Stochastic Analysis of Synchronous Neural Networks with Asymmetric Weights
Olivier Bernier · Europhysics Letters (EPL) · 1991
We present a method to analyse the properties of a synchronous stochastic neural network with asymmetric connections. We obtain an equivalence between the dynamics of the network and the iteration defined by a deterministic continuous mapping. This approach enables us to predict the existence of a bifurcation from a stable fixed point to an attracting cycle in a simple case.