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Representations of Musical Signals describes a new generation of digital audio and computer music systems made possible by recent advances in digital signal processing theory, hardware design, and programming techniques. It explores new representations of musical signals that can have profound effects on the way musicians conceive of and realize musical ideas. In particular, the book focuses on models that combine time-domain and frequency-domain representations (grains, wavelets, and physical models), visual programming and advanced user interfaces, and that incorporate musical knowledge using artificial intelligence techniques and adaptive neural networks.
The 14 contributions take up issues of how musical signals should be displayed to musicians, engineers, and scientists who want to work with them, how professionals can work with the representations to accomplish musical tasks, how systems can be designed to permit working with multiple views of the same signal, and how representations of musical signals should be organized to promote efficient communication between devices using these signals.
Contributors: J. M. Adrien. D. Arfib. R. D'Autilia. C. Cadoz. S. Cavaliere. G. De Poli, G. Evangelista. J. Florens. G. Garnett. A. Grossman. F. Guerra. K. Hebei. R. Kronland-Martinet. C. Lischka. A. Piccialli. J-C. Risset. C. Roads. C. Scaletti., J. Sundberg.
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Aldo Piccialli is a member of the faculty of the Department of Physics at the University of Naples.
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