Minimum-cost Ho-Kashyap associative processor for piecewise-hyperspherical classification

A synthesis algorithm is presented for generating a neural associative processor with piecewise-hyperspherical decision boundaries. Two important characteristics of the algorithm are that it represents each class with a near-minimum number of hyperspheres and that it has proven convergence properties. Classification results are presented for a three-class 3D distortion-invariant aircraft case study (invariant to changes in position, scale, and in-plane and out-of-plane rotation). The processor gives 98% accuracy