A learning model for oscillatory networks.
A learning model for coupled oscillators is proposed. The proposed learning rule takes a simple form by which the intrinsic frequencies of the component oscillators and the coupling strength between them are changed according to the effects of the input signals on the dynamics of the oscillator. In the learning mode, each component oscillator receives a teacher signal of desired phase and frequency, and a desired parameter set for generating the desired pattern is acquired by the proposed learning rule. It is known that the basic locomotor patterns of many living bodies are generated by coupled neural oscillators. The proposed learning rule could be a learning model used by such neural systems to acquire an adequate parameter set for generating a desired locomotor pattern.
Nishii
J
J
Laboratory for Neural Modeling, The Institute of Physical and Chemical Research (RIKEN), 2-1 Hirosawa, Wako, Saitama, Japan.