Ebook: Nonlinearities and Synchronization in Musical Acoustics and Music Psychology

Nonlinearities are a crucial and founding principle in nearly all musical systems, may they be musical instruments, timbre or rhythm perception and production, or neural networks of music perception. This volume gives an overview about present and past research in these fields. In Musical Acoustics, on the one hand the nonlinearities in musical instruments often produce the musically interesting features. On the other, musical instruments are nonlinear by nature, and tone production is the result of synchronization and self-organization within the instruments. Furthermore, as nearly all musical instruments are driven by impulses an Impulse Pattern Formulation (IPF) is suggested, an iterative framework holding for all musical instruments. It appears that this framework is able to reproduce the complex and perceptionally most salient initial transients of musical instruments. In Music Psychology, nonlinearities are present in all areas of musical features, like pitch, timbre, or rhythm perception. In terms of rhythm production and motion, self-organizing models are the only ones able to explain sudden phase-transitions while tapping. Self-organizing neural nets, both of the Kohonen and the connectionist types are able to reproduce tonality, timbre similarities, or phrases. The volume also gives an overview about the signal processing tools suitable to analyze sounds in a nonlinear way, both in the Fourier-domain, like Wavelets or correlograms, and in the phase-space domain, like fractal dimensions or information structures. Furthermore, it gives an introduction to Physical Modeling of musical instruments using Finite-Element and Finite-Difference methods, to cope with the high complexity of instrument bodies and wave couplings. It appears, that most musical systems are self-organized ones, and only therefore able to produce all unexpected and interesting features of music, both in production and perception.

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Nonlinearities are a crucial and founding principle in nearly all musical systems, may they be musical instruments, timbre or rhythm perception and production, or neural networks of music perception. This volume gives an overview about present and past research in these fields. In Musical Acoustics, on the one hand the nonlinearities in musical instruments often produce the musically interesting features. On the other, musical instruments are nonlinear by nature, and tone production is the result of synchronization and self-organization within the instruments. Furthermore, as nearly all musical instruments are driven by impulses an Impulse Pattern Formulation (IPF) is suggested, an iterative framework holding for all musical instruments. It appears that this framework is able to reproduce the complex and perceptionally most salient initial transients of musical instruments. In Music Psychology, nonlinearities are present in all areas of musical features, like pitch, timbre, or rhythm perception. In terms of rhythm production and motion, self-organizing models are the only ones able to explain sudden phase-transitions while tapping. Self-organizing neural nets, both of the Kohonen and the connectionist types are able to reproduce tonality, timbre similarities, or phrases. The volume also gives an overview about the signal processing tools suitable to analyze sounds in a nonlinear way, both in the Fourier-domain, like Wavelets or correlograms, and in the phase-space domain, like fractal dimensions or information structures. Furthermore, it gives an introduction to Physical Modeling of musical instruments using Finite-Element and Finite-Difference methods, to cope with the high complexity of instrument bodies and wave couplings. It appears, that most musical systems are self-organized ones, and only therefore able to produce all unexpected and interesting features of music, both in production and perception.

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Nonlinearities are a crucial and founding principle in nearly all musical systems, may they be musical instruments, timbre or rhythm perception and production, or neural networks of music perception. This volume gives an overview about present and past research in these fields. In Musical Acoustics, on the one hand the nonlinearities in musical instruments often produce the musically interesting features. On the other, musical instruments are nonlinear by nature, and tone production is the result of synchronization and self-organization within the instruments. Furthermore, as nearly all musical instruments are driven by impulses an Impulse Pattern Formulation (IPF) is suggested, an iterative framework holding for all musical instruments. It appears that this framework is able to reproduce the complex and perceptionally most salient initial transients of musical instruments. In Music Psychology, nonlinearities are present in all areas of musical features, like pitch, timbre, or rhythm perception. In terms of rhythm production and motion, self-organizing models are the only ones able to explain sudden phase-transitions while tapping. Self-organizing neural nets, both of the Kohonen and the connectionist types are able to reproduce tonality, timbre similarities, or phrases. The volume also gives an overview about the signal processing tools suitable to analyze sounds in a nonlinear way, both in the Fourier-domain, like Wavelets or correlograms, and in the phase-space domain, like fractal dimensions or information structures. Furthermore, it gives an introduction to Physical Modeling of musical instruments using Finite-Element and Finite-Difference methods, to cope with the high complexity of instrument bodies and wave couplings. It appears, that most musical systems are self-organized ones, and only therefore able to produce all unexpected and interesting features of music, both in production and perception.

Content:
Front Matter....Pages 1-29
Front Matter....Pages 9-10
Frequency Representations....Pages 13-56
Embedding Representations....Pages 57-108
Front Matter....Pages 109-111
Applications to Musical Instruments....Pages 113-115
Finite-Difference Simulation....Pages 117-131
Finite-Element Simulation....Pages 133-153
Front Matter....Pages 155-155
Musical Instruments....Pages 157-284
Impulse Pattern Formulation....Pages 285-296
Examples of Impulse Pattern Formulation....Pages 297-315
Front Matter....Pages 317-317
Psychoacoustics....Pages 319-328
Timbre....Pages 329-379
Rhythm....Pages 381-402
Pitch, Melody, Tonality....Pages 403-437
CD Tracks....Pages 439-441
Introduction....Pages 1-7
Back Matter....Pages 443-458

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Nonlinearities are a crucial and founding principle in nearly all musical systems, may they be musical instruments, timbre or rhythm perception and production, or neural networks of music perception. This volume gives an overview about present and past research in these fields. In Musical Acoustics, on the one hand the nonlinearities in musical instruments often produce the musically interesting features. On the other, musical instruments are nonlinear by nature, and tone production is the result of synchronization and self-organization within the instruments. Furthermore, as nearly all musical instruments are driven by impulses an Impulse Pattern Formulation (IPF) is suggested, an iterative framework holding for all musical instruments. It appears that this framework is able to reproduce the complex and perceptionally most salient initial transients of musical instruments. In Music Psychology, nonlinearities are present in all areas of musical features, like pitch, timbre, or rhythm perception. In terms of rhythm production and motion, self-organizing models are the only ones able to explain sudden phase-transitions while tapping. Self-organizing neural nets, both of the Kohonen and the connectionist types are able to reproduce tonality, timbre similarities, or phrases. The volume also gives an overview about the signal processing tools suitable to analyze sounds in a nonlinear way, both in the Fourier-domain, like Wavelets or correlograms, and in the phase-space domain, like fractal dimensions or information structures. Furthermore, it gives an introduction to Physical Modeling of musical instruments using Finite-Element and Finite-Difference methods, to cope with the high complexity of instrument bodies and wave couplings. It appears, that most musical systems are self-organized ones, and only therefore able to produce all unexpected and interesting features of music, both in production and perception.

Content:
Front Matter....Pages 1-29
Front Matter....Pages 9-10
Frequency Representations....Pages 13-56
Embedding Representations....Pages 57-108
Front Matter....Pages 109-111
Applications to Musical Instruments....Pages 113-115
Finite-Difference Simulation....Pages 117-131
Finite-Element Simulation....Pages 133-153
Front Matter....Pages 155-155
Musical Instruments....Pages 157-284
Impulse Pattern Formulation....Pages 285-296
Examples of Impulse Pattern Formulation....Pages 297-315
Front Matter....Pages 317-317
Psychoacoustics....Pages 319-328
Timbre....Pages 329-379
Rhythm....Pages 381-402
Pitch, Melody, Tonality....Pages 403-437
CD Tracks....Pages 439-441
Introduction....Pages 1-7
Back Matter....Pages 443-458
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