into information through spatial signal integration and threshold responses. The structure provides a mechanism by which individuals can vary their sets of influential neighbors, a measure of an individual's sensory load. Sensory loads are correlated with group order and density, and we discuss their adaptive values in an ecological context. The model also provides a mechanism by which group members can identify, and rapidly respond to, novel visual stimuli.

Fast ℓ1-regularized space-time adaptive processing using alternating direction method of multipliers

NASA Astrophysics Data System (ADS)

Qin, Lilong; Wu, Manqing; Wang, Xuan; Dong, Zhen

2017-04-01

Motivated by the sparsity of filter coefficients in full-dimension space-time adaptive processing (STAP) algorithms, this paper proposes a fast ℓ1-regularized STAP algorithm based on the alternating direction method of multipliers to accelerate the convergence and reduce the calculations. The proposed algorithm uses a splitting variable to obtain an equivalent optimization formulation, which is addressed with an augmented Lagrangian method. Using the alternating recursive algorithm, the method can rapidly result in a low minimum mean-square error without a large number of calculations. Through theoretical analysis and experimental verification, we demonstrate that the proposed algorithm provides a better output signal-to-clutter-noise ratio performance than other algorithms.

Ensemble Empirical Mode Decomposition based methodology for ultrasonic testing of coarse grain austenitic stainless steels.

PubMed

Sharma, Govind K; Kumar, Anish; Jayakumar, T; Purnachandra Rao, B; Mariyappa, N

2015-03-01

A signal processing methodology is proposed in this paper for effective reconstruction of ultrasonic signals in coarse grained high scattering austenitic stainless steel. The proposed methodology is comprised of the Ensemble Empirical Mode Decomposition (EEMD) processing of ultrasonic signals and application of signal minimisation algorithm on selected Intrinsic Mode Functions (IMFs) obtained by EEMD. The methodology is applied to ultrasonic signals obtained from austenitic stainless steel specimens of different grain size, with and without defects. The influence of probe frequency and data length of a signal on EEMD decomposition is also investigated. For a particular sampling rate and probe frequency, the same range of IMFs can be used to reconstruct the ultrasonic signal, irrespective of the grain size in the range of 30-210 μm investigated in this study. This methodology is successfully employed for detection of defects in a 50mm thick coarse grain austenitic stainless steel specimens. Signal to noise ratio improvement of better than 15 dB is observed for the ultrasonic signal obtained from a 25 mm deep flat bottom hole in 200 μm grain size specimen. For ultrasonic signals obtained from defects at different depths, a minimum of 7 dB extra enhancement in SNR is achieved as compared to the sum of selected IMF approach. The application of minimisation algorithm with EEMD processed signal in the proposed methodology proves to be effective for adaptive signal reconstruction with improved signal to noise ratio. This methodology was further employed for successful imaging of defects in a B-scan. Copyright © 2014. Published by Elsevier B.V.

Ultra-Low Power Dynamic Knob in Adaptive Compressed Sensing Towards Biosignal Dynamics.

PubMed

Wang, Aosen; Lin, Feng; Jin, Zhanpeng; Xu, Wenyao

2016-06-01

Compressed sensing (CS) is an emerging sampling paradigm in data acquisition. Its integrated analog-to-information structure can perform simultaneous data sensing and compression with low-complexity hardware. To date, most of the existing CS implementations have a fixed architectural setup, which lacks flexibility and adaptivity for efficient dynamic data sensing. In this paper, we propose a dynamic knob (DK) design to effectively reconfigure the CS architecture by recognizing the biosignals. Specifically, the dynamic knob design is a template-based structure that comprises a supervised learning module and a look-up table module. We model the DK performance in a closed analytic form and optimize the design via a dynamic programming formulation. We present the design on a 130 nm process, with a 0.058 mm (2) fingerprint and a 187.88 nJ/event energy-consumption. Furthermore, we benchmark the design performance using a publicly available dataset. Given the energy constraint in wireless sensing, the adaptive CS architecture can consistently improve the signal reconstruction quality by more than 70%, compared with the traditional CS. The experimental results indicate that the ultra-low power dynamic knob can provide an effective adaptivity and improve the signal quality in compressed sensing towards biosignal dynamics.

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Time Reversal Acoustic Communication Using Filtered Multitone Modulation

PubMed Central

Sun, Lin; Chen, Baowei; Li, Haisen; Zhou, Tian; Li, Ruo

2015-01-01

The multipath spread in underwater acoustic channels is severe and, therefore, when the symbol rate of the time reversal (TR) acoustic communication using single-carrier (SC) modulation is high, the large intersymbol interference (ISI) span caused by multipath reduces the performance of the TR process and needs to be removed using the long adaptive equalizer as the post-processor. In this paper, a TR acoustic communication method using filtered multitone (FMT) modulation is proposed in order to reduce the residual ISI in the processed signal using TR. In the proposed method, FMT modulation is exploited to modulate information symbols onto separate subcarriers with high spectral containment and TR technique, as well as adaptive equalization is adopted at the receiver to suppress ISI and noise. The performance of the proposed method is assessed through simulation and real data from a trial in an experimental pool. The proposed method was compared with the TR acoustic communication using SC modulation with the same spectral efficiency. Results demonstrate that the proposed method can improve the performance of the TR process and reduce the computational complexity of adaptive equalization for post-process. PMID:26393586

Time Reversal Acoustic Communication Using Filtered Multitone Modulation.

PubMed

Sun, Lin; Chen, Baowei; Li, Haisen; Zhou, Tian; Li, Ruo

2015-09-17

The multipath spread in underwater acoustic channels is severe and, therefore, when the symbol rate of the time reversal (TR) acoustic communication using single-carrier (SC) modulation is high, the large intersymbol interference (ISI) span caused by multipath reduces the performance of the TR process and needs to be removed using the long adaptive equalizer as the post-processor. In this paper, a TR acoustic communication method using filtered multitone (FMT) modulation is proposed in order to reduce the residual ISI in the processed signal using TR. In the proposed method, FMT modulation is exploited to modulate information symbols onto separate subcarriers with high spectral containment and TR technique, as well as adaptive equalization is adopted at the receiver to suppress ISI and noise. The performance of the proposed method is assessed through simulation and real data from a trial in an experimental pool. The proposed method was compared with the TR acoustic communication using SC modulation with the same spectral efficiency. Results demonstrate that the proposed method can improve the performance of the TR process and reduce the computational complexity of adaptive equalization for post-process.

Experiments on Adaptive Self-Tuning of Seismic Signal Detector Parameters

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Chael, E. P.; Peterson, M. G.; Lawry, B.; Phillips-Alonge, K. E.; Balch, R. S.; Ziegler, A.

2016-12-01

Scientific applications, including underground nuclear test monitoring and microseismic monitoring can benefit enormously from data-driven dynamic algorithms for tuning seismic and infrasound signal detection parameters since continuous streams are producing waveform archives on the order of 1TB per month. Tuning is a challenge because there are a large number of data processing parameters that interact in complex ways, and because the underlying populating of true signal detections is generally unknown. The largely manual process of identifying effective parameters, often performed only over a subset of stations over a short time period, is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. We present improvements to an Adaptive Self-Tuning algorithm for continuously adjusting detection parameters based on consistency with neighboring sensors. Results are shown for 1) data from a very dense network ( 120 stations, 10 km radius) deployed during 2008 on Erebus Volcano, Antarctica, and 2) data from a continuous downhole seismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project. Performance is assessed in terms of missed detections and false detections relative to human analyst detections, simulated waveforms where ground-truth detections exist and visual inspection.

Automated filtering of common-mode artifacts in multichannel physiological recordings.

PubMed

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

2013-10-01

The removal of spatially correlated noise is an important step in processing multichannel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases, the ACAR even outperformed independent component analysis. On 16 channels of simulated data, the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic recordings further showed the effectiveness of the ACAR.

Automated Filtering of Common Mode Artifacts in Multi-Channel Physiological Recordings

PubMed Central

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

2014-01-01

The removal of spatially correlated noise is an important step in processing multi-channel recordings. Here, a technique termed the adaptive common average reference (ACAR) is presented as an effective and simple method for removing this noise. The ACAR is based on a combination of the well-known common average reference (CAR) and an adaptive noise canceling (ANC) filter. In a convergent process, the CAR provides a reference to an ANC filter, which in turn provides feedback to enhance the CAR. This method was effective on both simulated and real data, outperforming the standard CAR when the amplitude or polarity of the noise changes across channels. In many cases the ACAR even outperformed independent component analysis (ICA). On 16 channels of simulated data the ACAR was able to attenuate up to approximately 290 dB of noise and could improve signal quality if the original SNR was as high as 5 dB. With an original SNR of 0 dB, the ACAR improved signal quality with only two data channels and performance improved as the number of channels increased. It also performed well under many different conditions for the structure of the noise and signals. Analysis of contaminated electrocorticographic (ECoG) recordings further showed the effectiveness of the ACAR. PMID:23708770

A Neural Mechanism for Time-Window Separation Resolves Ambiguity of Adaptive Coding

PubMed Central

Hildebrandt, K. Jannis; Ronacher, Bernhard; Hennig, R. Matthias; Benda, Jan

2015-01-01

The senses of animals are confronted with changing environments and different contexts. Neural adaptation is one important tool to adjust sensitivity to varying intensity ranges. For instance, in a quiet night outdoors, our hearing is more sensitive than when we are confronted with the plurality of sounds in a large city during the day. However, adaptation also removes available information on absolute sound levels and may thus cause ambiguity. Experimental data on the trade-off between benefits and loss through adaptation is scarce and very few mechanisms have been proposed to resolve it. We present an example where adaptation is beneficial for one task—namely, the reliable encoding of the pattern of an acoustic signal—but detrimental for another—the localization of the same acoustic stimulus. With a combination of neurophysiological data, modeling, and behavioral tests, we show that adaptation in the periphery of the auditory pathway of grasshoppers enables intensity-invariant coding of amplitude modulations, but at the same time, degrades information available for sound localization. We demonstrate how focusing the response of localization neurons to the onset of relevant signals separates processing of localization and pattern information temporally. In this way, the ambiguity of adaptive coding can be circumvented and both absolute and relative levels can be processed using the same set of peripheral neurons. PMID:25761097

Adaptive traffic signal control system (ACS-Lite) for Wolf Road, Albany, New York.

DOT National Transportation Integrated Search

2014-10-01

Adaptive Control Software Lite (ACS : - : Lite) is a : traffic : signal timing optimization system that : dynamically adjusts : traffic : signal timing : s : to meet current traffic demands. : The purpose of this : research project : was : to : deplo...

Immunometabolic circuits in trained immunity.

PubMed

Arts, Rob J W; Joosten, Leo A B; Netea, Mihai G

2016-10-01

The classical view that only adaptive immunity can build immunological memory has recently been challenged. Both in organisms lacking adaptive immunity as well as in mammals, the innate immune system can adapt to mount an increased resistance to reinfection, a de facto innate immune memory termed trained immunity. Recent studies have revealed that rewiring of cellular metabolism induced by different immunological signals is a crucial step for determining the epigenetic changes underlying trained immunity. Processes such as a shift of glucose metabolism from oxidative phosphorylation to aerobic glycolysis, increased glutamine metabolism and cholesterol synthesis, play a crucial role in these processes. The discovery of trained immunity opens the door for the design of novel generations of vaccines, for new therapeutic strategies for the treatment of immune deficiency states, and for modulation of exaggerated inflammation in autoinflammatory diseases. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

NASA Astrophysics Data System (ADS)

Orra, Kashfull; Choudhury, Sounak K.

2016-12-01

The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

Testing Convergent Evolution in Auditory Processing Genes between Echolocating Mammals and the Aye-Aye, a Percussive-Foraging Primate

PubMed Central

Jerjos, Michael; Hohman, Baily; Lauterbur, M. Elise; Kistler, Logan

2017-01-01

Abstract Several taxonomically distinct mammalian groups—certain microbats and cetaceans (e.g., dolphins)—share both morphological adaptations related to echolocation behavior and strong signatures of convergent evolution at the amino acid level across seven genes related to auditory processing. Aye-ayes (Daubentonia madagascariensis) are nocturnal lemurs with a specialized auditory processing system. Aye-ayes tap rapidly along the surfaces of trees, listening to reverberations to identify the mines of wood-boring insect larvae; this behavior has been hypothesized to functionally mimic echolocation. Here we investigated whether there are signals of convergence in auditory processing genes between aye-ayes and known mammalian echolocators. We developed a computational pipeline (Basic Exon Assembly Tool) that produces consensus sequences for regions of interest from shotgun genomic sequencing data for nonmodel organisms without requiring de novo genome assembly. We reconstructed complete coding region sequences for the seven convergent echolocating bat–dolphin genes for aye-ayes and another lemur. We compared sequences from these two lemurs in a phylogenetic framework with those of bat and dolphin echolocators and appropriate nonecholocating outgroups. Our analysis reaffirms the existence of amino acid convergence at these loci among echolocating bats and dolphins; some methods also detected signals of convergence between echolocating bats and both mice and elephants. However, we observed no significant signal of amino acid convergence between aye-ayes and echolocating bats and dolphins, suggesting that aye-aye tap-foraging auditory adaptations represent distinct evolutionary innovations. These results are also consistent with a developing consensus that convergent behavioral ecology does not reliably predict convergent molecular evolution. PMID:28810710

SLAP, a regulator of immunoreceptor ubiquitination, signaling, and trafficking.

PubMed

Dragone, Leonard L; Shaw, Laura A; Myers, Margaret D; Weiss, Arthur

2009-11-01

Src-like adapter proteins (SLAP and SLAP-2) constitute a family of proteins that are expressed in a variety of cell types but are studied most extensively in lymphocytes. They have been shown to associate with proximal components of the T-cell receptor (TCR) and B-cell receptor (BCR) signaling complexes. An interaction of SLAP with c-Cbl leads to the ubiquitination and degradation of phosphorylated components of the TCR- and BCR-signaling complexes. The absence of this process in immature SLAP-deficient T and B cells leads to increased immunoreceptor levels due to decreased intracellular retention and degradation. We propose a model in which SLAP-dependent regulation of immunoreceptor levels allows for finer control of immunoreceptor signaling. Thus, SLAP functions to dampen immunoreceptor signaling, thereby influencing lymphocyte development and repertoire selection.

SMI adaptive antenna arrays for weak interfering signals

NASA Technical Reports Server (NTRS)

Gupta, I. J.

1987-01-01

The performance of adaptive antenna arrays is studied when a sample matrix inversion (SMI) algorithm is used to control array weights. It is shown that conventional SMI adaptive antennas, like other adaptive antennas, are unable to suppress weak interfering signals (below thermal noise) encountered in broadcasting satellite communication systems. To overcome this problem, the SMI algorithm is modified. In the modified algorithm, the covariance matrix is modified such that the effect of thermal noise on the weights of the adaptive array is reduced. Thus, the weights are dictated by relatively weak coherent signals. It is shown that the modified algorithm provides the desired interference protection. The use of defocused feeds as auxiliary elements of an SMI adaptive array is also discussed.

How visual illusions illuminate complementary brain processes: illusory depth from brightness and apparent motion of illusory contours

PubMed Central

Grossberg, Stephen

2014-01-01

Neural models of perception clarify how visual illusions arise from adaptive neural processes. Illusions also provide important insights into how adaptive neural processes work. This article focuses on two illusions that illustrate a fundamental property of global brain organization; namely, that advanced brains are organized into parallel cortical processing streams with computationally complementary properties. That is, in order to process certain combinations of properties, each cortical stream cannot process complementary properties. Interactions between these streams, across multiple processing stages, overcome their complementary deficiencies to compute effective representations of the world, and to thereby achieve the property of complementary consistency. The two illusions concern how illusory depth can vary with brightness, and how apparent motion of illusory contours can occur. Illusory depth from brightness arises from the complementary properties of boundary and surface processes, notably boundary completion and surface-filling in, within the parvocellular form processing cortical stream. This illusion depends upon how surface contour signals from the V2 thin stripes to the V2 interstripes ensure complementary consistency of a unified boundary/surface percept. Apparent motion of illusory contours arises from the complementary properties of form and motion processes across the parvocellular and magnocellular cortical processing streams. This illusion depends upon how illusory contours help to complete boundary representations for object recognition, how apparent motion signals can help to form continuous trajectories for target tracking and prediction, and how formotion interactions from V2-to-MT enable completed object representations to be continuously tracked even when they move behind intermittently occluding objects through time. PMID:25389399

A reinforcement learning model of joy, distress, hope and fear

NASA Astrophysics Data System (ADS)

Broekens, Joost; Jacobs, Elmer; Jonker, Catholijn M.

2015-07-01

In this paper we computationally study the relation between adaptive behaviour and emotion. Using the reinforcement learning framework, we propose that learned state utility, ?, models fear (negative) and hope (positive) based on the fact that both signals are about anticipation of loss or gain. Further, we propose that joy/distress is a signal similar to the error signal. We present agent-based simulation experiments that show that this model replicates psychological and behavioural dynamics of emotion. This work distinguishes itself by assessing the dynamics of emotion in an adaptive agent framework - coupling it to the literature on habituation, development, extinction and hope theory. Our results support the idea that the function of emotion is to provide a complex feedback signal for an organism to adapt its behaviour. Our work is relevant for understanding the relation between emotion and adaptation in animals, as well as for human-robot interaction, in particular how emotional signals can be used to communicate between adaptive agents and humans.

Method and apparatus for detection of catalyst failure on-board a motor vehicle using a dual oxygen sensor and an algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clemmens, W.B.; Koupal, J.W.; Sabourin, M.A.

1993-07-20

Apparatus is described for detecting motor vehicle exhaust gas catalytic converter deterioration comprising a first exhaust gas oxygen sensor adapted for communication with an exhaust stream before passage of the exhaust stream through a catalytic converter and a second exhaust gas oxygen sensor adapted for communication with the exhaust stream after passage of the exhaust stream through the catalytic converter, an on-board vehicle computational means, said computational means adapted to accept oxygen content signals from the before and after catalytic converter oxygen sensors and adapted to generate signal threshold values, said computational means adapted to compare over repeated time intervalsmore » the oxygen content signals to the signal threshold values and to store the output of the compared oxygen content signals, and in response after a specified number of time intervals for a specified mode of motor vehicle operation to determine and indicate a level of catalyst deterioration.« less

A theory of cerebellar cortex and adaptive motor control based on two types of universal function approximation capability.

PubMed

Fujita, Masahiko

2016-03-01

Lesions of the cerebellum result in large errors in movements. The cerebellum adaptively controls the strength and timing of motor command signals depending on the internal and external environments of movements. The present theory describes how the cerebellar cortex can control signals for accurate and timed movements. A model network of the cerebellar Golgi and granule cells is shown to be equivalent to a multiple-input (from mossy fibers) hierarchical neural network with a single hidden layer of threshold units (granule cells) that receive a common recurrent inhibition (from a Golgi cell). The weighted sum of the hidden unit signals (Purkinje cell output) is theoretically analyzed regarding the capability of the network to perform two types of universal function approximation. The hidden units begin firing as the excitatory inputs exceed the recurrent inhibition. This simple threshold feature leads to the first approximation theory, and the network final output can be any continuous function of the multiple inputs. When the input is constant, this output becomes stationary. However, when the recurrent unit activity is triggered to decrease or the recurrent inhibition is triggered to increase through a certain mechanism (metabotropic modulation or extrasynaptic spillover), the network can generate any continuous signals for a prolonged period of change in the activity of recurrent signals, as the second approximation theory shows. By incorporating the cerebellar capability of two such types of approximations to a motor system, in which learning proceeds through repeated movement trials with accompanying corrections, accurate and timed responses for reaching the target can be adaptively acquired. Simple models of motor control can solve the motor error vs. sensory error problem, as well as the structural aspects of credit (or error) assignment problem. Two physiological experiments are proposed for examining the delay and trace conditioning of eyelid responses, as well as saccade adaptation, to investigate this novel idea of cerebellar processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Remote diagnosis server

NASA Technical Reports Server (NTRS)

Deb, Somnath (Inventor); Ghoshal, Sudipto (Inventor); Malepati, Venkata N. (Inventor); Kleinman, David L. (Inventor); Cavanaugh, Kevin F. (Inventor)

2004-01-01

A network-based diagnosis server for monitoring and diagnosing a system, the server being remote from the system it is observing, comprises a sensor for generating signals indicative of a characteristic of a component of the system, a network-interfaced sensor agent coupled to the sensor for receiving signals therefrom, a broker module coupled to the network for sending signals to and receiving signals from the sensor agent, a handler application connected to the broker module for transmitting signals to and receiving signals therefrom, a reasoner application in communication with the handler application for processing, and responding to signals received from the handler application, wherein the sensor agent, broker module, handler application, and reasoner applications operate simultaneously relative to each other, such that the present invention diagnosis server performs continuous monitoring and diagnosing of said components of the system in real time. The diagnosis server is readily adaptable to various different systems.

Chaotic Signal Denoising Based on Hierarchical Threshold Synchrosqueezed Wavelet Transform

NASA Astrophysics Data System (ADS)

Wang, Wen-Bo; Jing, Yun-yu; Zhao, Yan-chao; Zhang, Lian-Hua; Wang, Xiang-Li

2017-12-01

In order to overcoming the shortcoming of single threshold synchrosqueezed wavelet transform(SWT) denoising method, an adaptive hierarchical threshold SWT chaotic signal denoising method is proposed. Firstly, a new SWT threshold function is constructed based on Stein unbiased risk estimation, which is two order continuous derivable. Then, by using of the new threshold function, a threshold process based on the minimum mean square error was implemented, and the optimal estimation value of each layer threshold in SWT chaotic denoising is obtained. The experimental results of the simulating chaotic signal and measured sunspot signals show that, the proposed method can filter the noise of chaotic signal well, and the intrinsic chaotic characteristic of the original signal can be recovered very well. Compared with the EEMD denoising method and the single threshold SWT denoising method, the proposed method can obtain better denoising result for the chaotic signal.

Hostile takeover: Manipulation of HIF-1 signaling in pathogen-associated cancers (Review).

PubMed

Zhu, Caixia; Zhu, Qing; Wang, Chong; Zhang, Liming; Wei, Fang; Cai, Qiliang

2016-10-01

Hypoxia-inducible factor (HIF)-1 is a central regulator in the adaptation process of cell response to hypoxia (low oxygen). Emerging evidence has demonstrated that HIF-1 plays an important role in the development and progression of many types of human diseases, including pathogen-associated cancers. In the present review, we summarize the recent understandings of how human pathogenic agents including viruses, bacteria and parasites deregulate cellular HIF-1 signaling pathway in their associated cancer cells, and highlight the common molecular mechanisms of HIF-1 signaling activated by these pathogenic infection, which could act as potential diagnostic markers and new therapeutic strategies against human infectious cancers.

Adapting the Stress Response: Viral Subversion of the mTOR Signaling Pathway.

PubMed

Le Sage, Valerie; Cinti, Alessandro; Amorim, Raquel; Mouland, Andrew J

2016-05-24

The mammalian target of rapamycin (mTOR) is a central regulator of gene expression, translation and various metabolic processes. Multiple extracellular (growth factors) and intracellular (energy status) molecular signals as well as a variety of stressors are integrated into the mTOR pathway. Viral infection is a significant stress that can activate, reduce or even suppress the mTOR signaling pathway. Consequently, viruses have evolved a plethora of different mechanisms to attack and co-opt the mTOR pathway in order to make the host cell a hospitable environment for replication. A more comprehensive knowledge of different viral interactions may provide fruitful targets for new antiviral drugs.

The Development and Application of Random Matrix Theory in Adaptive Signal Processing in the Sample Deficient Regime

DTIC Science & Technology

2014-09-01

optimal diagonal loading which minimizes the MSE. The be- havior of optimal diagonal loading when the arrival process is composed of plane waves embedded...observation vectors. The examples of the ensemble correlation matrix corresponding to the input process consisting of a single or multiple plane waves...Y ∗ij is a complex-conjugate of Yij. This result is used in order to evaluate the expectations of different quadratic forms. The Poincare -Nash

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review.

PubMed

Du, Jiaying; Gerdtman, Christer; Lindén, Maria

2018-04-06

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review

PubMed Central

Gerdtman, Christer

2018-01-01

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented. PMID:29642412

Linking inter-individual differences in the conflict adaptation effect to spontaneous brain activity.

PubMed

Wang, Ting; Chen, Zhencai; Zhao, Guang; Hitchman, Glenn; Liu, Congcong; Zhao, Xiaoyue; Liu, Yijun; Chen, Antao

2014-04-15

Conflict adaptation has been widely researched in normal and clinical populations. There are large individual differences in conflict adaptation, and it has been linked to the schizotypal trait. However, no study to date has examined how individual differences in spontaneous brain activity are related to behavioral conflict adaptation (performance). Resting-state functional magnetic resonance imaging (RS-fMRI) is a promising tool to investigate this issue. The present study evaluated the regional homogeneity (ReHo) of RS-fMRI signals in order to explore the neural basis of individual differences in conflict adaptation across two independent samples comprising a total of 67 normal subjects. A partial correlation analysis was carried out to examine the relationship between ReHo and behavioral conflict adaptation, while controlling for reaction time, standard deviation and flanker interference effects. This analysis was conducted on 39 subjects' data (sample 1); the results showed significant positive correlations in the left dorsolateral prefrontal cortex (DLPFC) and left ventrolateral prefrontal cortex. We then conducted a test-validation procedure on the remaining 28 subjects' data (sample 2) to examine the reliability of the results. Regions of interest were defined based on the correlation results. Regression analysis showed that variability in ReHo values in the DLPFC accounted for 48% of the individual differences in the conflict adaptation effect in sample 2. The present findings provide further support for the importance of the DLPFC in the conflict adaptation process. More importantly, we demonstrated that ReHo of RS-fMRI signals in the DLPFC can predict behavioral performance in conflict adaptation, which provides potential biomarkers for the early detection of cognitive control deterioration. Copyright © 2013 Elsevier Inc. All rights reserved.

Adaptive/learning control of large space structures - System identification techniques. [for multi-configuration flexible spacecraft

NASA Technical Reports Server (NTRS)

Thau, F. E.; Montgomery, R. C.

1980-01-01

Techniques developed for the control of aircraft under changing operating conditions are used to develop a learning control system structure for a multi-configuration, flexible space vehicle. A configuration identification subsystem that is to be used with a learning algorithm and a memory and control process subsystem is developed. Adaptive gain adjustments can be achieved by this learning approach without prestoring of large blocks of parameter data and without dither signal inputs which will be suppressed during operations for which they are not compatible. The Space Shuttle Solar Electric Propulsion (SEP) experiment is used as a sample problem for the testing of adaptive/learning control system algorithms.

Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

2016-10-01

Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

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.

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

Adaptive control for accelerators

DOEpatents

Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

1991-01-01

An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.

An Approach for Smart Antenna Testbed

NASA Astrophysics Data System (ADS)

Kawitkar, R. S.; Wakde, D. G.

2003-07-01

The use of wireless, mobile, personal communications services are expanding rapidly. Adaptive or "Smart" antenna arrays can increase channel capacity through spatial division. Adaptive antennas can also track mobile users, improving both signal range and quality. For these reasons, smart antenna systems have attracted widespread interest in the telecommunications industry for applications to third generation wireless systems.This paper aims to design and develop an advanced antennas testbed to serve as a common reference for testing adaptive antenna arrays and signal combining algorithms, as well as complete systems. A flexible suite of off line processing software should be written using matlab to perform system calibration, test bed initialization, data acquisition control, data storage/transfer, off line signal processing and analysis and graph plotting. The goal of this paper is to develop low complexity smart antenna structures for 3G systems. The emphasis will be laid on ease of implementation in a multichannel / multi-user environment. A smart antenna test bed will be developed, and various state-of-the-art DSP structures and algorithms will be investigated.Facing the soaring demand for mobile communications, the use of smart antenna arrays in mobile communications systems to exploit spatial diversity to further improve spectral efficiency has recently received considerable attention. Basically, a smart antenna array comprises a number of antenna elements combined via a beamforming network (amplitude and phase control network). Some of the benefits that can be achieved by using SAS (Smart Antenna System) include lower mobile terminal power consumption, range extension, ISI reduction, higher data rate support, and ease of integration into the existing base station system. In terms of economic benefits, adaptive antenna systems employed at base station, though increases the per base station cost, can increase coverage area of each cell site, thereby reducing the total system cost dramatically - often by more than 50% without compromising the system performance. The testbed can be employed to illustrate enhancement of system capacity and service quality in wireless communications.

Diversity in spatial scope of contrast adaptation among mouse retinal ganglion cells.

PubMed

Khani, Mohammad Hossein; Gollisch, Tim

2017-12-01

Retinal ganglion cells adapt to changes in visual contrast by adjusting their response kinetics and sensitivity. While much work has focused on the time scales of these adaptation processes, less is known about the spatial scale of contrast adaptation. For example, do small, localized contrast changes affect a cell's signal processing across its entire receptive field? Previous investigations have provided conflicting evidence, suggesting that contrast adaptation occurs either locally within subregions of a ganglion cell's receptive field or globally over the receptive field in its entirety. Here, we investigated the spatial extent of contrast adaptation in ganglion cells of the isolated mouse retina through multielectrode-array recordings. We applied visual stimuli so that ganglion cell receptive fields contained regions where the average contrast level changed periodically as well as regions with constant average contrast level. This allowed us to analyze temporal stimulus integration and sensitivity separately for stimulus regions with and without contrast changes. We found that the spatial scope of contrast adaptation depends strongly on cell identity, with some ganglion cells displaying clear local adaptation, whereas others, in particular large transient ganglion cells, adapted globally to contrast changes. Thus, the spatial scope of contrast adaptation in mouse retinal ganglion cells appears to be cell-type specific. This could reflect differences in mechanisms of contrast adaptation and may contribute to the functional diversity of different ganglion cell types. NEW & NOTEWORTHY Understanding whether adaptation of a neuron in a sensory system can occur locally inside the receptive field or whether it always globally affects the entire receptive field is important for understanding how the neuron processes complex sensory stimuli. For mouse retinal ganglion cells, we here show that both local and global contrast adaptation exist and that this diversity in spatial scope can contribute to the functional diversity of retinal ganglion cell types. Copyright © 2017 the American Physiological Society.

Diversity in spatial scope of contrast adaptation among mouse retinal ganglion cells

PubMed Central

Khani, Mohammad Hossein

2017-01-01

Retinal ganglion cells adapt to changes in visual contrast by adjusting their response kinetics and sensitivity. While much work has focused on the time scales of these adaptation processes, less is known about the spatial scale of contrast adaptation. For example, do small, localized contrast changes affect a cell’s signal processing across its entire receptive field? Previous investigations have provided conflicting evidence, suggesting that contrast adaptation occurs either locally within subregions of a ganglion cell’s receptive field or globally over the receptive field in its entirety. Here, we investigated the spatial extent of contrast adaptation in ganglion cells of the isolated mouse retina through multielectrode-array recordings. We applied visual stimuli so that ganglion cell receptive fields contained regions where the average contrast level changed periodically as well as regions with constant average contrast level. This allowed us to analyze temporal stimulus integration and sensitivity separately for stimulus regions with and without contrast changes. We found that the spatial scope of contrast adaptation depends strongly on cell identity, with some ganglion cells displaying clear local adaptation, whereas others, in particular large transient ganglion cells, adapted globally to contrast changes. Thus, the spatial scope of contrast adaptation in mouse retinal ganglion cells appears to be cell-type specific. This could reflect differences in mechanisms of contrast adaptation and may contribute to the functional diversity of different ganglion cell types. NEW & NOTEWORTHY Understanding whether adaptation of a neuron in a sensory system can occur locally inside the receptive field or whether it always globally affects the entire receptive field is important for understanding how the neuron processes complex sensory stimuli. For mouse retinal ganglion cells, we here show that both local and global contrast adaptation exist and that this diversity in spatial scope can contribute to the functional diversity of retinal ganglion cell types. PMID:28904106

Efficient block processing of long duration biotelemetric brain data for health care monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soumya, I.; Zia Ur Rahman, M., E-mail: mdzr-5@ieee.org; Rama Koti Reddy, D. V.

In real time clinical environment, the brain signals which doctor need to analyze are usually very long. Such a scenario can be made simple by partitioning the input signal into several blocks and applying signal conditioning. This paper presents various block based adaptive filter structures for obtaining high resolution electroencephalogram (EEG) signals, which estimate the deterministic components of the EEG signal by removing noise. To process these long duration signals, we propose Time domain Block Least Mean Square (TDBLMS) algorithm for brain signal enhancement. In order to improve filtering capability, we introduce normalization in the weight update recursion of TDBLMS,more » which results TD-B-normalized-least mean square (LMS). To increase accuracy and resolution in the proposed noise cancelers, we implement the time domain cancelers in frequency domain which results frequency domain TDBLMS and FD-B-Normalized-LMS. Finally, we have applied these algorithms on real EEG signals obtained from human using Emotive Epoc EEG recorder and compared their performance with the conventional LMS algorithm. The results show that the performance of the block based algorithms is superior to the LMS counter-parts in terms of signal to noise ratio, convergence rate, excess mean square error, misadjustment, and coherence.« less

Evolution of SH2 domains and phosphotyrosine signalling networks

PubMed Central

Liu, Bernard A.; Nash, Piers D.

2012-01-01

Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

Vestibular blueprint in early vertebrates.

PubMed

Straka, Hans; Baker, Robert

2013-11-19

Central vestibular neurons form identifiable subgroups within the boundaries of classically outlined octavolateral nuclei in primitive vertebrates that are distinct from those processing lateral line, electrosensory, and auditory signals. Each vestibular subgroup exhibits a particular morpho-physiological property that receives origin-specific sensory inputs from semicircular canal and otolith organs. Behaviorally characterized phenotypes send discrete axonal projections to extraocular, spinal, and cerebellar targets including other ipsi- and contralateral vestibular nuclei. The anatomical locations of vestibuloocular and vestibulospinal neurons correlate with genetically defined hindbrain compartments that are well conserved throughout vertebrate evolution though some variability exists in fossil and extant vertebrate species. The different vestibular subgroups exhibit a robust sensorimotor signal processing complemented with a high degree of vestibular and visual adaptive plasticity.

Optimized method for atmospheric signal reduction in irregular sampled InSAR time series assisted by external atmospheric information

NASA Astrophysics Data System (ADS)

Gong, W.; Meyer, F. J.

2013-12-01

It is well known that spatio-temporal the tropospheric phase signatures complicate the interpretation and detection of smaller magnitude deformation signals or unstudied motion fields. Several advanced time-series InSAR techniques were developed in the last decade that make assumptions about the stochastic properties of the signal components in interferometric phases to reduce atmospheric delay effects on surface deformation estimates. However, their need for large datasets to successfully separate the different phase contributions limits their performance if data is scarce and irregularly sampled. Limited SAR data coverage is true for many areas affected by geophysical deformation. This is either due to their low priority in mission programming, unfavorable ground coverage condition, or turbulent seasonal weather effects. In this paper, we present new adaptive atmospheric phase filtering algorithms that are specifically designed to reconstruct surface deformation signals from atmosphere-affected and irregularly sampled InSAR time series. The filters take advantage of auxiliary atmospheric delay information that is extracted from various sources, e.g. atmospheric weather models. They are embedded into a model-free Persistent Scatterer Interferometry (PSI) approach that was selected to accommodate non-linear deformation patterns that are often observed near volcanoes and earthquake zones. Two types of adaptive phase filters were developed that operate in the time dimension and separate atmosphere from deformation based on their different temporal correlation properties. Both filter types use the fact that atmospheric models can reliably predict the spatial statistics and signal power of atmospheric phase delay fields in order to automatically optimize the filter's shape parameters. In essence, both filter types will attempt to maximize the linear correlation between a-priori and the extracted atmospheric phase information. Topography-related phase components, orbit errors and the master atmospheric delays are first removed in a pre-processing step before the atmospheric filters are applied. The first adaptive filter type is using a filter kernel of Gaussian shape and is adaptively adjusting the width (defined in days) of this filter until the correlation of extracted and modeled atmospheric signal power is maximized. If atmospheric properties vary along the time series, this approach will lead to filter setting that are adapted to best reproduce atmospheric conditions at a certain observation epoch. Despite the superior performance of this first filter design, its Gaussian shape imposes non-physical relative weights onto acquisitions that ignore the known atmospheric noise in the data. Hence, in our second approach we are using atmospheric a-priori information to adaptively define the full shape of the atmospheric filter. For this process, we use a so-called normalized convolution (NC) approach that is often used in image reconstruction. Several NC designs will be presented in this paper and studied for relative performance. A cross-validation of all developed algorithms was done using both synthetic and real data. This validation showed designed filters are outperforming conventional filter methods that particularly useful for regions with limited data coverage or lack of a deformation field prior.

When noise is beneficial for sensory encoding: Noise adaptation can improve face processing.

PubMed

Menzel, Claudia; Hayn-Leichsenring, Gregor U; Redies, Christoph; Németh, Kornél; Kovács, Gyula

2017-10-01

The presence of noise usually impairs the processing of a stimulus. Here, we studied the effects of noise on face processing and show, for the first time, that adaptation to noise patterns has beneficial effects on face perception. We used noiseless faces that were either surrounded by random noise or presented on a uniform background as stimuli. In addition, the faces were either preceded by noise adaptors or not. Moreover, we varied the statistics of the noise so that its spectral slope either matched that of the faces or it was steeper or shallower. Results of parallel ERP recordings showed that the background noise reduces the amplitude of the face-evoked N170, indicating less intensive face processing. Adaptation to a noise pattern, however, led to reduced P1 and enhanced N170 amplitudes as well as to a better behavioral performance in two of the three noise conditions. This effect was also augmented by the presence of background noise around the target stimuli. Additionally, the spectral slope of the noise pattern affected the size of the P1, N170 and P2 amplitudes. We reason that the observed effects are due to the selective adaptation of noise-sensitive neurons present in the face-processing cortical areas, which may enhance the signal-to-noise-ratio. Copyright © 2017 Elsevier Inc. All rights reserved.

Constrained Adaptive Beamforming for Improved Contrast in Breast Ultrasound

DTIC Science & Technology

2008-06-01

Medical Imaging 2007: Ultrasonic Imaging and Signal Processing Proceedings, vol. 6513, San Diego , CA, Feb. 18, 2007. 12. Guenther, D.A., Walker...Transactions on, vol. 6, pp. 185-192, 1987. [23] A. P. Schachat, R. P. Murphy, and A. Patz, Medical Retina, vol. 2, 1 ed. St. Louis: The C. V. Mosby

Abscisic Acid and Abiotic Stress Tolerance in Crop Plants

PubMed Central

Sah, Saroj K.; Reddy, Kambham R.; Li, Jiaxu

2016-01-01

Abiotic stress is a primary threat to fulfill the demand of agricultural production to feed the world in coming decades. Plants reduce growth and development process during stress conditions, which ultimately affect the yield. In stress conditions, plants develop various stress mechanism to face the magnitude of stress challenges, although that is not enough to protect them. Therefore, many strategies have been used to produce abiotic stress tolerance crop plants, among them, abscisic acid (ABA) phytohormone engineering could be one of the methods of choice. ABA is an isoprenoid phytohormone, which regulates various physiological processes ranging from stomatal opening to protein storage and provides adaptation to many stresses like drought, salt, and cold stresses. ABA is also called an important messenger that acts as the signaling mediator for regulating the adaptive response of plants to different environmental stress conditions. In this review, we will discuss the role of ABA in response to abiotic stress at the molecular level and ABA signaling. The review also deals with the effect of ABA in respect to gene expression. PMID:27200044

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm.

PubMed

Qin, Qin; Li, Jianqing; Yue, Yinggao; Liu, Chengyu

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method.

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm

PubMed Central

Qin, Qin

2017-01-01

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MIT-BIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method. PMID:29104745

Principles for integrating reactive species into in vivo biological processes: Examples from exercise physiology.

PubMed

Margaritelis, Nikos V; Cobley, James N; Paschalis, Vassilis; Veskoukis, Aristidis S; Theodorou, Anastasios A; Kyparos, Antonios; Nikolaidis, Michalis G

2016-04-01

The equivocal role of reactive species and redox signaling in exercise responses and adaptations is an example clearly showing the inadequacy of current redox biology research to shed light on fundamental biological processes in vivo. Part of the answer probably relies on the extreme complexity of the in vivo redox biology and the limitations of the currently applied methodological and experimental tools. We propose six fundamental principles that should be considered in future studies to mechanistically link reactive species production to exercise responses or adaptations: 1) identify and quantify the reactive species, 2) determine the potential signaling properties of the reactive species, 3) detect the sources of reactive species, 4) locate the domain modified and verify the (ir)reversibility of post-translational modifications, 5) establish causality between redox and physiological measurements, 6) use selective and targeted antioxidants. Fulfilling these principles requires an idealized human experimental setting, which is certainly a utopia. Thus, researchers should choose to satisfy those principles, which, based on scientific evidence, are most critical for their specific research question. Copyright © 2015 Elsevier Inc. All rights reserved.

Light Signaling in Bud Outgrowth and Branching in Plants

PubMed Central

Leduc, Nathalie; Roman, Hanaé; Barbier, François; Péron, Thomas; Huché-Thélier, Lydie; Lothier, Jérémy; Demotes-Mainard, Sabine; Sakr, Soulaiman

2014-01-01

Branching determines the final shape of plants, which influences adaptation, survival and the visual quality of many species. It is an intricate process that includes bud outgrowth and shoot extension, and these in turn respond to environmental cues and light conditions. Light is a powerful environmental factor that impacts multiple processes throughout plant life. The molecular basis of the perception and transduction of the light signal within buds is poorly understood and undoubtedly requires to be further unravelled. This review is based on current knowledge on bud outgrowth-related mechanisms and light-mediated regulation of many physiological processes. It provides an extensive, though not exhaustive, overview of the findings related to this field. In parallel, it points to issues to be addressed in the near future. PMID:27135502

Design and Implementation of Multi-Input Adaptive Signal Extractions.

DTIC Science & Technology

1982-09-01

deflected gradient) algorithm requiring only N+ l multiplications per adaptation step. Additional quantization is introduced to eliminate all multiplications...noise cancellation for intermittent-signal applications," IEEE Trans. Information Theory, Vol. IT-26. Nov. 1980, pp. 746-750. 1-2 J. Kazakoff and W. A...cancellation," Proc. IEEE, July 1981, Vol. 69, pp. 846-847. *I-10 P. L . Kelly and W. A. Gardner, "Pilot-Directed Adaptive Signal Extraction," Dept. of

Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay.

PubMed

Tutsoy, Onder; Barkana, Duygun Erol; Tugal, Harun

2018-05-01

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Method and apparatus for telemetry adaptive bandwidth compression

NASA Technical Reports Server (NTRS)

Graham, Olin L.

1987-01-01

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176

Science, Technical Innovation and Applications in Bioacoustics: Summary of a Workshop

DTIC Science & Technology

2004-07-01

binaural processing have been neglected. From a signal-processing standpoint, we should avoid complex computational methods and instead use massively...design and/or build transducers or arrays with anywhere near the performance and, most importantly, environmental adaptability of animal binaural ...shell Small animal imaging Cardiac Imaging in Mice The Challenge Mouse heart • 7mm diameter • 8 beats /sec Mouse Heart L16-28MHzL5-10MHz Laptop

Spatial segregation of adaptation and predictive sensitization in retinal ganglion cells

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2014-01-01

Sensory systems change their sensitivity based upon recent stimuli to adjust their response range to the range of inputs, and to predict future sensory input. Here we report the presence of retinal ganglion cells that have antagonistic plasticity, showing central adaptation and peripheral sensitization. Ganglion cell responses were captured by a spatiotemporal model with independently adapting excitatory and inhibitory subunits, and sensitization requires GABAergic inhibition. Using a simple theory of signal detection we show that the sensitizing surround conforms to an optimal inference model that continually updates the prior signal probability. This indicates that small receptive field regions have dual functionality—to adapt to the local range of signals, but sensitize based upon the probability of the presence of that signal. Within this framework, we show that sensitization predicts the location of a nearby object, revealing prediction as a new functional role for adapting inhibition in the nervous system. PMID:23932000

Acute adaptation of the vestibuloocular reflex: signal processing by floccular and ventral parafloccular Purkinje cells.

PubMed

Hirata, Y; Highstein, S M

2001-05-01

The gain of the vertical vestibuloocular reflex (VVOR), defined as eye velocity/head velocity was adapted in squirrel monkeys by employing visual-vestibular mismatch stimuli. VVOR gain, measured in the dark, could be trained to values between 0.4 and 1.5. Single-unit activity of vertical zone Purkinje cells was recorded from the flocculus and ventral paraflocculus in alert squirrel monkeys before and during the gain change training. Our goal was to evaluate the site(s) of learning of the gain change. To aid in the evaluation, a model of the vertical optokinetic reflex (VOKR) and VVOR was constructed consisting of floccular and nonfloccular systems divided into subsystems based on the known anatomy and input and output parameters. Three kinds of input to floccular Purkinje cells via mossy fibers were explicitly described, namely vestibular, visual (retinal slip), and efference copy of eye movement. The characteristics of each subsystem (gain and phase) were identified at different VOR gains by reconstructing single-unit activity of Purkinje cells during VOKR and VVOR with multiple linear regression models consisting of sensory input and motor output signals. Model adequacy was checked by evaluating the residual following the regressions and by predicting Purkinje cells' activity during visual-vestibular mismatch paradigms. As a result, parallel changes in identified characteristics with VVOR adaptation were found in the prefloccular/floccular subsystem that conveys vestibular signals and in the nonfloccular subsystem that conveys vestibular signals, while no change was found in other subsystems, namely prefloccular/floccular subsystems conveying efference copy or visual signals, nonfloccular subsystem conveying visual signals, and postfloccular subsystem transforming Purkinje cell activity to eye movements. The result suggests multiple sites for VVOR motor learning including both flocculus and nonflocculus pathways. The gain change in the nonfloccular vestibular subsystem was in the correct direction to cause VOR gain adaptation while the change in the prefloccular/floccular vestibular subsystem was incorrect (anti-compensatory). This apparent incorrect directional change might serve to prevent instability of the VOR caused by positive feedback via the efference copy pathway.

Separation of Intercepted Multi-Radar Signals Based on Parameterized Time-Frequency Analysis

NASA Astrophysics Data System (ADS)

Lu, W. L.; Xie, J. W.; Wang, H. M.; Sheng, C.

2016-09-01

Modern radars use complex waveforms to obtain high detection performance and low probabilities of interception and identification. Signals intercepted from multiple radars overlap considerably in both the time and frequency domains and are difficult to separate with primary time parameters. Time-frequency analysis (TFA), as a key signal-processing tool, can provide better insight into the signal than conventional methods. In particular, among the various types of TFA, parameterized time-frequency analysis (PTFA) has shown great potential to investigate the time-frequency features of such non-stationary signals. In this paper, we propose a procedure for PTFA to separate overlapped radar signals; it includes five steps: initiation, parameterized time-frequency analysis, demodulating the signal of interest, adaptive filtering and recovering the signal. The effectiveness of the method was verified with simulated data and an intercepted radar signal received in a microwave laboratory. The results show that the proposed method has good performance and has potential in electronic reconnaissance applications, such as electronic intelligence, electronic warfare support measures, and radar warning.

[Detection of Weak Speech Signals from Strong Noise Background Based on Adaptive Stochastic Resonance].

PubMed

Lu, Huanhuan; Wang, Fuzhong; Zhang, Huichun

2016-04-01

Traditional speech detection methods regard the noise as a jamming signal to filter,but under the strong noise background,these methods lost part of the original speech signal while eliminating noise.Stochastic resonance can use noise energy to amplify the weak signal and suppress the noise.According to stochastic resonance theory,a new method based on adaptive stochastic resonance to extract weak speech signals is proposed.This method,combined with twice sampling,realizes the detection of weak speech signals from strong noise.The parameters of the systema,b are adjusted adaptively by evaluating the signal-to-noise ratio of the output signal,and then the weak speech signal is optimally detected.Experimental simulation analysis showed that under the background of strong noise,the output signal-to-noise ratio increased from the initial value-7dB to about 0.86 dB,with the gain of signalto-noise ratio is 7.86 dB.This method obviously raises the signal-to-noise ratio of the output speech signals,which gives a new idea to detect the weak speech signals in strong noise environment.

Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment.

PubMed

Yao, Yao; Storme, Veronique; Marchal, Kathleen; Van de Peer, Yves

2016-01-01

We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.

Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

PubMed Central

Yao, Yao; Storme, Veronique; Marchal, Kathleen

2016-01-01

We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population. PMID:28028477

CORDIC-based digital signal processing (DSP) element for adaptive signal processing

NASA Astrophysics Data System (ADS)

Bolstad, Gregory D.; Neeld, Kenneth B.

1995-04-01

The High Performance Adaptive Weight Computation (HAWC) processing element is a CORDIC based application specific DSP element that, when connected in a linear array, can perform extremely high throughput (100s of GFLOPS) matrix arithmetic operations on linear systems of equations in real time. In particular, it very efficiently performs the numerically intense computation of optimal least squares solutions for large, over-determined linear systems. Most techniques for computing solutions to these types of problems have used either a hard-wired, non-programmable systolic array approach, or more commonly, programmable DSP or microprocessor approaches. The custom logic methods can be efficient, but are generally inflexible. Approaches using multiple programmable generic DSP devices are very flexible, but suffer from poor efficiency and high computation latencies, primarily due to the large number of DSP devices that must be utilized to achieve the necessary arithmetic throughput. The HAWC processor is implemented as a highly optimized systolic array, yet retains some of the flexibility of a programmable data-flow system, allowing efficient implementation of algorithm variations. This provides flexible matrix processing capabilities that are one to three orders of magnitude less expensive and more dense than the current state of the art, and more importantly, allows a realizable solution to matrix processing problems that were previously considered impractical to physically implement. HAWC has direct applications in RADAR, SONAR, communications, and image processing, as well as in many other types of systems.

Auxin-BR Interaction Regulates Plant Growth and Development

PubMed Central

Tian, Huiyu; Lv, Bingsheng; Ding, Tingting; Bai, Mingyi; Ding, Zhaojun

2018-01-01

Plants develop a high flexibility to alter growth, development, and metabolism to adapt to the ever-changing environments. Multiple signaling pathways are involved in these processes and the molecular pathways to transduce various developmental signals are not linear but are interconnected by a complex network and even feedback mutually to achieve the final outcome. This review will focus on two important plant hormones, auxin and brassinosteroid (BR), based on the most recent progresses about these two hormone regulated plant growth and development in Arabidopsis, and highlight the cross-talks between these two phytohormones. PMID:29403511

Analysis of and Techniques for Adaptive Equalization for Underwater Acoustic Communication

DTIC Science & Technology

2011-09-01

used and in (b) an averaging window of 1000 samples is used. There was an overlap length of half the averaging window. The solid black line shows the ...array processing by constraining the signal covariance matrix to be realizable when the received signal was a sum of narrowband plane waves. Their goal...u0 −u0 v(u)vH(u)du. (4.4.9) A key part of the proof in [48] uses the Poincare separation theorem to show that the eigenvectors corresponding to the

In-Situ Wire Damage Detection System

NASA Technical Reports Server (NTRS)

Jolley, Scott T. (Inventor); Gibson, Tracy L. (Inventor); Medelius, Pedro J. (Inventor); Roberson, Luke B. (Inventor); Tate, Lanetra C. (Inventor); Smith, Trent M. (Inventor); Williams, Martha K. (Inventor)

2014-01-01

An in-situ system for detecting damage in an electrically conductive wire. The system includes a substrate at least partially covered by a layer of electrically conductive material forming a continuous or non-continuous electrically conductive layer connected to an electrical signal generator adapted to delivering electrical signals to the electrically conductive layer. Data is received and processed to identify damage to the substrate or electrically conductive layer. The electrically conductive material may include metalized carbon fibers, a thin metal coating, a conductive polymer, carbon nanotubes, metal nanoparticles or a combination thereof.

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 encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching this goal.

Evaluation of an adaptive traffic signal system : route 291 in Lee's Summit, Missouri.

DOT National Transportation Integrated Search

2010-03-01

An adaptive traffic signal system was installed on a 12-signal, 2.5-mi arterial in Lees Summit, Missouri in the Spring : of 2008. An evaluation of travel time, delay, number of stops, fuel consumption, and emissions was conducted, which : compared...

Development of agent-based on-line adaptive signal control (ASC) framework using connected vehicle (CV) technology.

DOT National Transportation Integrated Search

2016-04-01

In this study, we developed an adaptive signal control (ASC) framework for connected vehicles (CVs) using agent-based modeling technique. : The proposed framework consists of two types of agents: 1) vehicle agents (VAs); and 2) signal controller agen...

Dynamic goal states: adjusting cognitive control without conflict monitoring.

PubMed

Scherbaum, Stefan; Dshemuchadse, Maja; Ruge, Hannes; Goschke, Thomas

2012-10-15

A central topic in the cognitive sciences is how cognitive control is adjusted flexibly to changing environmental demands at different time scales to produce goal-oriented behavior. According to an influential account, the context-sensitive recruitment of cognitive control is mediated by a specialized conflict monitoring process that registers current conflict and signals the demand for enhanced control in subsequent trials. This view has been immensely successful not least due to supporting evidence from neuroimaging studies suggesting that the conflict monitoring function is localized within the anterior cingulate cortex (ACC) which, in turn, signals the demand for enhanced control to the prefrontal cortex (PFC). In this article, we propose an alternative model of the adaptive regulation of cognitive control based on multistable goal attractor network dynamics and adjustments of cognitive control within a conflict trial. Without incorporation of an explicit conflict monitoring module, the model mirrors behavior in conflict tasks accounting for effects of response congruency, sequential conflict adaptation, and proportion of incongruent trials. Importantly, the model also mirrors frequency tagged EEG data indicating continuous conflict adaptation and suggests a reinterpretation of the correlation between ACC and the PFC BOLD data reported in previous imaging studies. Together, our simulation data propose an alternative interpretation of both behavioral data as well as imaging data that have previously been interpreted in favor of a specialized conflict monitoring process in the ACC. Copyright © 2012 Elsevier Inc. All rights reserved.

A 5 Gb/s CMOS adaptive equalizer for serial link

NASA Astrophysics Data System (ADS)

Wu, Hongbing; Wang, Jingyu; Liu, Hongxia

2018-04-01

A 5 Gb/s adaptive equalizer with a new adaptation scheme is presented here by using 0.13 μm CMOS process. The circuit consists of the combination of equalizer amplifier, limiter amplifier and adaptation loop. The adaptive algorithm exploits both the low frequency gain loop and the equalizer loop to minimize the inter-symbol interference (ISI) for a variety of cable characteristics. In addition, an offset cancellation loop is used to alleviate the offset influence of the signal path. The adaptive equalizer core occupies an area of 0.3567 mm2 and consumes a power consumption of 81.7 mW with 1.8 V power supply. Experiment results demonstrate that the equalizer could compensate for a designed cable loss with 0.23 UI peak-to-peak jitter. Project supported by the National Natural Science Foundation of China (No. 61376099), the Foundation for Fundamental Research of China (No. JSZL2016110B003), and the Major Fundamental Research Program of Shaanxi (No. 2017ZDJC-26).

Independent component analysis algorithm FPGA design to perform real-time blind source separation

NASA Astrophysics Data System (ADS)

Meyer-Baese, Uwe; Odom, Crispin; Botella, Guillermo; Meyer-Baese, Anke

2015-05-01

The conditions that arise in the Cocktail Party Problem prevail across many fields creating a need for of Blind Source Separation. The need for BSS has become prevalent in several fields of work. These fields include array processing, communications, medical signal processing, and speech processing, wireless communication, audio, acoustics and biomedical engineering. The concept of the cocktail party problem and BSS led to the development of Independent Component Analysis (ICA) algorithms. ICA proves useful for applications needing real time signal processing. The goal of this research was to perform an extensive study on ability and efficiency of Independent Component Analysis algorithms to perform blind source separation on mixed signals in software and implementation in hardware with a Field Programmable Gate Array (FPGA). The Algebraic ICA (A-ICA), Fast ICA, and Equivariant Adaptive Separation via Independence (EASI) ICA were examined and compared. The best algorithm required the least complexity and fewest resources while effectively separating mixed sources. The best algorithm was the EASI algorithm. The EASI ICA was implemented on hardware with Field Programmable Gate Arrays (FPGA) to perform and analyze its performance in real time.

An ultra low energy biomedical signal processing system operating at near-threshold.

PubMed

Hulzink, J; Konijnenburg, M; Ashouei, M; Breeschoten, A; Berset, T; Huisken, J; Stuyt, J; de Groot, H; Barat, F; David, J; Van Ginderdeuren, J

2011-12-01

This paper presents a voltage-scalable digital signal processing system designed for the use in a wireless sensor node (WSN) for ambulatory monitoring of biomedical signals. To fulfill the requirements of ambulatory monitoring, power consumption, which directly translates to the WSN battery lifetime and size, must be kept as low as possible. The proposed processing platform is an event-driven system with resources to run applications with different degrees of complexity in an energy-aware way. The architecture uses effective system partitioning to enable duty cycling, single instruction multiple data (SIMD) instructions, power gating, voltage scaling, multiple clock domains, multiple voltage domains, and extensive clock gating. It provides an alternative processing platform where the power and performance can be scaled to adapt to the application need. A case study on a continuous wavelet transform (CWT)-based heart-beat detection shows that the platform not only preserves the sensitivity and positive predictivity of the algorithm but also achieves the lowest energy/sample for ElectroCardioGram (ECG) heart-beat detection publicly reported today.

A general method for assessing brain-computer interface performance and its limitations

NASA Astrophysics Data System (ADS)

Hill, N. Jeremy; Häuser, Ann-Katrin; Schalk, Gerwin

2014-04-01

Objective. When researchers evaluate brain-computer interface (BCI) systems, we want quantitative answers to questions such as: How good is the system’s performance? How good does it need to be? and: Is it capable of reaching the desired level in future? In response to the current lack of objective, quantitative, study-independent approaches, we introduce methods that help to address such questions. We identified three challenges: (I) the need for efficient measurement techniques that adapt rapidly and reliably to capture a wide range of performance levels; (II) the need to express results in a way that allows comparison between similar but non-identical tasks; (III) the need to measure the extent to which certain components of a BCI system (e.g. the signal processing pipeline) not only support BCI performance, but also potentially restrict the maximum level it can reach. Approach. For challenge (I), we developed an automatic staircase method that adjusted task difficulty adaptively along a single abstract axis. For challenge (II), we used the rate of information gain between two Bernoulli distributions: one reflecting the observed success rate, the other reflecting chance performance estimated by a matched random-walk method. This measure includes Wolpaw’s information transfer rate as a special case, but addresses the latter’s limitations including its restriction to item-selection tasks. To validate our approach and address challenge (III), we compared four healthy subjects’ performance using an EEG-based BCI, a ‘Direct Controller’ (a high-performance hardware input device), and a ‘Pseudo-BCI Controller’ (the same input device, but with control signals processed by the BCI signal processing pipeline). Main results. Our results confirm the repeatability and validity of our measures, and indicate that our BCI signal processing pipeline reduced attainable performance by about 33% (21 bits min-1). Significance. Our approach provides a flexible basis for evaluating BCI performance and its limitations, across a wide range of tasks and task difficulties.

Phase coherence adaptive processor for automatic signal detection and identification

NASA Astrophysics Data System (ADS)

Wagstaff, Ronald A.

2006-05-01

A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

Using a signal cancellation technique to assess adaptive directivity of hearing aids.

PubMed

Wu, Yu-Hsiang; Bentler, Ruth A

2007-07-01

The directivity of an adaptive directional microphone hearing aid (DMHA) cannot be assessed by the method that calls for presenting a "probe" signal from a single loudspeaker to the DMHA that moves to different angles. This method is invalid because the probe signal itself changes the polar pattern. This paper proposes a method for assessing the adaptive DMHA using a "jammer" signal, presented from a second loudspeaker rotating with the DMHA, that simulates a noise source and freezes the polar pattern. Measurement at each angle is obtained by two sequential recordings from the DMHA, one using an input of a probe and a jammer, and the other with an input of the same probe and a phase-inverted jammer. After canceling out the jammer, the remaining response to the probe signal can be used to assess the directivity. In this paper, the new method is evaluated by comparing responses from five adaptive DMHAs to different jammer intensities and locations. This method was shown to be an accurate and reliable way to assess the directivity of the adaptive DMHA in a high-intensity-jammer condition.

Noise screen for attitude control system

NASA Technical Reports Server (NTRS)

Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Hong, David P. (Inventor); Hirschberg, Philip C. (Inventor)

2002-01-01

An attitude control system comprising a controller and a noise screen device coupled to the controller. The controller is adapted to control an attitude of a vehicle carrying an actuator system that is adapted to pulse in metered bursts in order to generate a control torque to control the attitude of the vehicle in response to a control pulse. The noise screen device is adapted to generate a noise screen signal in response to the control pulse that is generated when an input attitude error signal exceeds a predetermined deadband attitude level. The noise screen signal comprises a decaying offset signal that when combined with the attitude error input signal results in a net attitude error input signal away from the predetermined deadband level to reduce further control pulse generation.

Parallel implementation of all-digital timing recovery for high-speed and real-time optical coherent receivers.

PubMed

Zhou, Xian; Chen, Xue

2011-05-09

The digital coherent receivers combine coherent detection with digital signal processing (DSP) to compensate for transmission impairments, and therefore are a promising candidate for future high-speed optical transmission system. However, the maximum symbol rate supported by such real-time receivers is limited by the processing rate of hardware. In order to cope with this difficulty, the parallel processing algorithms is imperative. In this paper, we propose a novel parallel digital timing recovery loop (PDTRL) based on our previous work. Furthermore, for increasing the dynamic dispersion tolerance range of receivers, we embed a parallel adaptive equalizer in the PDTRL. This parallel joint scheme (PJS) can be used to complete synchronization, equalization and polarization de-multiplexing simultaneously. Finally, we demonstrate that PDTRL and PJS allow the hardware to process 112 Gbit/s POLMUX-DQPSK signal at the hundreds MHz range. © 2011 Optical Society of America

Nonlinear system identification of smart structures under high impact loads

NASA Astrophysics Data System (ADS)

Sarp Arsava, Kemal; Kim, Yeesock; El-Korchi, Tahar; Park, Hyo Seon

2013-05-01

The main purpose of this paper is to develop numerical models for the prediction and analysis of the highly nonlinear behavior of integrated structure control systems subjected to high impact loading. A time-delayed adaptive neuro-fuzzy inference system (TANFIS) is proposed for modeling of the complex nonlinear behavior of smart structures equipped with magnetorheological (MR) dampers under high impact forces. Experimental studies are performed to generate sets of input and output data for training and validation of the TANFIS models. The high impact load and current signals are used as the input disturbance and control signals while the displacement and acceleration responses from the structure-MR damper system are used as the output signals. The benchmark adaptive neuro-fuzzy inference system (ANFIS) is used as a baseline. Comparisons of the trained TANFIS models with experimental results demonstrate that the TANFIS modeling framework is an effective way to capture nonlinear behavior of integrated structure-MR damper systems under high impact loading. In addition, the performance of the TANFIS model is much better than that of ANFIS in both the training and the validation processes.

Functional Optical Coherence Tomography Enables In Vivo Physiological Assessment of Retinal Rod and Cone Photoreceptors

PubMed Central

Zhang, Qiuxiang; Lu, Rongwen; Wang, Benquan; Messinger, Jeffrey D.; Curcio, Christine A.; Yao, Xincheng

2015-01-01

Transient intrinsic optical signal (IOS) changes have been observed in retinal photoreceptors, suggesting a unique biomarker for eye disease detection. However, clinical deployment of IOS imaging is challenging due to unclear IOS sources and limited signal-to-noise ratios (SNRs). Here, by developing high spatiotemporal resolution optical coherence tomography (OCT) and applying an adaptive algorithm for IOS processing, we were able to record robust IOSs from single-pass measurements. Transient IOSs, which might reflect an early stage of light phototransduction, are consistently observed in the photoreceptor outer segment almost immediately (<4 ms) after retinal stimulation. Comparative studies of dark- and light-adapted retinas have demonstrated the feasibility of functional OCT mapping of rod and cone photoreceptors, promising a new method for early disease detection and improved treatment of diseases such as age-related macular degeneration (AMD) and other eye diseases that can cause photoreceptor damage. PMID:25901915

Functional Optical Coherence Tomography Enables In Vivo Physiological Assessment of Retinal Rod and Cone Photoreceptors

NASA Astrophysics Data System (ADS)

Zhang, Qiuxiang; Lu, Rongwen; Wang, Benquan; Messinger, Jeffrey D.; Curcio, Christine A.; Yao, Xincheng

2015-04-01

Transient intrinsic optical signal (IOS) changes have been observed in retinal photoreceptors, suggesting a unique biomarker for eye disease detection. However, clinical deployment of IOS imaging is challenging due to unclear IOS sources and limited signal-to-noise ratios (SNRs). Here, by developing high spatiotemporal resolution optical coherence tomography (OCT) and applying an adaptive algorithm for IOS processing, we were able to record robust IOSs from single-pass measurements. Transient IOSs, which might reflect an early stage of light phototransduction, are consistently observed in the photoreceptor outer segment almost immediately (<4 ms) after retinal stimulation. Comparative studies of dark- and light-adapted retinas have demonstrated the feasibility of functional OCT mapping of rod and cone photoreceptors, promising a new method for early disease detection and improved treatment of diseases such as age-related macular degeneration (AMD) and other eye diseases that can cause photoreceptor damage.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Transcutaneous vagus nerve stimulation (tVNS) enhances conflict-triggered adjustment of cognitive control.

PubMed

Fischer, Rico; Ventura-Bort, Carlos; Hamm, Alfons; Weymar, Mathias

2018-04-24

Response conflicts play a prominent role in the flexible adaptation of behavior as they represent context-signals that indicate the necessity for the recruitment of cognitive control. Previous studies have highlighted the functional roles of the affectively aversive and arousing quality of the conflict signal in triggering the adaptation process. To further test this potential link with arousal, participants performed a response conflict task in two separate sessions with either transcutaneous vagus nerve stimulation (tVNS), which is assumed to activate the locus coeruleus-noradrenaline (LC-NE) system, or with neutral sham stimulation. In both sessions the N2 and P3 event-related potentials (ERP) were assessed. In line with previous findings, conflict interference, the N2 and P3 amplitude were reduced after conflict. Most importantly, this adaptation to conflict was enhanced under tVNS compared to sham stimulation for conflict interference and the N2 amplitude. No effect of tVNS on the P3 component was found. These findings suggest that tVNS increases behavioral and electrophysiological markers of adaptation to conflict. Results are discussed in the context of the potentially underlying LC-NE and other neuromodulatory (e.g., GABA) systems. The present findings add important pieces to the understanding of the neurophysiological mechanisms of conflict-triggered adjustment of cognitive control.

Adaptive virus detection using filament-coupled antibodies.

PubMed

Stone, Gregory P; Lin, Kelvin S; Haselton, Frederick R

2006-01-01

We recently reported the development of a filament-antibody recognition assay (FARA), in which the presence of virions in solution initiates the formation of enzyme-linked immunosorbent assay (ELISA)-like antibody complexes. The unique features of this assay are that processing is achieved by motion of a filament and that, in the presence of a virus, antibody-virus complexes are coupled to the filament at known locations. In this work, we combine the unique features of this assay with a 638-nm laser-based optical detector to enable adaptive control of virus detection. Integration of on-line fluorescence detection yields approximately a five-fold increase in signal-to-noise ratio (SNR) compared to the fluorescence detection method reported previously. A one-minute incubation with an M13K07 test virus is required to detect 10(10) virionsml, and 40 min was required to detect 10(8) virionsml. In tests of the components of an adaptive strategy, a 30-min virus (3.3 x 10(10) virionsml) incubation time, followed by repositioning the filament-captured virus either within the detecting antibody chamber, (20 microg ml) or within the virus chamber, found an increase in signal roughly proportional to the cumulative residence times in these chambers. Furthermore, cumulative fluorescence signals observed for a filament-captured virus after repeated positioning of the filament within the virus chamber are similar to those observed for a single long incubation time. The unique features of the FARA-like design combined with online optical detection to direct subsequent bioprocessing steps provides new flexibility for developing adaptive molecular recognition assays.

The remapping of space in motor learning and human-machine interfaces

PubMed Central

Mussa-Ivaldi, F.A.; Danziger, Z.

2009-01-01

Studies of motor adaptation to patterns of deterministic forces have revealed the ability of the motor control system to form and use predictive representations of the environment. One of the most fundamental elements of our environment is space itself. This article focuses on the notion of Euclidean space as it applies to common sensory motor experiences. Starting from the assumption that we interact with the world through a system of neural signals, we observe that these signals are not inherently endowed with metric properties of the ordinary Euclidean space. The ability of the nervous system to represent these properties depends on adaptive mechanisms that reconstruct the Euclidean metric from signals that are not Euclidean. Gaining access to these mechanisms will reveal the process by which the nervous system handles novel sophisticated coordinate transformation tasks, thus highlighting possible avenues to create functional human-machine interfaces that can make that task much easier. A set of experiments is presented that demonstrate the ability of the sensory-motor system to reorganize coordination in novel geometrical environments. In these environments multiple degrees of freedom of body motions are used to control the coordinates of a point in a two-dimensional Euclidean space. We discuss how practice leads to the acquisition of the metric properties of the controlled space. Methods of machine learning based on the reduction of reaching errors are tested as a means to facilitate learning by adaptively changing he map from body motions to controlled device. We discuss the relevance of the results to the development of adaptive human machine interfaces and optimal control. PMID:19665553

Speech as a breakthrough signaling resource in the cognitive evolution of biological complex adaptive systems.

PubMed

Mattei, Tobias A

2014-12-01

In self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.

Testing Convergent Evolution in Auditory Processing Genes between Echolocating Mammals and the Aye-Aye, a Percussive-Foraging Primate.

PubMed

Bankoff, Richard J; Jerjos, Michael; Hohman, Baily; Lauterbur, M Elise; Kistler, Logan; Perry, George H

2017-07-01

Several taxonomically distinct mammalian groups-certain microbats and cetaceans (e.g., dolphins)-share both morphological adaptations related to echolocation behavior and strong signatures of convergent evolution at the amino acid level across seven genes related to auditory processing. Aye-ayes (Daubentonia madagascariensis) are nocturnal lemurs with a specialized auditory processing system. Aye-ayes tap rapidly along the surfaces of trees, listening to reverberations to identify the mines of wood-boring insect larvae; this behavior has been hypothesized to functionally mimic echolocation. Here we investigated whether there are signals of convergence in auditory processing genes between aye-ayes and known mammalian echolocators. We developed a computational pipeline (Basic Exon Assembly Tool) that produces consensus sequences for regions of interest from shotgun genomic sequencing data for nonmodel organisms without requiring de novo genome assembly. We reconstructed complete coding region sequences for the seven convergent echolocating bat-dolphin genes for aye-ayes and another lemur. We compared sequences from these two lemurs in a phylogenetic framework with those of bat and dolphin echolocators and appropriate nonecholocating outgroups. Our analysis reaffirms the existence of amino acid convergence at these loci among echolocating bats and dolphins; some methods also detected signals of convergence between echolocating bats and both mice and elephants. However, we observed no significant signal of amino acid convergence between aye-ayes and echolocating bats and dolphins, suggesting that aye-aye tap-foraging auditory adaptations represent distinct evolutionary innovations. These results are also consistent with a developing consensus that convergent behavioral ecology does not reliably predict convergent molecular evolution. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Adapting the Stress Response: Viral Subversion of the mTOR Signaling Pathway

PubMed Central

Le Sage, Valerie; Cinti, Alessandro; Amorim, Raquel; Mouland, Andrew J.

2016-01-01

The mammalian target of rapamycin (mTOR) is a central regulator of gene expression, translation and various metabolic processes. Multiple extracellular (growth factors) and intracellular (energy status) molecular signals as well as a variety of stressors are integrated into the mTOR pathway. Viral infection is a significant stress that can activate, reduce or even suppress the mTOR signaling pathway. Consequently, viruses have evolved a plethora of different mechanisms to attack and co-opt the mTOR pathway in order to make the host cell a hospitable environment for replication. A more comprehensive knowledge of different viral interactions may provide fruitful targets for new antiviral drugs. PMID:27231932

Matrikine and matricellular regulators of EGF Receptor signaling on cancer cell migration and invasion

PubMed Central

Grahovac, Jelena; Wells, Alan

2014-01-01

SYNOPSIS Cancer invasion is a complex process requiring, among other events, extensive remodeling of the extracellular matrix including deposition of pro-migratory and pro-proliferative moieties. In recent years it has been described that while invading through matrices cancer cells can change shape and adapt their migration strategies depending on the microenvironmental context. Although intracellular signaling pathways governing the mesenchymal to amoeboid migration shift and vice versa have been mostly elucidated, the extracellular signals promoting these shifts are largely unknown. In this review we summarize findings that point to matrikines that bind specifically to the EGF receptor as matricellular molecules that enable cancer cell migrational plasticity and promote invasion. PMID:24247562

Recognition of digital characteristics based new improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Meng; Xu, Guoqiang; Lin, Zihao

2017-08-01

In the field of digital signal processing, Estimating the characteristics of signal modulation parameters is an significant research direction. The paper determines the set of eigenvalue which can show the difference of the digital signal modulation based on the deep research of the new improved genetic algorithm. Firstly take them as the best gene pool; secondly, The best gene pool will be changed in the genetic evolvement by selecting, overlapping and eliminating each other; Finally, Adapting the strategy of futher enhance competition and punishment to more optimizer the gene pool and ensure each generation are of high quality gene. The simulation results show that this method not only has the global convergence, stability and faster convergence speed.

The Plant Target of Rapamycin Kinase: A connecTOR between Sulfur and Growth.

PubMed

Forzani, Céline; Turqueto Duarte, Gustavo; Meyer, Christian

2018-06-01

Sulfur is an essential macronutrient for plants that is incorporated into sulfur-containing amino acids or metabolites crucial for plant growth and stress adaptation. A recent publication shows a connection between sulfur sensing, growth processes, and the conserved eukaryotic target of rapamycin (TOR) kinase signaling pathway. Copyright © 2018 Elsevier Ltd. All rights reserved.

3-D Signal Processing in a Computer Vision System

Treesearch

Dongping Zhu; Richard W. Conners; Philip A. Araman

1991-01-01

This paper discusses the problem of 3-dimensional image filtering in a computer vision system that would locate and identify internal structural failure. In particular, a 2-dimensional adaptive filter proposed by Unser has been extended to 3-dimension. In conjunction with segmentation and labeling, the new filter has been used in the computer vision system to...

Development of High Data Rate Acoustic Multiple-Input/Multiple-Output Modems

DTIC Science & Technology

2015-09-30

communication capabilities of underwater platforms and facilitate real-time adaptive operations in the ocean. OBJECTIVES The ...signaling at the transmitter and low-complexity time reversal processing at the receiver. APPROACH Underwater acoustic (UWA) communication is useful...digital communications in shallow water environments. The advancement has direct impacts on defense appliations since underwater acoustic modems

Wavelet domain image restoration with adaptive edge-preserving regularization.

PubMed

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

NASA Technical Reports Server (NTRS)

Salazar, George A. (Inventor); Haynes, Dena S. (Inventor); Sommers, Marc J. (Inventor)

1998-01-01

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

Glucose and phytohormone interplay in controlling root directional growth in Arabidopsis.

PubMed

Singh, Manjul; Gupta, Aditi; Laxmi, Ashverya

2014-01-01

Sensing and responding toward gravity vector is a complicated and multistep process. Gravity is a constant factor feeding plants with reliable information for the spatial orientation of their organs. Auxin, cytokinin, ethylene and BRs have been the most explored hormones in relation to gravitropism. We have previously shown that glucose (Glc) could promote brassinosteroid (BR) signaling thereby inducing changes in root directional growth. Auxin signaling and polar transport components are also involved in Glc induced changes in root directional growth. Here, we provide evidence for involvement of cytokinin and ethylene signaling components in regulation of root directional growth downstream to Glc and BR. Altogether, Glc mediated change in root direction is an adaptive feature which is a result of a collaborative effort integrating phytohormonal signaling cues.

Environmental Electrophiles: Protein Adducts, Modulation of Redox Signaling, and Interaction with Persulfides/Polysulfides.

PubMed

Kumagai, Yoshito; Abiko, Yumi

2017-01-17

Included among the many environmental electrophiles are aromatic hydrocarbon quinones formed during combustion of gasoline, crotonaldehyde in tobacco smoke, methylmercury accumulated in fish, cadmium contaminated in rice, and acrylamide in baked foods. These electrophiles can modify nucleophilic functions such as cysteine residues in proteins forming adducts and in the process activate cellular redox signal transduction pathways such as kinases and transcription factors. However, higher concentrations of electrophiles disrupt such signaling by nonselective covalent modification of cellular proteins. Persulfide/polysulfides produced by various enzymes appear to capture environmental electrophiles because of the formation of their sulfur adducts without electrophilicity. We therefore speculate that persulfide/polysulfides are candidates for the regulation of redox signal transduction pathways (e.g., cell survival, cell proliferation, and adaptive response) and toxicity during exposure to environmental electrophiles.

Redox-mediated signal transduction by cardiovascular Nox NADPH oxidases.

PubMed

Brandes, Ralf P; Weissmann, Norbert; Schröder, Katrin

2014-08-01

The only known function of the Nox family of NADPH oxidases is the production of reactive oxygen species (ROS). Some Nox enzymes show high tissue-specific expression and the ROS locally produced are required for synthesis of hormones or tissue components. In the cardiovascular system, Nox enzymes are low abundant and function as redox-modulators. By reacting with thiols, nitric oxide (NO) or trace metals, Nox-derived ROS elicit a plethora of cellular responses required for physiological growth factor signaling and the induction and adaptation to pathological processes. The interactions of Nox-derived ROS with signaling elements in the cardiovascular system are highly diverse and will be detailed in this article, which is part of a Special Issue entitled "Redox Signalling in the Cardiovascular System". Copyright © 2014 Elsevier Ltd. All rights reserved.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

PubMed

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

2015-11-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal

PubMed Central

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D.; Hubbi, Basil; Liu, Xuan

2015-01-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue. PMID:26600996

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

On the role of dimensionality and sample size for unstructured and structured covariance matrix estimation

NASA Technical Reports Server (NTRS)

Morgera, S. D.; Cooper, D. B.

1976-01-01

The experimental observation that a surprisingly small sample size vis-a-vis dimension is needed to achieve good signal-to-interference ratio (SIR) performance with an adaptive predetection filter is explained. The adaptive filter requires estimates as obtained by a recursive stochastic algorithm of the inverse of the filter input data covariance matrix. The SIR performance with sample size is compared for the situations where the covariance matrix estimates are of unstructured (generalized) form and of structured (finite Toeplitz) form; the latter case is consistent with weak stationarity of the input data stochastic process.

Digital Audio Signal Processing and Nde: AN Unlikely but Valuable Partnership

NASA Astrophysics Data System (ADS)

Gaydecki, Patrick

2008-02-01

In the Digital Signal Processing (DSP) group, within the School of Electrical and Electronic Engineering at The University of Manchester, research is conducted into two seemingly distinct and disparate subjects: instrumentation for nondestructive evaluation, and DSP systems & algorithms for digital audio. We have often found that many of the hardware systems and algorithms employed to recover, extract or enhance audio signals may also be applied to signals provided by ultrasonic or magnetic NDE instruments. Furthermore, modern DSP hardware is so fast (typically performing hundreds of millions of operations per second), that much of the processing and signal reconstruction may be performed in real time. Here, we describe some of the hardware systems we have developed, together with algorithms that can be implemented both in real time and offline. A next generation system has now been designed, which incorporates a processor operating at 0.55 Giga MMACS, six input and eight output analogue channels, digital input/output in the form of S/PDIF, a JTAG and a USB interface. The software allows the user, with no knowledge of filter theory or programming, to design and run standard or arbitrary FIR, IIR and adaptive filters. Using audio as a vehicle, we can demonstrate the remarkable properties of modern reconstruction algorithms when used in conjunction with such hardware; applications in NDE include signal enhancement and recovery in acoustic, ultrasonic, magnetic and eddy current modalities.

[Signal reception and processing by the retina].

PubMed

Eysel, U

2007-01-01

Phototransduction occurs in the retina, which, as an outsourced part of the brain, fulfills important tasks in neuronal processing for image analysis relevant to perception. Interlinked biochemical cycles with immense amplification factors transform the electromagnetic waves of light into neuronal activity, and photochemical adaptation allows adjustment to light intensities of over more than 10 logarithmic units. Beginning with its dual system of photoreceptors with highly sensible rods and a color sensitive cone system, the retina, with between 50 and 100 main cell types, is characterized by complex neuronal circuits. The resulting center-surround antagonism of the receptive fields serves, amongst other things, to amplify intensity and color contrasts. Specialized ganglion cell types give rise to parallel signaling pathways into the higher visual centers of the brain.

Low-complexity camera digital signal imaging for video document projection system

NASA Astrophysics Data System (ADS)

Hsia, Shih-Chang; Tsai, Po-Shien

2011-04-01

We present high-performance and low-complexity algorithms for real-time camera imaging applications. The main functions of the proposed camera digital signal processing (DSP) involve color interpolation, white balance, adaptive binary processing, auto gain control, and edge and color enhancement for video projection systems. A series of simulations demonstrate that the proposed method can achieve good image quality while keeping computation cost and memory requirements low. On the basis of the proposed algorithms, the cost-effective hardware core is developed using Verilog HDL. The prototype chip has been verified with one low-cost programmable device. The real-time camera system can achieve 1270 × 792 resolution with the combination of extra components and can demonstrate each DSP function.

Concepts for on-board satellite image registration. Volume 3: Impact of VLSI/VHSIC on satellite on-board signal processing

NASA Technical Reports Server (NTRS)

Aanstoos, J. V.; Snyder, W. E.

1981-01-01

Anticipated major advances in integrated circuit technology in the near future are described as well as their impact on satellite onboard signal processing systems. Dramatic improvements in chip density, speed, power consumption, and system reliability are expected from very large scale integration. Improvements are expected from very large scale integration enable more intelligence to be placed on remote sensing platforms in space, meeting the goals of NASA's information adaptive system concept, a major component of the NASA End-to-End Data System program. A forecast of VLSI technological advances is presented, including a description of the Defense Department's very high speed integrated circuit program, a seven-year research and development effort.

Monitoring temperatures in coal conversion and combustion processes via ultrasound

NASA Astrophysics Data System (ADS)

Gopalsami, N.; Raptis, A. C.; Mulcahey, T. P.

1980-02-01

The state of the art of instrumentation for monitoring temperatures in coal conversion and combustion systems is examined. The instrumentation types studied include thermocouples, radiation pyrometers, and acoustical thermometers. The capabilities and limitations of each type are reviewed. A feasibility study of the ultrasonic thermometry is described. A mathematical model of a pulse-echo ultrasonic temperature measurement system is developed using linear system theory. The mathematical model lends itself to the adaptation of generalized correlation techniques for the estimation of propagation delays. Computer simulations are made to test the efficacy of the signal processing techniques for noise-free as well as noisy signals. Based on the theoretical study, acoustic techniques to measure temperature in reactors and combustors are feasible.

Detecting determinism from point processes.

PubMed

Andrzejak, Ralph G; Mormann, Florian; Kreuz, Thomas

2014-12-01

The detection of a nonrandom structure from experimental data can be crucial for the classification, understanding, and interpretation of the generating process. We here introduce a rank-based nonlinear predictability score to detect determinism from point process data. Thanks to its modular nature, this approach can be adapted to whatever signature in the data one considers indicative of deterministic structure. After validating our approach using point process signals from deterministic and stochastic model dynamics, we show an application to neuronal spike trains recorded in the brain of an epilepsy patient. While we illustrate our approach in the context of temporal point processes, it can be readily applied to spatial point processes as well.

Design of an LVDS to USB3.0 adapter and application

NASA Astrophysics Data System (ADS)

Qiu, Xiaohan; Wang, Yu; Zhao, Xin; Chang, Zhen; Zhang, Quan; Tian, Yuze; Zhang, Yunyi; Lin, Fang; Liu, Wenqing

2016-10-01

USB 3.0 specification was published in 2008. With the development of technology, USB 3.0 is becoming popular. LVDS(Low Voltage Differential Signaling) to USB 3.0 Adapter connects the communication port of spectrometer device and the USB 3.0 port of a computer, and converts the output of an LVDS spectrometer device data to USB. In order to adapt to the changing and developing of technology, LVDS to USB3.0 Adapter was designed and developed based on LVDS to USB2.0 Adapter. The CYUSB3014, a new generation of USB bus interface chip produced by Cypress and conforming to USB3.0 communication protocol, utilizes GPIF-II (GPIF, general programmable interface) to connect the FPGA and increases effective communication speed to 2Gbps. Therefore, the adapter, based on USB3.0 technology, is able to connect more spectrometers to single computer and provides technical basis for the development of the higher speed industrial camera. This article describes the design and development process of the LVDS to USB3.0 adapter.

Asynchronous signal-dependent non-uniform sampler

NASA Astrophysics Data System (ADS)

Can-Cimino, Azime; Chaparro, Luis F.; Sejdić, Ervin

2014-05-01

Analog sparse signals resulting from biomedical and sensing network applications are typically non-stationary with frequency-varying spectra. By ignoring that the maximum frequency of their spectra is changing, uniform sampling of sparse signals collects unnecessary samples in quiescent segments of the signal. A more appropriate sampling approach would be signal-dependent. Moreover, in many of these applications power consumption and analog processing are issues of great importance that need to be considered. In this paper we present a signal dependent non-uniform sampler that uses a Modified Asynchronous Sigma Delta Modulator which consumes low-power and can be processed using analog procedures. Using Prolate Spheroidal Wave Functions (PSWF) interpolation of the original signal is performed, thus giving an asynchronous analog to digital and digital to analog conversion. Stable solutions are obtained by using modulated PSWFs functions. The advantage of the adapted asynchronous sampler is that range of frequencies of the sparse signal is taken into account avoiding aliasing. Moreover, it requires saving only the zero-crossing times of the non-uniform samples, or their differences, and the reconstruction can be done using their quantized values and a PSWF-based interpolation. The range of frequencies analyzed can be changed and the sampler can be implemented as a bank of filters for unknown range of frequencies. The performance of the proposed algorithm is illustrated with an electroencephalogram (EEG) signal.

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Reconfigurable signal processor designs for advanced digital array radar systems

NASA Astrophysics Data System (ADS)

Suarez, Hernan; Zhang, Yan (Rockee); Yu, Xining

2017-05-01

The new challenges originated from Digital Array Radar (DAR) demands a new generation of reconfigurable backend processor in the system. The new FPGA devices can support much higher speed, more bandwidth and processing capabilities for the need of digital Line Replaceable Unit (LRU). This study focuses on using the latest Altera and Xilinx devices in an adaptive beamforming processor. The field reprogrammable RF devices from Analog Devices are used as analog front end transceivers. Different from other existing Software-Defined Radio transceivers on the market, this processor is designed for distributed adaptive beamforming in a networked environment. The following aspects of the novel radar processor will be presented: (1) A new system-on-chip architecture based on Altera's devices and adaptive processing module, especially for the adaptive beamforming and pulse compression, will be introduced, (2) Successful implementation of generation 2 serial RapidIO data links on FPGA, which supports VITA-49 radio packet format for large distributed DAR processing. (3) Demonstration of the feasibility and capabilities of the processor in a Micro-TCA based, SRIO switching backplane to support multichannel beamforming in real-time. (4) Application of this processor in ongoing radar system development projects, including OU's dual-polarized digital array radar, the planned new cylindrical array radars, and future airborne radars.

Real-time alkali monitoring system

DOEpatents

Goff, David R.; Romanosky, Robert R.; Hensel, Peter

1990-01-01

A fiber optics based optical emission line monitoring system is provided in which selected spectral emission lines, such as the sodium emission line, may be detected in the presence of interfering background radiation. A combustion flame is fed by a diverted portion of a process stream and the common end of a bifurcated or quadfurcated fiber optic light guide is adapted to collect light from the flame. The light is guided through the branches of the fiber optic cable to bandpass filters, one of which is adapted to each of the branches of the fiber optic light guide. The bandpass filters are centered at wavelengths corresponding to the emission lines to be detected and two separate filters are required for each species being detected. The first filter has a bandwidth of about 3 nms and the second filter has a bandwidth of about 10 nms. Light detectors are located to view the light passing through the bandpass filters and amplifiers are connected to receive signals from the light detectors. The amplifier corresponding to the bandpass filter having the narrower bandwidth is preset to scale the signal by a factor equal to the ratio of the wide and narrow bandwidths of the bandpass filters. This scaling produces a scaled signal from which the difference between the scaled signal on the other signal can be calculated to produce a signal having an amplitude directly proportional to the concentration of the species of interest and independent of background radiation.

System and method for adaptively deskewing parallel data signals relative to a clock

DOEpatents

Jenkins, Philip Nord; Cornett, Frank N.

2006-04-18

A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. Each of the plurality of delayed signals is compared to a reference signal to detect changes in the skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in the detected skew.

Adaptive and Innate Transforming Growth Factor β Signaling Impact Herpes Simplex Virus 1 Latency and Reactivation▿

PubMed Central

Allen, Sariah J.; Mott, Kevin R.; Wechsler, Steven L.; Flavell, Richard A.; Town, Terrence; Ghiasi, Homayon

2011-01-01

Innate and adaptive immunity play important protective roles by combating herpes simplex virus 1 (HSV-1) infection. Transforming growth factor β (TGF-β) is a key negative cytokine regulator of both innate and adaptive immune responses. Yet, it is unknown whether TGF-β signaling in either immune compartment impacts HSV-1 replication and latency. We undertook genetic approaches to address these issues by infecting two different dominant negative TGF-β receptor type II transgenic mouse lines. These mice have specific TGF-β signaling blockades in either T cells or innate cells. Mice were ocularly infected with HSV-1 to evaluate the effects of restricted innate or adaptive TGF-β signaling during acute and latent infections. Limiting innate cell but not T cell TGF-β signaling reduced virus replication in the eyes of infected mice. On the other hand, blocking TGF-β signaling in either innate cells or T cells resulted in decreased latency in the trigeminal ganglia of infected mice. Furthermore, inhibiting TGF-β signaling in T cells reduced cell lysis and leukocyte infiltration in corneas and trigeminal ganglia during primary HSV-1 infection of mice. These findings strongly suggest that TGF-β signaling, which generally functions to dampen immune responses, results in increased HSV-1 latency. PMID:21880769

Adaptive interference cancel filter for evoked potential using high-order cumulants.

PubMed

Lin, Bor-Shyh; Lin, Bor-Shing; Chong, Fok-Ching; Lai, Feipei

2004-01-01

This paper is to present evoked potential (EP) processing using adaptive interference cancel (AIC) filter with second and high order cumulants. In conventional ensemble averaging method, people have to conduct repetitively experiments to record the required data. Recently, the use of AIC structure with second statistics in processing EP has proved more efficiency than traditional averaging method, but it is sensitive to both of the reference signal statistics and the choice of step size. Thus, we proposed higher order statistics-based AIC method to improve these disadvantages. This study was experimented in somatosensory EP corrupted with EEG. Gradient type algorithm is used in AIC method. Comparisons with AIC filter on second, third, fourth order statistics are also presented in this paper. We observed that AIC filter with third order statistics has better convergent performance for EP processing and is not sensitive to the selection of step size and reference input.

Attractive Serial Dependence in the Absence of an Explicit Task.

PubMed

Fornaciai, Michele; Park, Joonkoo

2018-03-01

Attractive serial dependence refers to an adaptive change in the representation of sensory information, whereby a current stimulus appears to be similar to a previous one. The nature of this phenomenon is controversial, however, as serial dependence could arise from biased perceptual representations or from biased traces of working memory representation at a decisional stage. Here, we demonstrated a neural signature of serial dependence in numerosity perception emerging early in the visual processing stream even in the absence of an explicit task. Furthermore, a psychophysical experiment revealed that numerosity perception is biased by a previously presented stimulus in an attractive way, not by repulsive adaptation. These results suggest that serial dependence is a perceptual phenomenon starting from early levels of visual processing and occurring independently from a decision process, which is consistent with the view that these biases smooth out noise from neural signals to establish perceptual continuity.

System and method for adaptively deskewing parallel data signals relative to a clock

DOEpatents

Jenkins, Philip Nord [Eau Claire, WI; Cornett, Frank N [Chippewa Falls, WI

2008-10-07

A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in detected skew.

System and method for adaptively deskewing parallel data signals relative to a clock

DOEpatents

Jenkins, Philip Nord [Redwood Shores, CA; Cornett, Frank N [Chippewa Falls, WI

2011-10-04

A system and method of reducing skew between a plurality of signals transmitted with a transmit clock is described. Skew is detected between the received transmit clock and each of received data signals. Delay is added to the clock or to one or more of the plurality of data signals to compensate for the detected skew. The delay added to each of the plurality of delayed signals is updated to adapt to changes in detected skew.

A new chaotic communication scheme based on adaptive synchronization.

PubMed

Xiang-Jun, Wu

2006-12-01

A new chaotic communication scheme using adaptive synchronization technique of two unified chaotic systems is proposed. Different from the existing secure communication methods, the transmitted signal is modulated into the parameter of chaotic systems. The adaptive synchronization technique is used to synchronize two identical chaotic systems embedded in the transmitter and the receiver. It is assumed that the parameter of the receiver system is unknown. Based on the Lyapunov stability theory, an adaptive control law is derived to make the states of two identical unified chaotic systems with unknown system parameters asymptotically synchronized; thus the parameter of the receiver system is identified. Then the recovery of the original information signal in the receiver is successfully achieved on the basis of the estimated parameter. It is noticed that the time required for recovering the information signal and the accuracy of the recovered signal very sensitively depends on the frequency of the information signal. Numerical results have verified the effectiveness of the proposed scheme.

O-Linked-N-Acetylglucosamine Cycling and Insulin Signaling Are Required for the Glucose Stress Response in Caenorhabditis elegans

PubMed Central

Mondoux, Michelle A.; Love, Dona C.; Ghosh, Salil K.; Fukushige, Tetsunari; Bond, Michelle; Weerasinghe, Gayani R.; Hanover, John A.; Krause, Michael W.

2011-01-01

In a variety of organisms, including worms, flies, and mammals, glucose homeostasis is maintained by insulin-like signaling in a robust network of opposing and complementary signaling pathways. The hexosamine signaling pathway, terminating in O-linked-N-acetylglucosamine (O-GlcNAc) cycling, is a key sensor of nutrient status and has been genetically linked to the regulation of insulin signaling in Caenorhabditis elegans. Here we demonstrate that O-GlcNAc cycling and insulin signaling are both essential components of the C. elegans response to glucose stress. A number of insulin-dependent processes were found to be sensitive to glucose stress, including fertility, reproductive timing, and dauer formation, yet each of these differed in their threshold of sensitivity to glucose excess. Our findings suggest that O-GlcNAc cycling and insulin signaling are both required for a robust and adaptable response to glucose stress, but these two pathways show complex and interdependent roles in the maintenance of glucose–insulin homeostasis. PMID:21441213

Extraction of fetal ECG signal by an improved method using extended Kalman smoother framework from single channel abdominal ECG signal.

PubMed

Panigrahy, D; Sahu, P K

2017-03-01

This paper proposes a five-stage based methodology to extract the fetal electrocardiogram (FECG) from the single channel abdominal ECG using differential evolution (DE) algorithm, extended Kalman smoother (EKS) and adaptive neuro fuzzy inference system (ANFIS) framework. The heart rate of the fetus can easily be detected after estimation of the fetal ECG signal. The abdominal ECG signal contains fetal ECG signal, maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary. The pre-processing stage is used to remove the noise from the abdominal ECG signal. The EKS framework is used to estimate the maternal ECG signal from the abdominal ECG signal. The optimized parameters of the maternal ECG components are required to develop the state and measurement equation of the EKS framework. These optimized maternal ECG parameters are selected by the differential evolution algorithm. The relationship between the maternal ECG signal and the available maternal ECG component in the abdominal ECG signal is nonlinear. To estimate the actual maternal ECG component present in the abdominal ECG signal and also to recognize this nonlinear relationship the ANFIS is used. Inputs to the ANFIS framework are the output of EKS and the pre-processed abdominal ECG signal. The fetal ECG signal is computed by subtracting the output of ANFIS from the pre-processed abdominal ECG signal. Non-invasive fetal ECG database and set A of 2013 physionet/computing in cardiology challenge database (PCDB) are used for validation of the proposed methodology. The proposed methodology shows a sensitivity of 94.21%, accuracy of 90.66%, and positive predictive value of 96.05% from the non-invasive fetal ECG database. The proposed methodology also shows a sensitivity of 91.47%, accuracy of 84.89%, and positive predictive value of 92.18% from the set A of PCDB.

Simulations for Improved Imaging of Faint Objects at Maui Space Surveillance Site

NASA Astrophysics Data System (ADS)

Holmes, R.; Roggemann, M.; Werth, M.; Lucas, J.; Thompson, D.

A detailed wave-optics simulation is used in conjunction with advanced post-processing algorithms to explore the trade space between image post-processing and adaptive optics for improved imaging of low signal-to-noise ratio (SNR) targets. Target-based guidestars are required for imaging of most active Earth-orbiting satellites because of restrictions on using laser-backscatter-based guidestars in the direction of such objects. With such target-based guidestars and Maui conditions, it is found that significant reductions in adaptive optics actuator and subaperture density can result in improved imaging of fainter objects. Simulation indicates that elimination of adaptive optics produces sub-optimal results for all of the faint-object cases considered. This research was developed with funding from the Defense Advanced Research Projects Agency (DARPA). The views, opinions, and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government.

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation.

PubMed

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C; Wong, Willy; Daskalakis, Zafiris J; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research.

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation

PubMed Central

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C.; Wong, Willy; Daskalakis, Zafiris J.; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research. PMID:27774054

Adaptive plasticity in speech perception: Effects of external information and internal predictions.

PubMed

Guediche, Sara; Fiez, Julie A; Holt, Lori L

2016-07-01

When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g., written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through (a) the availability of explicit external disambiguating information via the presence or absence of postresponse orthographic information paired with a repetition of the degraded stimulus, and (b) the accuracy of internally generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Adaptive plasticity in speech perception: effects of external information and internal predictions

PubMed Central

Guediche, Sara; Fiez, Julie A.; Holt, Lori L.

2016-01-01

When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g. written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through 1) the availability of explicit external disambiguating information via the presence or absence of post-response orthographic information paired with a repetition of the degraded stimulus, and 2) the accuracy of internally-generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally-generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information. PMID:26854531

Src homology 2-domain containing leukocyte-specific phosphoprotein of 76 kDa is mandatory for TCR-mediated inside-out signaling, but dispensable for CXCR4-mediated LFA-1 activation, adhesion, and migration of T cells.

PubMed

Horn, Jessica; Wang, Xiaoqian; Reichardt, Peter; Stradal, Theresia E; Warnecke, Nicole; Simeoni, Luca; Gunzer, Matthias; Yablonski, Deborah; Schraven, Burkhart; Kliche, Stefanie

2009-11-01

Engagement of the TCR or of chemokine receptors such as CXCR4 induces adhesion and migration of T cells via so-called inside-out signaling pathways. The molecular processes underlying inside-out signaling events are as yet not completely understood. In this study, we show that TCR- and CXCR4-mediated activation of integrins critically depends on the membrane recruitment of the adhesion- and degranulation-promoting adapter protein (ADAP)/Src kinase-associated phosphoprotein of 55 kDa (SKAP55)/Rap1-interacting adapter protein (RIAM)/Rap1 module. We further demonstrate that the Src homology 2 domain containing leukocyte-specific phosphoprotein of 76 kDa (SLP76) is crucial for TCR-mediated inside-out signaling and T cell/APC interaction. Besides facilitating membrane recruitment of ADAP, SKAP55, and RIAM, SLP76 regulates TCR-mediated inside-out signaling by controlling the activation of Rap1 as well as Rac-mediated actin polymerization. Surprisingly, however, SLP76 is not mandatory for CXCR4-mediated inside-out signaling. Indeed, both CXCR4-induced T cell adhesion and migration are not affected by loss of SLP76. Moreover, after CXCR4 stimulation, the ADAP/SKAP55/RIAM/Rap1 module is recruited to the plasma membrane independently of SLP76. Collectively, our data indicate a differential requirement for SLP76 in TCR- vs CXCR4-mediated inside-out signaling pathways regulating T cell adhesion and migration.

Machine learning based Intelligent cognitive network using fog computing

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

Mechanical signaling in reproductive tissues: mechanisms and importance.

PubMed

Jorge, Soledad; Chang, Sydney; Barzilai, Joshua J; Leppert, Phyllis; Segars, James H

2014-09-01

The organs of the female reproductive system are among the most dynamic tissues in the human body, undergoing repeated cycles of growth and involution from puberty through menopause. To achieve such impressive plasticity, reproductive tissues must respond not only to soluble signals (hormones, growth factors, and cytokines) but also to physical cues (mechanical forces and osmotic stress) as well. Here, we review the mechanisms underlying the process of mechanotransduction-how signals are conveyed from the extracellular matrix that surrounds the cells of reproductive tissues to the downstream molecules and signaling pathways that coordinate the cellular adaptive response to external forces. Our objective was to examine how mechanical forces contribute significantly to physiological functions and pathogenesis in reproductive tissues. We highlight how widespread diseases of the reproductive tract, from preterm labor to tumors of the uterus and breast, result from an impairment in mechanical signaling. © The Author(s) 2014.

Plant response to gravity: towards a biosystems view of root gravitropism

NASA Astrophysics Data System (ADS)

Palme, Klaus; Volkmann, Dieter; Bennett, Malcolm J.; Gausepohl, Heinrich

2005-10-01

Plants are sessile organisms that originated and evolved in Earth's environment. They monitor a wide range of disparate external and internal signals and compute appropriate developmental responses. How do plant cells process these myriad signals into an appropriate response? How do they integrate these signals to reach a finely balanced decision on how to grow, how to determine the direction of growth and how to develop their organs to exploit the environment? As plant responses are generally irreversible growth responses, their signalling systems must compute each developmental decision with extreme care. One stimulus to which plants are continuously exposed is the gravity vector. Gravity affects adaptive growth responses that reorient organs towards light and nutrient resources. The MAP team was established by ESA to study in the model plant Arabidopsis thaliana the role of the hormone auxin in gravity-mediated growth control. Another goal was to dissect gravity perception and gravity signal transduction pathways.