Applications of Neural Networks, Fuzzy Logic and Rough Sets to Musical Acoustics
First Statement of Responsibility
by Boz̊ena Kostek.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Heidelberg
Name of Publisher, Distributor, etc.
Physica-Verlag HD
Date of Publication, Distribution, etc.
1999
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 ressource en ligne (XV, 244 pages)
SERIES
Series Title
Studies in Fuzziness and Soft Computing, 31.
CONTENTS NOTE
Text of Note
1. Introduction --; 2. Some Selected Soft Computing Tools and Techniques --; 3. Preprocessing of Acoustical Data --; 4. Automatic Classification of Musical Instrument Sounds --; 5. Automatic Recognition of Musical Phrases --; 6. Intelligent Processing of Test Results --; 7. Control Applications --; 8. Conclusions --; 9. References.
SUMMARY OR ABSTRACT
Text of Note
Applications of some selected soft computing methods to acoustics and sound engineering are presented in this book. 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 may be used for solving some vital problems in both musical and architectural acoustics.