Interpreting Rhythmic Structures Using Artificial Nerual Networks

• This thesis discusses the development of an artifical neural system for the real-time interpretation of rhythmic structures. The system comprises two self-organising sub-systems, the SONNET network devised by Albert Nigrin and a neural foot-tapper, each of which responds to a continuous sequence of onsets pertaining to musical events. Object-oriented software simulations of the system are discussed throughout the thesis, and SONNET modifications are presented.

• Keywords:
  

Rhythm and Meter

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