The recalling process dynamics of associative memory neural networks in macrodynamical approach

Abstract The results of a computer study of the continuous-time version of macrodynamical system of equations governing the recalling process of associative memory neural networks are presented. The comparative analysis of two models of associative memory network—recurrent (autoassociative) and layered (feedforward)—is given. The phase portraits of macrodynamical system at a variety of representative values of parameter α, the loading ratio, are obtained and the appearance of the bifurcation of equilibrium frustration (the saddle-node bifurcation) is demonstrated. The behavior of the basins of attraction of network dynamics equilibria is studied as well.