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

The aim of this book is to show that the nonparametric regression can be successfully
applied to system identification and how much can be achieved in this way. It gathers what …

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

Derived from the idea of stochastic approximation, recursive algorithms to identify a
Hammerstein system are presented. Two of them recover the characteristic of the nonlinear …

This paper proposes a neural network (NN) approach for modeling nonlinear channels with
memory. Two main examples are given:(1) modeling digital satellite channels and (2) …

A continuous-time Hammerstein system, ie, a system consisting of a nonlinear memoryless
subsystem followed by a linear dynamic one, is identified. The system is driven and …

This paper presents analytical, numerical, and experimental results for a stochastic gradient
adaptive scheme that identifies a polynomial-type nonlinear system with memory for noisy …

Identification of continuous-time non-linear systems characterised by fractional order
dynamics is studied. The Riemann-Liouville definition of fractional differentiation is used. A …

This paper is concerned with the blind identification of Volterra-Hammerstein systems. Two
identification scenarios are covered. The first scenario assumes that, although the input is …

Full realization of all versions of Volterra series like pure, truncated, and doubly finite
Volterra series, and especially, the realization of their high orders is an intractable problem …