A generalized Lyapunov stability theory-based adaptive FIR filter algorithm with variable step sizes

Küçük Resim Yok

Tarih

2017

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer London Ltd

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

This paper presents a novel approach to Lyapunov stability theory-based adaptive filter (LAF) design. The proposed design is based on the minimization of the Euclidean norm of the difference weight vector under negative definiteness constraint defined over a novel linear Lyapunov function. The proposed fixed step size LAF (FSS-LAF) algorithm is first obtained by using the method of Lagrangian multipliers. The FSS-LAF satisfying asymptotic stability in the sense of Lyapunov provides a significant performance gain in the presence of a measurement noise. The stability of the FSS-LAF algorithm is also statistically analyzed in this study. Moreover, gradient variable step size (VSS) algorithms are adapted to the FSS-LAF algorithm to further enhance the performance for the first time in this paper. These VSS algorithms are Benveniste (BVSS), Mathews and Farhang-Ang (FVSS) algorithms. Simulation results on system identification problems show that the bounds of step size for the FSS-LAF algorithm are verified, and especially, the BVSS-LAF and FVSS-LAF algorithms provide a better trade-off between steady-state mean square deviation error and convergence rate than other proposed algorithms.

Açıklama

Anahtar Kelimeler

Adaptive filter, Lyapunov stability theory, Variable step size, System identification

Kaynak

Signal Image and Video Processing

WoS Q Değeri

Q3

Scopus Q Değeri

Q2

Cilt

11

Sayı

8

Künye