Neural network Z-plane implementation with very high interconnection rates

John C. Carson

doi:10.1117/12.23008

1 November 1990 Neural network Z-plane implementation with very high interconnection rates

John C. Carson

Proceedings Volume 1339, Materials, Devices, Techniques, and Applications for Z-Plane Focal Plane Array Technology II; (1990) https://doi.org/10.1117/12.23008
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States

Abstract

Neural networks offer the potential for a quantum leap in the capabilities of imaging sensor systems. The critical neural network implementation factors are: weighted interconnect between all detector outputs; parallel, linear processing of each detector output; fan-out to multiple (thousands) processing nodes per detector output and the ability to independently change interconnect weights and processor node connections within the detector integration times. For a 128 x 128 pixel detector array, the number of desirable interconnects could be as high as iO per second, compared to the approximately iO rates achieved presently with off-focal plane digital processors. Irvine Sensors Corporation (ISC) has conceived a new way of interconnecting 3-D focal plane readout modules and of laying out their component integrated circuits that appears to fulfill the very high interconnect rate requirements. This concept is described and mterconnectivity and other performance attributes are discussed.

Citation Download Citation

John C. Carson "Neural network Z-plane implementation with very high interconnection rates", Proc. SPIE 1339, Materials, Devices, Techniques, and Applications for Z-Plane Focal Plane Array Technology II, (1 November 1990); https://doi.org/10.1117/12.23008

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KEYWORDS

Sensors

Signal processing

Neural networks

Detector arrays

Artificial neural networks

Information operations

Analog electronics

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