Series: Studies in Computational Intelligence. Num Pages: 436 pages, 146 black & white illustrations, 8 colour illustrations, 71 black & white tables, biograp. BIC Classification: UY. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 30. Weight in Grams: 818. . 2005. Hardback. . . . .

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Bibliographic Details

Title: Perception-based Data Processing in Acoustics
Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Publication Date: 2005
Language: English
ISBN 10: 3540257292
ISBN 13: 9783540257295
Binding: Hardcover
Condition: New

About this title

Synopsis

This monograph provides novel insights into cognitive mechanisms underlying the processing of sound and music in different environments. A solid understanding of these mechanisms is vital for numerous technological applications such as for example information retrieval from distributed musical databases or building expert systems. In order to investigate the cognitive mechanisms of music perception fundamentals of hearing psychophysiology and principles of music perception are presented. In addition, some computational intelligence methods are reviewed, such as rough sets, fuzzy logic, artificial neural networks, decision trees and genetic algorithms. The applications of hybrid decision systems to problem solving in music and acoustics are exemplified and discussed on the basis of obtained experimental results.

From the Back Cover

The objective of the monograph is to provide novel insights into cognitive mechanisms underlying processing of sound and music in different environments. A solid understanding of these mechanisms is vital for numerous technological applications such as for example information retrieval from distributed musical databases or building expert systems. In order to investigate the cognitive mechanisms underlying music perception fundamentals of hearing psychophysiology and principles of music perception are presented. In addition, some computational intelligence methods are reviewed, such as rough sets, fuzzy logic, artificial neural networks, decision trees and genetic algorithms. The applications of hybrid decision systems to problem solving in music and acoustics are exemplified in this book and discussed on the basis of obtained experimental results.

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