Characteristics of Dynamical Phase Transitions for Noise Intensities
Muyoung Heo, Jong‐Kil Park, Kyungsik Kim · Procedia Computer Science · 2014
We simulate and analyze dynamical phase transitions in a Boolean neural network with initial random connections. Since we treat a stochastic evolution by using a noise intensity, we show from our condition that there exists a critical value for the noise intensity. The nature of the phase transition are found numerically and analytically in two connections of probability density function and one random network.