TRAINABLE PATTERN CLASSIFIER USING A COMPUTER-GENERATED HOLOGRAM

Abstract

A novel technique for pattern classification is proposed and demonstrated. The perceptron learning algorithm is used for training, and the trained interconnection weight matrix is transferred into a computer-generated hologram. The hologram is used as a correlation filter in the optical system for pattern classification. Both computer simulation and optical experiment results are presented.