Results 271 to 280 of about 919,633 (302)

A variable step size firefly algorithm for numerical optimization

Applied Mathematics and Computation, 2015
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Shuhao Yu, Shenglong Zhu, Yan Ma, Demei Mao   +3 more
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Fast implementation of evolutionary variable step size algorithm

Proceedings of IEEE International Conference on Evolutionary Computation, 2002
A new variable step size algorithm, namely the evolutionary variable step size (EVS) algorithm, has been recently proposed by the authors. The EVS algorithm employs the concept of evolution that the step size of the adaptive filter is evolved regularly in a controlled manner and the fittest step size candidate is chosen for the subsequent adaptation ...
C. Y. Ching, Sin Chun Ng, Shu Hung Leung
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Analysis and implementation of variable step size adaptive algorithms

IEEE Transactions on Signal Processing, 1993
Stochastic gradient adaptive filtering algorithms using variable step sizes are investigated. The variable-step-size algorithm improves the convergence rate while sacrificing little in steady-state error. Expressions describing the convergence of the mean and mean-squared values of the coefficients are developed and used to calculate the mean-square ...
Joseph B. Evans, Ping Xue 0004, Bede Liu
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New variable step size affine projection algorithms

2012 9th International Conference on Communications (COMM), 2012
In this paper, we propose new variable step size affine projection algorithms whose step sizes are adjusted according to the square of a time-averaging estimate of the autocorrelation of a priori and a posteriori errors. The proposed algorithms have fast convergence, robustness against near-end signal variations (including double-talk) and do not ...
Felix Albu, Constantin Paleologu, Silviu Ciochina   +2 more
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New Variable Step-size of l1-LMS Algorithm

Proceedings of the 8th International Conference on Signal Processing Systems, 2016
In order to quickenthe convergence rateand enhanceperformanceforanti-noise when identify the unknown coefficients of a sparse system. A variable step-size l1-LMS algorithm is proposed. In this paper, using current error and correlation value of errorto adjust step-size and zero-attracting part.
Sihai Guan, Zhi Li, Hairu Zhang
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Evaluation and design of variable step size adaptive algorithms

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
This paper presents a new methodology for evaluation and design of variable step size adaptive algorithms. The new methodology is based on a learning plane, which combines the evolutions of both the step size and the mean square error. It includes both transient and steady-state behaviors and can be used to compare performances of different algorithms ...
Cássio Guimarães Lopes, José Carlos Moreira Bermudez   +1 more
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Variable Step-Size LMS Algorithm for Fractal Signals

IEEE Transactions on Signal Processing, 2008
This paper presents a novel variable step-size LMS (VSLMS) algorithm for tracking signals from the Gaussian 1/fbeta family of fractal signals that are inherently nonstationary. The proposed algorithm differs from the existing VSLMS algorithms in the following ways: 1) it deals with a specific class of nonstationary signals, 2) it utilizes a nondiagonal
Anubha Gupta, Shiv Dutt Joshi
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A noise resilient variable step-size LMS algorithm

Signal Processing, 2008
This work presents a modified version of the variable step size (VSS) least mean square (LMS) algorithm originally proposed by Kwong and Johnston [IEEE Trans. Signal Process. 40(7) (July 1992) 1633-1642]. The performance of the new algorithm, called noise resilient variable step size (NRVSS), is less sensitive than VSS to the power of the measurement ...
Márcio Holsbach Costa, José Carlos M. Bermudez   +1 more
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A variable step size strategy for sparse system identification

10th International Multi-Conferences on Systems, Signals & Devices 2013 (SSD13), 2013
This work proposes a novel two-strategy approach to improve the performance of a recently-proposed (RZA-LMS) algorithm for sparse environments. The first and key strategy uses a novel h -norm-based variable step-size scheme to improve the performance of both the conventional and the RZA-LMS algorithms.
Muhammad O. Bin Saeed, Azzedine Zerguine
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A faster path-based algorithm with Barzilai-Borwein step size for solving stochastic traffic equilibrium models

European Journal of Operational Research, 2021
Muqing Du, Anthony Chen, Xiaoxia Ye
exaly