Granular sampling using a pulse-coupled network of spiking neurons

Authors:
Eduardo Reck Miranda;John Matthias
Affiliations:
Computer Music Research Faculty of Technology and Faculty of Arts, University of Plymouth, Plymouth, UK;Computer Music Research Faculty of Technology and Faculty of Arts, University of Plymouth, Plymouth, UK
Venue:
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Year:
2005

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Abstract

We present a new technique for granular sampling using a pulsecoupled network of spiking artificial neurons to generate grain events. The system plays randomly selected sound grains from a given sound sample when any one of a weakly coupled network of up to 1000 neurons fires. The network can exhibit loosely correlated temporal solutions and also collective synchronised behaviour. This leads to very interesting sonic results, particularly with regard to rhythmic textures which can be controlled with various parameters within the model.