PAUSIBLE NEURAL NETWORK WITH SUPERVISED AND UNSUPERVISED CLUSTER ANALYSIS

摘要

A plausible neural network (PLANN) is an artificial neural network with weight connection given by mutual information, which has the capability and learning, and yet retains many characteristics of a biological neural network. The learning algorithm (300, 301, 302, 304, 306, 308) is based on statistical estimation, which is faster than the gradient decent approach currently used. The network after training becomes a fuzzy/belief network; the inference and weight are exchangeable, and as a result, knowledge extraction becomes simple. PLANN performs associative memory, supervised, semi-supervised, unsupervised learning and function/relation approximation in a single network architecture. This network architecture can easily be implemented by analog VLSI circuit design.