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Leaky-FXlms algorithm: Stochastic analysis for Gaussian data and secondary path modeling error

IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING 2005年第6期13卷 1217-1230页

作者： Tobias, OJ Seara, R Univ Fed Santa Catarina Dept Elect Engn LINSE Circuits & Signal Proc Lab Florianopolis SC Brazil

This paper presents a stochastic analysis of the leaky filtered-X least-mean-square (LFXlms) algorithm. The version with leakage of the adaptive algorithm is used in practical implementations aiming to reduce undesirable effects due to numerical errors in finite-precision machines, overload of the secondary source, among others. Based on new analysis assumptions, instead of the ordinary independence theory frequently used in classical lms analysis, an analytical model for the first and second moments of the adaptive filter weights has been derived. In addition, the proposed theoretical models consider the situation in which the secondary path is imperfectly modeled. Experimental results demonstrate the accuracy of the proposed model as compared with the classical analysis.

关键词： active noise/vibration control leaky filtered-X lms algorithm lms algorithm

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A New Formula to Compute the Nlms algorithm at a Computational Complexity of O(2N)

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2019年第11期E102A卷 1545-1549页

作者： Nishiyama, Kiyoshi Sunohara, Masahiro Hiruma, Nobuhiko Iwate Univ Fac Sci & Engn Dept Syst Innovat Engn Morioka Iwate 0208551 Japan Rion Co Ltd Kokubunji Tokyo 1858533 Japan

The least mean squares (lms) algorithm has been widely used for adaptive filtering because of easily implementing at a computational complexity of O(2N) where N is the number of taps. The drawback of the lms algorithm is that its performance is sensitive to the scaling of the input. The normalized lms (Nlms) algorithm solves this problem on the lms algorithm by normalizing with the sliding-window power of the input;however, this normalization increases the computational cost to O(3N) per iteration. In this work, we derive a new formula to strictly perform the Nlms algorithm at a computational complexity of O(2N), that is referred to as the C-Nlms algorithm. The derivation of the C-Nlms algorithm uses the H-infinity framework presented previously by one of the authors for creating a unified view of adaptive filtering algorithms. The validity of the C-Nlms algorithm is verified using simulations.

关键词： Nlms algorithm lms algorithm adaptive filter H-infinity filter fast H-infinity filter system identification

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Modified lms and Nlms algorithms with non-negative weights

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SIGNAL PROCESSING 2024年 223卷

作者： Bershad, Neil J. Bermudez, Jose C. M. Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA USA Univ Fed Santa Catarina Dept Elect & Elect Engn Florianopolis SC Brazil

Non -negative constraints arise in certain system identification problems when the systems to be identified have only positive coefficients. This paper studies the stochastic behavior of modified lms and Nlms algorithms, modified so as to only allow adaptation with positive coefficients. The mean and second moment behavior of these algorithms are analyzed for Gaussian inputs. Excellent agreement is demonstrated between the theory and Monte Carlo simulations for the lms algorithm.

关键词： Adaptive filters Analysis lms algorithm Stochastic algorithms

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DSP implementation of the Fxlms algorithm for active noise control Texas instruments TSM320C6713DSK 2

DSP implementation of the FxLMS algorithm for active noise c...

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Automatic Control (CCAC), 2015 IEEE 2nd Colombian Conference on Automatic Control

作者： Garcia, Mauricio Patino, Diego Quintana, Ricardo Pontificia Univ Javeriana Dept Elect Engn Bogota Colombia

ISBN: (纸本)9781467393058

In this work it is presented a DSP card implementation method of the Fxlms single channel algorithm for active noise control (ANC). The ANC technique uses the superposition principle to attenuate acoustical noise. It is presented some simulating and experimental results of the lms and Fxlms algorithms. The signals used in the ANC are several low frequency tones and a broadband sound signal (air compressor), which is a machine widely used in industrial applications. The experiments are carried out in an enclosure (control room of approximately 36 cubic meters of volume).

关键词： component system identification lms algorithm Fxlms algorithm active noise control Matlab Simulink adaptive filtering FIR filters secondary path estimation transfer function adaptive algorithm impulse response FIT white noise

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A variable step-size lms adaptive filtering algorithm for speech denoising in VoIP

A variable step-size LMS adaptive filtering algorithm for sp...

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2017 3rd International Conference on Computational Systems and Communications(ICCSC 2017)

作者： Hongyu Chen College of Information Engineering Zhejiang University of Technology

There is a contradiction between convergence speed and steady-state error in the lms algorithm. When the step size factor is too large, the convergence speed is fast, but the error is larger. Otherwise, the reverse. In view of this contradiction, based on the original lms algorithm, consider from the correlation of the signal itself, has proposed a variable step size lms algorithm based on DCT transform. This algorithm combined with the original DCT-lms algorithm, through the introduction of Lorentzian function to achieve the change of step size factor, take full advantage of the relevant capacity of the DCT transform and Lorentzian function of the fast convergence ability. Simulation results show that the proposed algorithm has better convergence performance than the traditional adaptive filtering algorithm and DCT-lms algorithm, and has better steady state error.

关键词： Adaptive filtering Lorentzian function DCT transform lms algorithm

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Systolic design of frequency-domain block lms adaptive digital filters

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COMPUTERS & ELECTRICAL ENGINEERING 1998年第3-4期24卷 263-275页

作者： Alwan, NAS Al-Hashemy, BAR Univ Baghdad Coll Engn Dept Elect Engn Baghdad Iraq

Adaptive filtering in the frequency domain can be achieved by Fourier transformation of the input signal and independent weighting of the contents of each frequency bin. In certain applications, filtering in the frequency domain results in great improvements in convergence rate over the conventional time-domain adaptive filtering. In this paper, the use of word-level systolic arrays to implement frequency-domain adaptive filters based on the complex least mean square (I,MS) algorithm is described, The transform employed is the discrete Fourier transform (DFT). The proposed architecture operates on a block-by-block basis and makes use of the parallelism inherent in the computational problem under consideration. The input and output data flow sequentially and continuously into and out of the systolic arrays at the system clock rate. During each clock period, processing elements of three different types operate in parallel. The most computationally demanding among them performs only three consecutive multiplications and two addition/subtractions per clock period thereby allowing a very high throughput and very fast block signal processing to be achieved at the expense of a delay of 2L + 1 samples between the input and the output, L being the block size. (C) 1998 Elsevier Science Ltd. All rights reserved.

关键词： adaptive signal processing frequency-domain adaptive filters lms algorithm VLSI systolic arrays

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A Variable Step-Size lms Adaptive Filtering algorithm Based on Error Feedback

A Variable Step-Size LMS Adaptive Filtering Algorithm Based ...

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2013教育技术与信息系统国际会议

作者： Fengchun Wang Jiyan Du Institute of UAV Army Officer Academy

In order to solve the problem of lms algorithm, a new variable step-size lms algorithm is studied. The algorithm is based on the sigmoid function which builds the non-linear functional relationship between step and error. By introducing the error feedback strategy to adjust the parameters adaptively, the algorithm solves the problem of setting parameters in the function. Compared with other algorithms, simulation results show that the algorithm performs perfect at convergence rate and steady-state error with a better applicability.

关键词： lms algorithm Adaptive Filtering Convergence Rate Steady-state Error

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Application of New lms Adaptive Filtering algorithm with Variable Step Size in Adaptive Echo Cancellation

Application of New LMS Adaptive Filtering Algorithm with Var...

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2017 17th IEEE International Conference on Communication Technology (ICCT 2017)

作者： Zhang Yuan Xi Songtao Nanjing College of Information Technology Nanjing Research Institute of Electronics Technology

This paper presents a new variable step size lms（Least-Mean-Square） adaptive filtering algorithm in adaptive echo cancellation. This step size algorithm builds a nonlinear function relationship between the step-size parameter and the error signal. Theoretical analysis and computer simulations show that convergence rate can be improved than the former by the proposed algorithm. The new algorithm has good performance. It is applied in the filtering process of adaptive echo cancellation. The filtering effect is good.

关键词： adaptive filter variable step size adaptive filtering algorithm lms algorithm convergence speed adaptive echo canceller

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Performance of Rlms algorithm in Adaptive Array Beam Forming

Performance of RLMS Algorithm in Adaptive Array Beam Forming

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11th IEEE Singapore International Conference on Communication Systems

作者： Srar, Jalal Abdulsayed Chung, Kah-Seng Curtin Univ Technol Dept Elect & Comp Engn Perth WA Australia

ISBN: (纸本)9781424424238

This paper examines the performance of an adaptive linear array employing the new Rlms algorithm, which consists of a recursive least square (RLS) section followed by a least mean square (lms) section. The performance measures used are output and input signal-to-interference plus noise ratios (SINR), side lobe level (SLL), and Delta SINRo, as a function of the direction of arrival of the interfering signal. Computer simulation results show that the performance of Rlms is superior to either the RLS or lms based on these measures, particularly when operating with low input SINR.

关键词： RLS algorithm lms algorithm Rlms algorithm adaptive antenna array beam forming

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FEATURE lms algorithmS

FEATURE LMS ALGORITHMS

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Paulo S. R. Diniz Hamed Yazdanpanah Markus V. S. Lima Universidade Federal do Rio de Janeiro DEE-DEL/Poli & PEE/COPPE/UFRJ P.O. Box 68504 Rio de Janeiro RJ 21941-972 Brazil

ISBN: (纸本)9781538646595

In recent years, there is a growing effort in the learning algorithms area to propose new strategies to detect and exploit sparsity in the model parameters. In many situations, the sparsity is hidden in the relations among these coefficients so that some suitable tools are required to reveal the potential sparsity. This work proposes a set of lms-type algorithms, collectively called Feature lms (F-lms) algorithms, setting forth a hidden feature of the unknown parameters, which ultimately would improve convergence speed and steady-state mean-squared error. The key idea is to apply linear transformations, by means of the so-called feature matrices, to reveal the sparsity hidden in the coefficient vector, followed by a sparsity-promoting penalty function to exploit such sparsity. Some F-lms algorithms for lowpass and highpass systems are also introduced by using simple feature matrices that require only trivial operations. Simulation results demonstrate that the proposed F-lms algorithms bring about several performance improvements whenever the hidden sparsity of the parameters is exposed.

关键词： adaptive filtering lms algorithm feature matrix lowpass system highpass system Least mean square algorithm adaptive filters Levamisole learning management system algorithms linear transformations Unknown parameter model parameters

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