Weight error sensitivity of fixed point attractors in associative memory networks

ArticleinElectronics Letters 26(23):1985 - 1986 · December 1990with1 Read
Impact Factor: 0.93 · DOI: 10.1049/el:19901283 · Source: IEEE Xplore

    Abstract

    The sensitivity of Hopfield neural networks, with two-state neurons is investigated. Simple expressions are derived which give the probability that an equilibrium point of the nominal connection matrix remains a fixed point and an attractor, as a function of the relative error in the weights. Such probability decreases as the number of neurons in the network and the number of stored patterns increase.