Proceedings ArticleDOI
Constrained adaptive LMS L-filters
Constantine Kotropoulos,Ioannis Pitas +1 more
- Vol. 3, pp 1665-1668
TLDR
Two novel adaptive nonlinear filter structures are proposed which are based on linear combinations of order statistics and have the ability to incorporate constraints imposed on coefficients in order to permit location invariant and unbiased estimation of a constant signal in the presence of additive white noise.Abstract:
Two novel adaptive nonlinear filter structures are proposed which are based on linear combinations of order statistics. These adaptive schemes are modifications of the standard LMS (least mean square) algorithm and have the ability to incorporate constraints imposed on coefficients in order to permit location invariant and unbiased estimation of a constant signal in the presence of additive white noise. The convergence properties of the proposed filters are considered. Both of them can adapt well to a variety of noise probability distributions ranging from short-tailed to long-tailed ones. Simulation examples are given. >read more
Citations
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Journal ArticleDOI
Robust L-estimation based forms of signal transforms and time-frequency representations
TL;DR: The L-estimation based signal transforms and time-frequency representations are introduced by considering the corresponding minimization problems in the Huber (1981, 1998) estimation theory to produce robust estimates of the non-noisy signal transforms.
Journal ArticleDOI
Introduction to Matrix Analysis. By Richard Bellman. 2nd Edition. Pp. xxiii, 403. £7·50. (McGraw-Hill.)
TL;DR: This book discusses Maximization, Minimization, and Motivation, which is concerned with the optimization of Symmetric Matrices, and its applications in Programming and Mathematical Economics.
Proceedings ArticleDOI
Application of adaptive order statistic filters in digital image/image sequence filtering
TL;DR: An application of adaptive order statistic filters in digital image filtering and in image sequence filtering is presented and it is proven that these filters adapt fairly well and remove effectively noise having various probability distributions.
Proceedings ArticleDOI
Low resolution method using adaptive LMS scheme for moving objects detection and tracking
TL;DR: A new model for adaptive filter with the least-mean-square (LMS) scheme to train the mask operation on low resolution images to ensure effective moving object detection and tracking in real-time.
References
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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
The algebraic eigenvalue problem
TL;DR: Theoretical background Perturbation theory Error analysis Solution of linear algebraic equations Hermitian matrices Reduction of a general matrix to condensed form Eigenvalues of matrices of condensed forms The LR and QR algorithms Iterative methods Bibliography.
Book
Introduction to Matrix Analysis
TL;DR: In this article, the Second Edition Preface is presented, where Maximization, Minimization, and Motivation are discussed, as well as a method of Hermite and Quadratic Form Index.
BookDOI
Nonlinear Digital Filters
TL;DR: This chapter discusses digital filters based on order statistics, Morphological image and signal processing, and Adaptive nonlinear filters.