The previous work for the filter design considers uncorrelated white measurement noise
disturbance. For more complex correlated noise disturbance, the conventional adaptive filter …

The present bibliography represents a comprehensive list of references on nonlinear system
identification and its applications in signal processing, communications, and biomedical …

Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
introduces engineers and researchers to the field of nonlinear adaptive system identification …

In recent years, a wealth of research has emerged addressing various aspects of mobile
communications signal processing. New applications and services are continually arising …

In this paper a novel class of nonlinear Hammerstein adaptive filters, consisting of a flexible
memory-less function followed by a linear combiner, is presented. The nonlinear function …

The problem of identification and tracking of time-varying nonlinear systems is addressed. In
particular, the Wiener system that consists of a dynamic time-varying linear part followed by …

Dynamic system modeling plays a crucial role in the development of techniques for
stationary and nonstationary signal processing. Due to the inherent physical characteristics …

The paper presents an improved statistical analysis of the least mean fourth (LMF) adaptive
algorithm behavior for a stationary Gaussian input. The analysis improves previous results in …

Recently, a novel class of nonlinear adaptive filters, called spline adaptive filters (SAFs), has
been introduced and demonstrated to be very effective in many practical applications. The …

This paper presents a statistical analysis of the filtered-X LMS algorithm behavior when the
secondary path (output of the adaptive filter) includes a nonlinear element. This system is of …