Networks of Mixed Canonical-Dissipative Systems and Dynamic Hebbian Learning
Julio Rodríguez, Max-Olivier Hongler · International Journal of Computational Intelligence Systems · 2009
We study the dynamics of a network consisting of N diffusively coupled, stable-limit-cycle oscillators on which individual frequencies are parametrized by ω k , k = 1, . . ., N. We introduce a learning rule which influences the ω k by driving the system towards a consensual oscillatory state in which all oscillators share a common frequency ω c .We are able to analytically calculate ω c .The network topology strongly affects the relaxation rate but not the ultimate consensual ω c .We report numerical simulations to show the learning mechanisms at work and confirm our theoretical assertions.