Open AccessProceedings Article
Stability of the LMS adaptive filter by means of a state equation
Vitor H. Nascimento,Ali H. Sayed +1 more
- Vol. 36, pp 242-251
About:
This article is published in Allerton Conference on Communication, Control, and Computing.The article was published on 1998-01-01 and is currently open access. It has received 2 citations till now. The article focuses on the topics: Adaptive filter.read more
Citations
More filters
Journal ArticleDOI
Transient analysis of adaptive filters with error nonlinearities
TL;DR: The paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities based on energy-conservation arguments and avoids the need for explicit recursions for the covariance matrix of the weight-error vector.
Journal ArticleDOI
On the learning mechanism of adaptive filters
Vitor H. Nascimento,Ali H. Sayed +1 more
TL;DR: The paper shows that even ensemble-average learning curves of single-tap LMS filters actually exhibit two distinct rates of convergence: one for the initial time instant and another, faster one, for later time instants.
References
More filters
Book
Matrix Analysis
Roger A. Horn,Charles R. Johnson +1 more
TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Book
Adaptive Signal Processing
Bernard Widrow,Samuel D. Stearns +1 more
TL;DR: This chapter discusses Adaptive Arrays and Adaptive Beamforming, as well as other Adaptive Algorithms and Structures, and discusses the Z-Transform in Adaptive Signal Processing.
Book ChapterDOI
Stationary and nonstationary learning characteristics of the LMS adaptive filter
TL;DR: It is shown that for stationary inputs the LMS adaptive algorithm, based on the method of steepest descent, approaches the theoretical limit of efficiency in terms of misadjustment and speed of adaptation when the eigenvalues of the input correlation matrix are equal or close in value.
Journal ArticleDOI
Analysis of recursive stochastic algorithms
TL;DR: It is shown how a deterministic differential equation can be associated with the algorithm and examples of applications of the results to problems in identification and adaptive control.