Neural networks in multidimensional domains : fundamentals and new trends in modelling and control /
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| Imprint: | London ; New York : Springer, ©1998. |
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| Description: | 1 online resource (xiv, 165 pages) : illustrations. |
| Language: | English |
| Series: | Lecture notes in control and information sciences, 0170-8643 ; 234 Lecture notes in control and information sciences ; 234. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11072051 |
| Summary: | In this monograph, new structures of neural networks in multidimensional domains are introduced. These architectures are a generalization of the Multi-layer Perceptron (MLP) in Complex, Vectorial and Hypercomplex algebra. The approximation capabilities of these networks and their learning algorithms are discussed in a multidimensional context. The work includes the theoretical basis to address the properties of such structures and the advantages introduced in system modelling, function approximation and control. Some applications, referring to attractive themes in system engineering and a MATLAB software tool, are also reported. The appropriate background for this text is a knowledge of neural networks fundamentals. The manuscript is intended as a research report, but a great effort has been performed to make the subject comprehensible to graduate students in computer engineering, control engineering, computer sciences and related disciplines. |
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| Physical Description: | 1 online resource (xiv, 165 pages) : illustrations. |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references (pages 161-165). |
| ISBN: | 1852330066 9781852330064 |
| ISSN: | 0170-8643 ; |