Neural-processing-type optical WDM demultiplexer

A neural-processing-type optical WDM demultiplexer consisting of a multimode waveguide, a detector array, and an electrical neural network (NN) is described. This demultiplexer regenerates the original signals by recognizing the different speckle patterns of each channel with the pattern-recognition function of an NN. The demultiplexing properties can be flexibly changed, in the electrical domain, by modifying the parameters of the NN, and only simple optical components are required for implementation. Three 150-Mb/s WDM signals are successfully demultiplexed with a silica-based multimode planar waveguide, a four-channel detector array, and two high-speed analog neural network integrated circuits (ANNIC's), each of which has sixteen modifiable weights and four sigmoidal transfer functions.<
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