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News paradigms for channel equalization and identification based on nonlinear structures and evolutionary algorithms

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Author(s):
Romis Ribeiro de Faissol Attux
Total Authors: 1
Document type: Doctoral Thesis
Press: Campinas, SP.
Institution: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação
Defense date:
Examining board members:
João Marcos Travassos Romano; João Cesar Moura Mota; Amauri Lopes; Fernando José Von Zuben; Wagner Caradori do Amaral; Rui Seara
Advisor: João Marcos Travassos Romano
Abstract

The objective of this work is to investigate the use of nonlinear structures and optimization techniques based on evolutionary computation in channel equalization and identification problems. The text is structured according to a twofold division: the first part is dedicated to the analysis of the foundations of the filtering problem, and the second, to the exposition of new approaches to its solution. The first part, whose starting point is the primordial idea of communication, encompasses the various aspects of the design of a signal-processing device. The entire explanation is permeated by a fundamental idea: the constitution of a generic paradigm for adaptive filtering. In the second part, a number of original contributions are presented that are related in various ways to the essence of this paradigm. These contributions involve the problems of blind linear equalization, neural network-based equalization and pre-distortion, blind and supervised identification of feedforward and feedback plants, maximum-likelihood sequence estimation and nonlinear blind equalization based on prediction. Such proposals, apart from possessing an intrinsic value, can also be understood as a corpus of evidences of the validity of the unifying ideas belonging to the established theoretical framework (AU)