NDLI: Variants of Non-Negative Least-Mean-Square Algorithm and Convergence Analysis

Content Provider	IEEE Xplore Digital Library
Author	Jie Chen Richard, C. Bermudez, J.-C.M. Honeine, P.
Copyright Year	1991
Abstract	Due to the inherent physical characteristics of systems under investigation, non-negativity is one of the most interesting constraints that can usually be imposed on the parameters to estimate. The Non-Negative Least-Mean-Square algorithm (NNLMS) was proposed to adaptively find solutions of a typical Wiener filtering problem but with the side constraint that the resulting weights need to be non-negative. It has been shown to have good convergence properties. Nevertheless, certain practical applications may benefit from the use of modified versions of this algorithm. In this paper, we derive three variants of NNLMS. Each variant aims at improving the NNLMS performance regarding one of the following aspects: sensitivity of input power, unbalance of convergence rates for different weights and computational cost. We study the stochastic behavior of the adaptive weights for these three new algorithms for non-stationary environments. This study leads to analytical models to predict the first and second order moment behaviors of the weights for Gaussian inputs. Simulation results are presented to illustrate the performance of the new algorithms and the accuracy of the derived models.
Sponsorship	IEEE Signal Processing Society
Starting Page	3990
Ending Page	4005
Page Count	16
File Size	6890149
File Format	PDF
ISSN	1053587X
Volume Number	62
Issue Number	15
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing algorithms Convergence Algorithm design and analysis Prediction algorithms Vectors Equations Estimation sign-sign algorithm Adaptive signal processing convergence analysis exponential algorithm least-mean-square algorithms non-negativity constraints normalized algorithm
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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