Skip to main content

Research Repository

See what's under the surface

Advanced Search

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

Gale, Ella; Matthews, Oliver; de Lacy Costello, Ben; Adamatzky, Andrew

Authors

Ella Gale ella.gale@uwe.ac.uk

Oliver Matthews



Abstract

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.

Presentation Conference Type Conference Paper (unpublished)
Start Date Apr 2, 2013
Publication Date Apr 2, 2013
Peer Reviewed Peer Reviewed
APA6 Citation Gale, E., Matthews, O., de Lacy Costello, B., & Adamatzky, A. (2013, April). Beyond Markov chains, towards adaptive memristor network-based music generation. Paper presented at First AISB symposium on Music and Unconventional Computing
Keywords music, memristor, memristor network, graph theory, rock'n'roll, jazz, light opera, procedural generation of music
Related Public URLs http://arxiv.org/abs/1302.0785
Additional Information Additional Information : Oliver Matthews can be contacted at: ojm@codersoffortune.net
Title of Conference or Conference Proceedings : First AISB symposium on Music and Unconventional Computing
Corporate Creators : Oliver Matthews

Files







You might also like



Downloadable Citations

;