Inductive Modelling of Temporal Sequences by

Abstract. In this paper we present a new self-organizing neural network, which builds a spatiotemporal model of an input temporal sequence inductively. The network is an extension of Kohonen’s Self-organizing Map with a modified Hebb’s rule for update of temporal synapses. The model building behavior is shown on inductive learning of a transition matrix from a data generated by a Markov Chain