tailieunhanh - Báo cáo hóa học: " Performance Analysis of Adaptive Volterra Filters in the Finite-Alphabet Input Case"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Performance Analysis of Adaptive Volterra Filters in the Finite-Alphabet Input Case | EURASIP Journal on Applied Signal Processing 2004 17 2715-2722 2004 Hindawi Publishing Corporation Performance Analysis of Adaptive Volterra Filters in the Finite-Alphabet Input Case Hichem Besbes Ecole Superieure des Communications de Tunis Sup Com Ariana 2083 Tunisia Email Meriem Jaidane Ecole Nationale dTngenieurs de Tunis ENIT Le Belvedere 1002 Tunisia Email Jelel Ezzine Ecole Nationale dTngenieurs de Tunis ENIT Le Belvedere 1002 Tunisia Email Received 15 September 2003 Revised 21 May 2004 Recommended for Publication byFulvio Gini This paper deals with the analysis of adaptive Volterra filters driven by the LMS algorithm in the finite-alphabet inputs case. A tailored approach for the input context is presented and used to analyze the behavior of this nonlinear adaptive filter. Complete and rigorous mean square analysis is provided without any constraining independence assumption. Exact transient and steadystate performances expressed in terms of critical step size rate of transient decrease optimal step size excess mean square error in stationary mode and tracking nonstationarities are deduced. Keywords and phrases adaptive Volterra filters LMS algorithm time-varying channels finite-alphabet inputs exact performance analysis. 1. INTRODUCTION Adaptive systems have been extensively designed and implemented in the area of digital communications. In particular nonlinear adaptive filters such as adaptive Volterra filters have been used to model nonlinear channels encountered in satellite communications applications 1 2 . The nonlinearity is essentially due to the high-power amplifier used in the transmission 3 . When dealing with land-mobile satellite systems the channels are time varying and can be modeled by a general Mth-order Markovian model to describe these variations 4 . Hence to take into account the effect of the amplifier s nonlinearity and channel variations one can model the

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