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Identifying Time-Varying Neuromuscular System with a Recursive Least-Squares algorithm: a Monte-Carlo Simulation Study

Identifying Time-Varying Neuromuscular System with a Recursi...

引用

IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Olivari, Mario Nieuwenhuizen, Frank M. Buelthoff, Heinrich H. Pollini, Lorenzo Max Planck Inst Biol Cybernet Dept Human Percept Cognit & Action D-72012 Tubingen Germany Univ Pisa Fac Automat Engn Dipartimento Ingn Informaz I-56100 Pisa Italy Korea Univ Dept Brain & Cognit Engn Seoul South Korea

ISBN: (纸本)9781479938407

A human-centered design of haptic aids aims at tuning the force feedback based on the effect it has on human behavior. For this goal, a better understanding of the influence of haptic aids on the pilot neuromuscular response becomes crucial. In realistic scenarios, the neuromuscular response can continuously vary depending on many factors, such as environmental factors or pilot fatigue. This paper presents a method that online estimates time-varying neuromuscular dynamics during force-related tasks. This method is based on a Recursive Least Squares (rls) algorithm and assumes that the neuromuscular response can be approximated by a Finite Impulse Response filter. The reliability and the robustness of the method were investigated by performing a set of Monte-Carlo simulations with increasing level or remnant noise. Even with high level of remnant noise, the rls algorithm provided accurate estimates when the neuromuscular dynamics were constant or changed slowly. With instantaneous changes, the rls algorithm needed almost 8s to converge to a reliable estimate. These results seem to indicate that rls algorithm is a valid tool for estimating online time-varying admittance.

关键词： FIR filters Monte Carlo methods force feedback haptic interfaces least squares approximations medical signal processing neuromuscular stimulation Monte Carlo simulation rls algorithm environmental factors finite impulse response filter haptic aids human-centered design neuromuscular response pilot fatigue recursive least squares algorithm time-varying neuromuscular system Admittance Dynamics Force Haptic interfaces Heuristic algorithms Least squares approximations Neuromuscular

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Convex combination of adaptive filters with different tracking capabilities

Convex combination of adaptive filters with different tracki...

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32nd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Silva, Magno T. M. Nascimento, Vitor H. Univ Sao Paulo Escola Politecn Dept Elect Syst Engn BR-05508900 Sao Paulo Brazil

ISBN: (纸本)1424407281

Recently, an adaptive convex combination of two LMS (Least Mean-Square) filters was proposed and its tracking performance analyzed. Motivated by the performance of such scheme and by the differences between the tracking capabilities of the rls (Recursive Least-Squares) and LMS algorithms, we propose a convex combination of one LMS and one rls filter. The resulting combination should profit of the best tracking behavior of each component filter. A steady-state analysis via energy conservation relation is also presented for stationary and non-stationary environments.

关键词： adaptive filters convex combination energy conservation tracking analysis LMS algorithm rls algorithm

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Channel Prediction on the Downlink of Precoded Multiuser MIMO OFDM Systems Using the Set-Membership Affine Projection Filtering

Channel Prediction on the Downlink of Precoded Multiuser MIM...

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IEEE 74th Vehicular Technology Conference (VTC)

作者： Leite, Joao P. De Carvalho, Paulo Henrique P. Vieira, Robson D. Univ Brasilia Dept Elect Engn Campus Univ Darcy Ribeiro Brasilia DF Brazil Nokia Technol Inst INdt Brasilia DF Brazil

ISBN: (纸本)9781424483273

Multiuser MIMO (MU MIMO) communications have attracted considerable attention in the last years since these systems are able to offer the higher link capacity of MIMO systems as long as channel state information (CSI) is available at the transmitter, so that the spatial properties of the channel can be exploited by precoding. However, the time varying nature of the channel and other transmissions constraints may cause CSI to be outdated, degrading the performance of the system. Considering this scenario, channel prediction can provide up-to-date channel CSI and reduce the performance loss. This paper presents a channel predictor based on the set-membership affine projection (SM-AP) filtering as way to compensate the outdated CSI. A realistic standardized channel model is used to evaluate the influence of the proposed predictor on two classical precoding schemes of the MIMO broadcast channel of a multiuser scenario, namely zero-forcing vector perturbation. The performance of the predictor is compared to the well-known adaptive algorithms normalized least mean squares (NLMS) and recursive least squares (rls). Simulation results show that the SM-AP predictor has lower computational cost and superior performance when compared to the classical algorithms.

关键词： CSI MIMO MIMO broadcast channel MIMO communication MU MIMO communication NLMS algorithm OFDM Prediction algorithms rls algorithm SM-AP filtering Transmitting antennas Vectors Wireless communication adaptive algorithm affine transforms broadcast channels c

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PERFORMANCE ANALYSIS OF RECURSIVE LEAST MODULI algorithm FOR FAST CONVERGENT AND ROBUST ADAPTIVE FILTERS

PERFORMANCE ANALYSIS OF RECURSIVE LEAST MODULI ALGORITHM FOR...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Koike, Shin'ichi

ISBN: (纸本)9781424423538

This paper derives a new adaptation algorithm named recursive least moduli (RLM) algorithm that combines least mean modulus (LMM) algorithm for complex-domain adaptive filters with recursive estimation of the inverse covariance matrix of the filter reference input. The RLM algorithm achieves significant improvement in the filter convergence speed of the LMM algorithm with a strongly correlated filter reference input, while it preserves robustness of the LMM algorithm against impulsive observation noise. Analysis of the RLM algorithm is developed for calculating transient and steady-state behavior of the filter convergence. Through experiment with simulations and theoretical calculations of the filter convergence for the RLM algorithm, we demonstrate its effectiveness in making adaptive filters fast convergent and robust in the presence of impulse noise. Good agreement between the simulations and theory proves the validity of the analysis.

关键词： rls algorithm covariance impulse noise

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Kalman filtering based dynamic OD matrix estimation and prediction for traffic systems

Kalman filtering based dynamic OD matrix estimation and pred...

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6th IEEE International Conference on Intelligent Transportation Systems

作者： Lin, Y Cai, YL Huang, YX Xian Jiaotong Univ Syst Engn Inst Sch Elect & Informat Engn Xian 710049 Peoples R China

ISBN: (纸本)0780381254

In this paper, a state space model is proposed so that the dynamic OD matrix can be estimated through the surveillance of flows and traveling time on links in a traffic network. To eliminate the influence of slow time-variant parameters, a Recursive Least Square (rls) algorithm is introduced to identify the system matrix online. Moreover, an analytical formula to calculate the key assignment matrix is presented. With the sequential Kalman Filtering method, the fast and real-time OD estimation and prediction algorithm is established. The algorithm is proven to be very effective and efficient with simulation test.

关键词： dynamic OD matrix estimation Kalman filtering rls algorithm

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Analysis of Convex Adaptive Structures and algorithms for Smart Antennas

Analysis of Convex Adaptive Structures and Algorithms for Sm...

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IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)

作者： Orozco-Tupacyupanqui, W. Carpio-Aleman, M. Nakano-Miyatake, M. Perez-Meana, H. Univ Politecn Salesiana Cuenca Ecuador Inst Politecn Nacl Mexico City DF Mexico

ISBN: (纸本)9781509037940

In this paper, two different filter structures for smart antennas based on a convex combination of independent transversal adaptive sub-filters are analyzed. The first structure combines the least-mean-squares (LMS) and the augmented complex least-mean-squares (ACLMS) algorithms, whereas the second one uses the recursive least-squares (rls) and the complex dual least-mean-squares (CDU-LMS) algorithms. The individual sub-filters are independently adapted using their own error signals, while the whole smart system is adapted by means of a convex stochastic gradient algorithm that generates an third independent error signal. The number of iterations required to reach convergence and the effects of the control parameter tau on the learning curve of the whole structure are studied. According to the simulation, these hybrid smart structures turned out to be more robust than a smart antenna that uses an unique adaptive filter. In general, both hybrid smart beamformers show to have a better filtering capacity than the standard LMS and rls smart antenna systems. General equations for the overall output and the radiation pattern have been developed for both variations.

关键词： Convex smart antennas adaptive algorithms hybrid smart structures LMS algorithm rls algorithm ACLMS algorithm CDU-LMS algorithm

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Adaptive Equalizer for DS-CDMA Multi-user Communication System Based on Laguerre Filter Structure with Sign-algorithm

Adaptive Equalizer for DS-CDMA Multi-user Communication Syst...

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International Conference on Information Science, Electronics and Electrical Engineering (ISEEE)

作者： Benjangkaprasert, C. Sirithummachak, P. King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok 10520 Thailand

ISBN: (纸本)9781479931972

In order to improve the performance of DS-CDMA receiver. This paper proposes a new adaptive equalizer that using a modified sign-algorithm based on Laguerre filter structure. The proposed algorithm combined the construction methods of Signum operator and the difference of an error signal. The performance of proposed equalizer was compared with the conventional equalizer using LMS and rls algorithms in multipath channel. This equalizer not only reduce the effected of ISI, MAI and AWGN but also minimizes the computational complexity when compared to the attractive rls algorithm and support the long impulse response system. The function detail and performance result of the proposed equalizer are described by computer simulation in terms of the bit error rate (BER).

关键词： DS-CDMA system Laguerre equalizer LMS algorithm rls algorithm sign-LMS algorithm

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On Learning Analysis of Neural Fuzzy Systems

On Learning Analysis of Neural Fuzzy Systems

引用

2010 IEEE World Congress on Computational Intelligence

作者： Yeh, Jen-Wei Su, Shun-Feng Jeng, Jin-Tsong Chen, Bor-Sen Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Natl Formosa Univ Dept Informat Engn Fuwei Taiwan Natl Tsing Hua Univ Dept Elect Engn Hsinchu Taiwan

ISBN: (纸本)9781424469208

Self-constructing neural fuzzy inference network (SONFIN) is a neural fuzzy system and owing to its structure learning capability, SONFIN has been demonstrated to have excellent learning performance. However, various parameters must be selected in the implementation of SONFIN. In this paper, the learning behavior of SONFIN is studied. First, the SONFIN system with different thresholds and variances are considered. Different selections will result in different rule numbers and membership function widths. Our experiment results indicate that when there are possibilities of overfitting, more rules may not always come up with better performance. Secondly, two different learning algorithms are considered;the backpropagation (BP) learning algorithm and the recursive least square (rls) algorithm. It can found that the learning of using rls is much faster than that of using BP as expected. However, it can be found that when overfitting may occur, BP can have better learning performance in terms of testing errors. Finally, the use of reset for the covariance matrix in the rls algorithm is investigated. From this primitive study, it can be found that the learning algorithms or some parameter selections may have both good effects in the testing performance and the training performance before the learning does not have significant overfitting. However, when the learning crosses this point, any selection is good for learning may bring bad effects on the testing performance.

关键词： rls algorithm SONFIN system backpropagation backpropagation learning algorithm covariance matrices covariance matrix fuzzy neural nets fuzzy reasoning learning analysis learning behavior learning performance least squares approximations membership function neural fuzzy system parameter selection recursive least square algorithm self-constructing neural fuzzy inference network testing performance training performance

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Performance Analysis of Active Noise Control Using Wavelet Denoising Technique

Performance Analysis of Active Noise Control Using Wavelet D...

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International Conference on Recent Advances in Microwave Theory and Applications

作者： Manikandan, S. Madheswaran, M. Purusothaman, T. King Coll Technol Namakkal Tamil Nadu India Govt Coll Technol Dept Comp Sci & Engn Coimbatore 64013 Tamil Nadu India Muthayammal Engn Coll Ctr Adv Res Dept Elect & Commun Engn Raipuram 637408 Tamil Nadu India

In this paper the noise control using wavelet based denoising has been carried out and the performance is compared with the well known adaptive control algorithms. The simulated results show that the wavelet based app... 详细信息

ISBN: (纸本)9781424426904

关键词： Active noise control SNR LMS algorithm rls algorithm wavelet denoising

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Double-Talk Detection Based on Enhanced Geigel algorithmfor Acoustic Echo Cancellation 6

Double-Talk Detection Based on Enhanced Geigel Algorithmfor ...

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6th International Conference on Control Engineering and Information Technology (CEIT)

作者： Benziane, Mourad Bouamar, Mohamed Makdir, Mouldi Univ Bouira Elect Engn Dept Lab LPM3E Bouira Algeria Univ Msila Lab Anal Signals & Syst LAAS Msila Algeria Univ Msila Elect Dept Msila Algeria

ISBN: (纸本)9781538676417

The role of a double talk detector (DTD) in acoustic echo cancelation (AEC) system is to detect the presence of near-end speech signal with the microphone signal and freeze the filter adaptation to avoid the adaptive algorithm divergence. This paper presents a DTD based on an enhanced Geigel algorithm where a modified form of decision variable is proposed. The aim is to improve the behavior of Geigel algorithm, evaluate performances of the proposed method, and compare it to conventional Geigel algorithm. Recursive Least Squares (rls) algorithm is used in this case as an adaptive filter which it requires a good DTD due to its fast convergence and its sensitivity to double talk situations.

关键词： Acoustic echo cancellation Adaptive filtering rls algorithm DTD Geigel algorithm

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