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Experimental study on arranging music by chaotic neural network
Author(s) -
Nagashima Tomomasa,
Kawashima Jun
Publication year - 1997
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/(sici)1098-111x(199704)12:4<323::aid-int5>3.0.co;2-q
Subject(s) - chaotic , artificial neural network , excuse , computer science , variation (astronomy) , content addressable memory , task (project management) , artificial intelligence , associative property , mathematics , engineering , physics , systems engineering , astrophysics , political science , law , pure mathematics
Based on the recalling ability on dynamic (chaotic) associative memory of neural networks, we have proposed two methods for making variations of an original melody. By computer simulations, we have shown candidates for the variation of the original melody taken from the first 16 bars of Minuet G major by Bach. The results obtained in this article may suggest a possibility that chaotic neural networks can excuse such a creative task as making variations of an original melody. © 1997 John Wiley & Sons, Inc.