Abstract
Hardware associative or content-addressable memory (CAM) which finds in one operation the nearest match to input data among several templates is very crucial in the design of effective pattern recognition systems. We call this type of memory a relaxative CAM (RCAM) as opposed to the traditional exact-match CAM design. A compact implementation of an RCAM calls for the employment of a neural network model. In the paper we present the design and silicon implementation of an RCAM using a neural mutual inhibition network as the relaxation circuit. Spice simulations of the mutual inhibition and the RCAM performance are presented. A 16-word 12-bit IC has been fabricated through MOSIS using 2 μm double-metal CMOS technology. The RCAM chip was tested and its correct functionality has been fully verified.
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