
Learning Algorithms
Theory and Applications in Signal Processing, Control and Communications
P. Mars(Author)
CRC Press
1st Edition
Published on 29. November 2017
Book
Hardback
240 pages
978-1-315-89487-4 (ISBN)
Description
Over the past decade, interest in computational or non-symbolic artificial intelligence has grown. The algorithms involved have the ability to learn from past experience, and therefore have significant potential in the adaptive control of signals and systems. This book focuses on the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms, evolutionary strategies, and evolutionary programming. Hybrid combinations of various algorithms are also discussed.Chapter 1 provides a brief overview of the topics discussed and organization of the text. The first half of the book (Chapters 2 through 4) discusses the basic theory of the learning algorithms, with one chapter devoted to each type. In the second half (Chapters 5 through 7), the emphasis is on a wide range of applications drawn from adaptive signal processing, system identification, and adaptive control problems in telecommunication networks.Learning Algorithms: Theory and Applications in Signal Processing, Control and Communications is an excellent text for final year undergraduate and first year graduate students in engineering, computer science, and related areas. Professional engineers and everyone involved in the application of learning techniques in adaptive signal processing, control, and communications will find this text a valuable synthesis of theory and practical application of the most useful algorithms.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Dimensions
Height: 234 mm
Width: 156 mm
Weight
600 gr
ISBN-13
978-1-315-89487-4 (9781315894874)
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Schweitzer Classification
Other editions
Additional editions

E-Book
01/2018
1st Edition
CRC Press
€264.99
Available for download
Person
P. Mars
Content
1. Introduction 2. Stochastic Learning Automata (SLA) 3. Artificial Neural Networks 4. Genetic and Evolutionary Optimisation 5. Applications in Signal Processing 6. Applications in Systems Control 7. Applications in Communications