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.

Inhalt

Z. Pawlak: Foreword.- Preface.- Introduction.- Some Selected Soft Computing Tools and Techniques: Artificial Neural Networks; Fuzzy Sets and Fuzzy Logic; Rough Sets.- Preprocessing of Data in Acoustics: Musical Signal Representation; Musical Phrase Analyis; Acquisition of Test Results; Data Discretization.- Automatics Classification of Musical Instrument Sounds: Uncertainty of Musical Instrument Sound Representation; Feature Vector Extraction; Statistical Properties of Musical Data; Neural Network as a Classifier of Musical Instruments; Rough Set Decision System as a Classifier of Musical Instruments.- Automatic Recognition of Musical Phrases: Data Acquisition; Parametrization Process; Neural Network as a Classifier of Musical Phrases; Rough Set-Based Classification of Musical Phrases.- Intelligent Processing of Test Results: Inconsistency of Subjective Assessment Results; Application of Fuzzy Logic to the Processing of Test Results; Application of Rough Sets to the Processing of Test Results; Rough-Fuzzy Method of Test Result Processing.- Control Applications: Articulation-Related Features in the Pipe Organ Sound; Fuzzy Control of Pipe Organ.- Conclusions.