Statistical mechanics and neural networks

This review discusses the application of analytical methods from statistical mechanics to various neural network models of associative memory. The relevance of statistical mechanics stems from the discovery that some neural network models have a direct analogy with spin glass models of theoretical solid state physics. By using this analogy, one is able to study many of the properties of neural networks such as storage capacity, quality of retrieval and the effects of noise.