Temporal Sequences of Patterns with an Inverse Function Delayed Neural Network
Johan Sveholm, Y. HAYAKAWA, Koji Nakajima · IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences · 2006
A network based on the Inverse Function Delayed (ID) model which can recall a temporal sequence of patterns, is proposed. The classical problem that the network is forced to make long distance jumps due to strong attractors that have to be isolated from each other, is solved by the introduction of the ID neuron. The ID neuron has negative resistance in its dynamics which makes a gradual change from one attractor to another possible. It is then shown that a network structure consisting of paired conventional and ID neurons, perfectly can recall a sequence.