Extended random neural network model and its probability structure features
Yuanlie Lin · Journal of Tsinghua University(Science and Technology) · 1998
This paper proposes an extended random neural network (EGNN) model based on the model of Gelenbe's random neural network (GNN). It considers the case that the time intervals between successive signal emissions of a neuron are dependent on the neuron potential, and analyzes the stationary distribution of the EGNN. The paper proves that the EGNN has a stationary distribution of product form which leads to simple expressions for the system state, and shows that it has enhanced functions of adjusting the probability structure comparing with the GNN. Thus, the EGNN is competent in representing many intelligent and biological features (e.g., the feature of associated memory).