An optical matrix-vector multiplier has ben efficiently used for photonic implementation of Hopfield network model, which is used for binary pattern recognition. Training matrices are recorded on electrically addressed spatial light modulator, where each matrix is composed of the same row of each pattern, that the network is being trained with. After training, if an unknown pattern is presented to the network in the form of a vector, the output vector is obtained by the element that has the highest magnitude through a winner- take-all algorithm. Pattern can be recognized even if the input is noisy and distorted.
An improved optical matrix-vector multiplication is performed by convolution process. The multiplicated binary numbers are represented by on/off states of light sources and the multiplier binary numbers are recorded on a spatial light modulator. Cylindrical optics is used as free space interconnection. The convolution coefficients are recorded on a CCD array. The output of the CCD array are added in a computer to yield the result of multiplication. The operation is completely digital and needs no analog to digital conversion. Because of parallel operation in two dimensions, the processing speed is greatly increased.
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