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A Variable Step Size for Normalized Subband Adaptive Filters
IEEE Signal Processing Letters, 2012 A normalized subband adaptive filter algorithm uses a fixed step size, which is chosen as a trade-off between the steady-state error and the convergence rate. In this letter, a variable step size for normalized subband adaptive filters is derived by minimizing the mean-square deviation between the optimal weight vector and the estimated weight vector ...
Jeong, JJ, Koo, K, Choi, GT, Kim, SW
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The exponentiated convex variable step-size (ECVSS) algorithm
Signal Processing, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Corneliu Rusu, Colin F. N. Cowan
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A switched variable step size NLMS adaptive filter
Digital Signal Processing, 2020Abstract This paper studies the statistical behavior of a switched variable step size Normalized Least Mean Square adaptive filter. The purpose of the switching is to obtain a Normalized Least Mean Square adaptive filter combination with fast convergence and small steady-state mean-square weight deviation (MSD).
Neil J. Bershad, José C. M. Bermudez
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A variable step-size GMDF and its performance analysis
2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011Numerous time-domain variable step-size normalized least mean square algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This paper proposes a variable step-size control method for the generalized frequency-domain multidelay adaptive filter (GMDF), which is an attractive ...
Hsu Chang Huang, Junghsi Lee
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A simple variable step size LMS adaptive algorithm
International Journal of Circuit Theory and Applications, 2004AbstractA new LMS based variable step size adaptive algorithm is presented. The step size is incremented or decremented by a small positive value, whenever the instantaneous error is positive or negative, respectively. The algorithm is simple, robust and efficient. It is characterized by fast convergence and low steady state mean squared error.
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A new Variable step-Size strategy for adaptive networks
2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011Several algorithms have been developed over the last few years that utilize the distributed nature of an ad hoc wireless sensor network to estimate a certain parameter of interest. One such algorithm is called the diffusion least mean squares (DLMS) algorithm.
Muhammad Omer Bin Saeed +1 more
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A variable step-size sign algorithm for channel estimation
Signal Processing, 2014This paper proposes a new variable step-size sign algorithm (VSSA) for unknown channel estimation or system identification, and applies this algorithm to an environment containing two-component Gaussian mixture observation noise. The step size is adjusted using the gradient-based weighted average of the sign algorithm.
Yuan-Ping Li, Ta-Sung Lee, Bing-Fei Wu
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A New Robust Variable Step-Size NLMS Algorithm
IEEE Transactions on Signal Processing, 2008A new framework for designing robust adaptive filters is introduced. It is based on the optimization of a certain cost function subject to a time-dependent constraint on the norm of the filter update. Particularly, we present a robust variable step-size NLMS algorithm which optimizes the square of the a posteriori error.
Leonardo Rey Vega +3 more
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A variable step size algorithm with generate-and-evaluate function
Proceedings of ISCAS'95 - International Symposium on Circuits and Systems, 2002A new variable step-size algorithm which has a framework similar to the variable step (VS) adaptive filter algorithm given by R. W. Harris et al. (1986) is introduced. The methodology is to periodically invoke a generate-and-evaluate function during the adaptation.
Chi Yin Chung +3 more
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Variable Step Size Multistep Methods for Parabolic Problems
SIAM Journal on Numerical Analysis, 1982We study the error due to the discretization in time of a parabolic problem by variable step size multistep methods. It is proved that the multistep methods remain stable when the rate of step changing is not too great. Error estimates are obtained for A-stable and strongly $A(\Theta )$-stable methods $(0 \leqq \Theta \leqq {\pi / 2})$.
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