Fast competitive learning algorithm for image compression neural networks

摘要

A fast training algorithm for competitive learning neural networks is presented. The algorithm identifies the full Euclidean distance calculation as the major bottleneck. Through theoretical analysis, a simple approximate distance is derived and used as the pre-test to exclude most of the neurons in competitive learning. This provides significant efficiency improvement over the standard algorithm.