Simulation of the Neocognitron on a CCD Parallel Processing Architecture

The neocognitron is a neural network for pattern recognition and feature extraction. An analog CCD parallel processing architecture developed at Lincoln Laboratory is particularly well suited to the computational re(cid:173) quirements of shared-weight networks such as the neocognitron, and imple(cid:173) mentation of the neocognitron using the CCD architecture was simulated. A modification to the neocognitron training procedure, which improves network performance under the limited arithmetic precision that would be imposed by the CCD architecture, is presented.