Dynamical properties of higher order random neural networks

Abstract

The authors have previously shown dynamical properties-dynamics of the activities for states-for higher order random neural networks, which use the weighted sum of products of input variables, with the digital state {1-,1} model. The paper describes dynamical properties for higher order random neural networks with the analog state models and the digital state (0,1) model.