Tuesday, April 9, 2013

Soft Computing in Acoustics

Soft Computing in Acoustics
Author: Bozena Kostek
Edition: 1999
Binding: Hardcover
ISBN: 3790811904



Soft Computing in Acoustics: Applications of Neural Networks, Fuzzy Logic and Rough Sets to Musical Acoustics (Studies in Fuzziness and Soft Computing)


Applications of some selected soft computing methods to acoustics and sound engineering are presented in this book. Get Soft Computing in Acoustics computer books for free.
The aim of this research study is the implementation of soft computing methods to musical signal analysis and to the recognition of musical sounds and phrases. Accordingly, some methods based on such learning algorithms as neural networks, rough sets and fuzzy-logic were conceived, implemented and tested. Additionally, the above-mentioned methods were applied to the analysis and verification of subjective testing results. The last problem discussed within the framework of this book was the problem of fuzzy control of the classical pipe organ instrument. The obtained results show that computational intelligence and soft computing Check Soft Computing in Acoustics our best computer books for 2013. All books are available in pdf format and downloadable from rapidshare, 4shared, and mediafire.

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The aim of this research study is the implementation of soft computing methods to musical signal analysis and to the recognition of musical sounds and phrases. Accordingly, some methods based on such learning algorithms as neural networks, rough sets and fuzzy-logic were conceived, implemented and tested. Additionally, the above-mentioned methods were applied to the analysis and verification of subjective testing results. The last problem discussed within the framework of this book was the problem of fuzzy control of the classical pipe organ instrument he aim of this research study is the implementation of soft computing methods to musical signal analysis and to the recognition of musical sounds and phrases. Accordingly, some methods based on such learning algorithms as neural networks, rough sets and fuzzy-logic were conceived, implemented and tested. Additionally, the above-mentioned methods were applied to the analysis and verification of subjective testing results. The last problem discussed within the framework of this book was the problem of fuzzy control of the classical pipe organ instrument. The obtained results show that computational intelligence and soft computing

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