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Composing popular music with physarum polycephalum-based memristors

  • University of Plymouth
  • Interdisciplinary Centre for Computer Music Research

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Creative systems such as algorithmic composers often use Artificial Intelligence models like Markov chains, Neural Networks, and Genetic Algorithms to model stochastic processes. Unconventional Computing (UC) technologies explore non-digital ways of data storage, processing, input, and output. UC paradigms such as Biocomputing and Quantum Computing delve into domains beyond the binary bit to handle complex non-linear functions. In this paper, we harness Physarum polycephalum as a memristor to process and generate creative data for popular music. The organism works as a collaborator in the process of composing our song titled Creep into my Lawn. While there has been research conducted in this area, the literature lacks examples of popular music and how the organism’s non-linear behaviour can be controlled while composing music. This is important because non-linear forms of representation are not as obvious as conventional digital means. This study aims at disseminating this technology to non-experts and musicians so that they can incorporate it in their creative processes. Furthermore, it combines resistors and memristors to have more flexibility while generating music and optimises parameters for faster processing and performance.

Original languageEnglish
Pages (from-to)514-519
Number of pages6
JournalProceedings of the International Conference on New Interfaces for Musical Expression
DOIs
Publication statusPublished - 2020
Event20th International Conference on New Interfaces for Musical Expression, NIME 2020 - Birmingham, United Kingdom
Duration: 21 Jul 202025 Jul 2020

Keywords

  • Biocomputing
  • Musical Composition
  • Physarum polycephalum
  • Popular Music
  • Unconventional Computing

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Signal Processing
  • Control and Systems Engineering
  • Instrumentation
  • Computer Science Applications
  • Music

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