Words recognition using associative memory

Abstract

Introduces the application of an analog associative memory chip to word recognition, which is a fundamental topic of the text recognition process. The word recognition method takes advantage of a statistical evaluation of the behavior of the optical character recognition system preceding it. That statistical information leads to the creation of a coding that is used to store a lexicon of the most used words in the chip. An input pattern is matched against the full database of the associative memory, and a set of closest patterns is returned. The precision reached by this operation ranges from 93% to 99%. These encouraging results demonstrate the general aptitude of the chip to solve classes of problems that need to use an associative memory.