Beyond Markov chains, towards adaptive memristor network-based music generation

Gale, E., Matthews, O., de Lacy Costello, B. and Adamatzky, A. and Oliver Matthews (2013) Beyond Markov chains, towards adaptive memristor network-based music generation. In: First AISB symposium on Music and Unconventional Computing, University of Exeter, UK, April 2nd-5th, 2013. University of Exeter, UK: UNSPECIFIED Available from: http://eprints.uwe.ac.uk/18913

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Abstract/Description

We undertook a study of the use of a memristor network for music generation, making use of the memristor's memory to go beyond the Markov hypothesis. Seed transition matrices are created and populated using memristor equations, and which are shown to generate musical melodies and change in style over time as a result of feedback into the transition matrix. The spiking properties of simple memristor networks are demonstrated and discussed with reference to applications of music making. The limitations of simulating composing memristor networks in von Neumann hardware is discussed and a hardware solution based on physical memristor properties is presented.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Oliver Matthews can be contacted at: ojm@codersoffortune.net
Uncontrolled Keywords:music, memristor, memristor network, graph theory, rock'n'roll, jazz, light opera, procedural generation of music
Faculty/Department:Faculty of Health and Applied Sciences > Department of Applied Sciences
ID Code:18913
Deposited By: Dr E. Gale
Deposited On:13 Feb 2013 14:45
Last Modified:05 Dec 2016 05:13

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