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Soft Computing in Acoustics
Soft Computing in Acoustics
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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 v…
  • Leidėjas:
  • Metai: 2014
  • Puslapiai: 244
  • ISBN-10: 366213005X
  • ISBN-13: 9783662130056
  • Formatas: 21 x 27.9 x 1.4 cm, minkšti viršeliai
  • Kalba: Anglų

Soft Computing in Acoustics (el. knyga) (skaityta knyga) | knygos.lt

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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.

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  • Autorius: Bozena Kostek
  • Leidėjas:
  • Metai: 2014
  • Puslapiai: 244
  • ISBN-10: 366213005X
  • ISBN-13: 9783662130056
  • Formatas: 21 x 27.9 x 1.4 cm, minkšti viršeliai
  • Kalba: Anglų

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.

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