Figure 2. The inner product computing model where l.P.O. represents an inner proouct operator and V.S.O. represents a vector scaling operation. (8) (1-fh) l.P.O., I • 1. 2 . M. 0)) (Hh) V.S.O., I - 1, 2 . M. Figure 3. A scnematlc diagram of the optical implementation of l.P.O. and V.s.o. discussed…
Liu, Hua-Kuang · California inst of technology pasadena jet propulsion lab · Television systems · Image processing · Optical processing · Liquid crystals · Neural nets · Optimization · Real time · Computer architecture · Optical images · Microchannel plates · Fabry perot interferometers · Information retrieval · Computer applications · Associative processing · Correlation techniques · BIAS · Low frequency · Dynamic range · Light modulators · Holograms · Pulse frequency modulation · Optical properties · Spatial distribution · INPUT · Compression · Nonlinear systems
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