Optical implementations of radial basis classifiers

We describe two optical systems based on the radial basis function approach to pattern classification. An optical-disk-based system for handwritten character recognition is demonstrated. The optical system computes the Euclidean distance between an unknown input and 650 stored patterns at a demonstrated rate of26, 000 pattern comparisons/s. The ultimate performance of this system is limited by optical-disk resolution to 1011 binary operations/s. An adaptive system is also presented that facilitates on-line learning and provides additional robustness.