Alpha-Beta Associative Memories for Gray Level Patterns.

In this paper, we show how the binary Alpha-Beta associative memories, created and developed by Yáñez-Márquez, and introduced in [1-3], can be used to operate with gray level patterns (namely gray-level images), improving the results presented by Sossa et. al. in [4]. To achieve our goal, given a fundamental set of gray-level patterns, we find the binary representation of each entry, then we build a binary Alpha-Beta associative memory. After that, a given gray level pattern or a distorted version of it is recalled by converting its entries to a binary representation, then recalling it with the binary associative memory, and finally converting again this binary output pattern into a gray level pattern. Experimental results show the efficiency of the new memories. It is important to point out that this solution is more simple and elegant than that of the presented in [4]. [ABSTRACT FROM AUTHOR]