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Missileborne Artificial Vision System (MAVIS)Several years ago when INTEL and China Lake designed the ETANN chip, analog VLSI appeared to be the only way to do high density neural computing. In the last five years, however, digital parallel processing chips capable of performing neural computation functions have evolved to the point of rough equality with analog chips in system level computational density. The Naval Air Warfare Center, China Lake, has developed a real time, hardware and software system designed to implement and evaluate biologically inspired retinal and cortical models. The hardware is based on the Adaptive Solutions Inc. massively parallel CNAPS system COHO boards. Each COHO board is a standard size 6U VME card featuring 256 fixed point, RISC processors running at 20 MHz in a SIMD configuration. Each COHO board has a companion board built to support a real time VSB interface to an imaging seeker, a NTSC camera, and to other COHO boards. The system is designed to have multiple SIMD machines each performing different corticomorphic functions. The system level software has been developed which allows a high level description of corticomorphic structures to be translated into the native microcode of the CNAPS chips. Corticomorphic structures are those neural structures with a form similar to that of the retina, the lateral geniculate nucleus, or the visual cortex. This real time hardware system is designed to be shrunk into a volume compatible with air launched tactical missiles. Initial versions of the software and hardware have been completed and are in the early stages of integration with a missile seeker.
Document ID
19950018834
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Andes, David K.
(Naval Air Warfare Center China Lake, CA, United States)
Witham, James C.
(Naval Air Warfare Center China Lake, CA, United States)
Miles, Michael D.
(Naval Air Warfare Center China Lake, CA, United States)
Date Acquired
September 6, 2013
Publication Date
May 11, 1994
Publication Information
Publication: JPL, A Decade of Neural Networks: Practical Applications and Prospects
Subject Category
Cybernetics
Accession Number
95N25254
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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