Compact VLSI neural computer integrated with active pixel sensor for real-time ATR applications

Wai-Chi  Fang*, Gabriel Udomkesmalee, Leon Alkalai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A compact VLSI neural computer integrated with an active pixel sensor has been under development to mimic what is inherent in biological vision systems. This electronic eye- brain computer is targeted for real-time machine vision applications which require both high-bandwidth communication and high-performance computing for data sensing, synergy of multiple types of sensory information, feature extraction, target detection, target recognition, and control functions. The neural computer is based on a composite structure which combines Annealing Cellular Neural Network (ACNN) and Hierarchical Self-Organization Neural Network (HSONN). The ACNN architecture is a programmable and scalable multi- dimensional array of annealing neurons which are locally connected with their local neurons. Meanwhile, the HSONN adopts a hierarchical structure with nonlinear basis functions. The ACNN+HSONN neural computer is effectively designed to perform programmable functions for machine vision processing in all levels with its embedded host processor. It provides a two order-of-magnitude increase in computation power over the state-of-the-art microcomputer and DSP microelectronics. A compact current-mode VLSI design feasibility of the ACNN+HSONN neural computer is demonstrated by a 3D 16×8×9-cube neural processor chip design in a 2-μm CMOS technology. Integration of this neural computer as one slice of a 4'×4' multichip module into the 3D MCM based avionics architecture for NASA's New Millennium Program is also described.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsSteven K. Rogers
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages266-275
Number of pages10
ISBN (Print)0819424927
DOIs
StatePublished - 1 Dec 1997
EventApplications and Science of Artificial Neural Networks III - Orlando, FL, USA
Duration: 21 Apr 199724 Apr 1997

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume3077
ISSN (Print)0277-786X

Conference

ConferenceApplications and Science of Artificial Neural Networks III
CityOrlando, FL, USA
Period21/04/9724/04/97

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    Fang, W-C., Udomkesmalee, G., & Alkalai, L. (1997). Compact VLSI neural computer integrated with active pixel sensor for real-time ATR applications. In S. K. Rogers (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (pp. 266-275). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 3077). Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.271487