Locally linear neural networks for optical correlators
Steven C. Gustafson, Gordon R. Little, Eugene G. Olczak · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
Locally linear neural networks that were developed to process image data using optical correlator outputs are described. These networks extend well-known nearest neighbor techniques and have the desirable properties of coordinate invariance, data interpolation, linear representation, and data bootstrapping. Simplified locally linear networks are successfully used to estimate the rotation of objects in images for objects located by simulated optical correlation.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.