Synchronization of laser oscillators, associative memory, and optical neurocomputing

Abstract

We investigate here possible neurocomputational features of networks of laser oscillators. Our approach is similar to classical optical neurocomputing where artificial neurons are lasers and connection matrices are holographic media. However, we consider oscillatory neurons communicating via phases rather than amplitudes. Memorized patterns correspond to synchronized states where the neurons oscillate with equal frequencies and with prescribed phase relations. The mechanism of recognition is related to phase locking.