An associative memory model of language

An associative-memory model of language based on a neural network is proposed. It is shown that a language with finite sentences can be stored in a neural net completely. The memorizing process is realized by a dynamical learning algorithm which is convergent. Thus, a neural net not only has the ability to memorize syntactic information but can also memorize the semantic information of a language. The model is similar to human memory in some respects. A set of English words and Chinese sentences has been tested, and the simulation results on recognizing a word in default of a few characters are given