Adaptive Neural Network Models for Intelligent Computations

摘要

By looking closely at the dynamics of learning, it was discovered that fordifferent input the states of network tended to cluster around three values plus the initial state. These four states can be considered as possible states of an actual finite state machine and the movement between these states as a function of input can be interpreted as the state transition of a state machine. This four state machine constructed is a perfect state machine that recognize the dual parity grammar. It recognizes dual parity strings with arbitrary length. This rule extraction generalization power is qualitatively different from that of the 'data interpolation' paradigm which is usually true for a feedforward neural net.