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Three-D Artificial Neural Network (3DANN) technology. Blueprint for the futureIrvine Sensors Corporation (ISC), working closely with JPL under BMDO/ONR sponsorship, is developing a radically new neural computing technology. Primarily aimed at discrimination and target recognition for BMDO missile interceptor applications, it appears to have near term commercial applicability to such problems as handwriting and face recognition, just to name two. In its earliest form it will be able to perform inner product computation using 262 thousand 64x64 templates (weighted synapse arrays) where the 64(exp 5) weights can all be changed every millisecond. Internal switching provides an inherent capability to zoom, translate, or rotate the templates. The 3D silicon architecture is manufactured on a commercial, high volume DRAM production line at very low cost, enabling its commercialization. Two technology thrusts are beginning: in the first, the 64 layer capability of 3DANN-I will be extended to 1024 layers and beyond. In the second layer size will be shrunk to 2-3 millimeters to reduce layer costs. Our workshop goal is to expose this technology to the neural network community as an emerging tool for their use and to obtain their desire for its future development.
Document ID
19950018840
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Carson, John
(Irvine Sensors Corp. Costa Mesa, 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
95N25260
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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