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|a 9783211755402
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|a Nierhaus, Gerhard
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|a Algorithmic Composition
|h Elektronische Ressource
|b Paradigms of Automated Music Generation
|c by Gerhard Nierhaus
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| 250 |
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|a 1st ed. 2009
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| 260 |
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|a Vienna
|b Springer Vienna
|c 2009, 2009
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| 300 |
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|a X, 287 p. With 20 tables
|b online resource
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|a Historical Development of Algorithmic Procedures -- Markov Models -- Generative Grammars -- Transition Networks -- Chaos and Self-Similarity -- Genetic Algorithms -- Cellular Automata -- Artificial Neural Networks -- Artificial Intelligence -- Final Synopsis
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| 653 |
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|a Digital humanities
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| 653 |
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|a Algorithms
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| 653 |
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|a Computational Mathematics and Numerical Analysis
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| 653 |
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|a Mathematics / Data processing
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| 653 |
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|a Music
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| 653 |
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|a Applications of Mathematics
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| 653 |
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|a Digital Humanities
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| 653 |
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|a Mathematics
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|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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|a 10.1007/978-3-211-75540-2
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|u https://doi.org/10.1007/978-3-211-75540-2?nosfx=y
|x Verlag
|3 Volltext
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|a 519
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|a Algorithmic composition – composing by means of formalizable methods – has a century old tradition not only in occidental music history. This is the first book to provide a detailed overview of prominent procedures of algorithmic composition in a pragmatic way rather than by treating formalizable aspects in single works. In addition to an historic overview, each chapter presents a specific class of algorithm in a compositional context by providing a general introduction to its development and theoretical basis and describes different musical applications. Each chapter outlines the strengths, weaknesses and possible aesthetical implications resulting from the application of the treated approaches. Topics covered are: markov models, generative grammars, transition networks, chaos and self-similarity, genetic algorithms, cellular automata, neural networks and artificial intelligence are covered. The comprehensive bibliography makes this work ideal for the musician and the researcher alike
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