title: 64-channel correlator implementing a Kohonen-like neural network for handwritten-digit recognition.
abstract: We present an optical implementation of an improved version of the Kohonen map neural network applied to the recognition of handwritten digits taken from a postal code database. Improvements result from the introduction of supervision during the learning stage, a technique that also simplifies the map layer labeling. The experimental implementation is based on a frequency-multiplexed raster computer-generated hologram used to realize the required N(4) interconnection. The setup is shown to be equivalent to a 64-channel correlator. Computer simulations are used to study various detection and classification procedures. The results of the optical experiments, obtained with binary phase computer-generated holograms, are presented and shown to be in excellent agreement with the simulations.
authors.forename: M
authors.initials: M
authors.lastname: Barge
authors.forename: K
authors.initials: K
authors.lastname: Heggarty
authors.forename: Y
authors.initials: Y
authors.lastname: Idan
authors.forename: R
authors.initials: R
authors.lastname: Chevallier