Over the past four decades, the growth of information processing and computational capacity has been truly remarkable, paced to a large extent by equally remarkable progress in the integration and ultra-miniaturization of semiconductor devices. And yet it is becoming increasingly apparent that currently envisioned electronic processors and computers are rapidly approaching technological barriers that delimit processing speed, computational sophistication, and throughput per unit dissipated power. This realization has in turn led to intensive efforts to circumvent such bottlenecks through appropriate advances in processor architecture, multiprocessor distributed tasking, and software-defined algorithms.An alternative strategy that may yield significant computational enhancements for certain broad classes of problems involves the utilization of multidimensional optical components capable of modulating and/or redirecting information-carrying light wave-fronts. Such an optical processing or computing approach relies for its competitive advantage principally on massive parallelism in conjunction with relative ease of implementation of complex (weighted) interconnections among many (perhaps simple) processing elements. A wide range of computational problems exist that lend themselves quite naturally to optical processing architectures, including pattern recognition, earth resources data acquisition and analysis, texture discrimination, synthetic aperture radar (SAR) image formation, radar ambiguity function generation, spread spectrum identification and analysis, systolic array processing, phased array beam steering, and artificial (robotic) vision.
Information-processing architectures in multidimensional classification: A validation test of the systems factorial technology.
