Neural Analog Information Processing

Robert Hecht-Nielsen

doi:10.1117/12.932522

30 July 1982 Neural Analog Information Processing

Robert Hecht-Nielsen

Proceedings Volume 0298, Real-Time Signal Processing IV; (1982) https://doi.org/10.1117/12.932522
Event: 25th Annual Technical Symposium, 1981, San Diego, United States

Abstract

Neural Analog Information Processing (NAIP) is an effort to develop general purpose pattern classification architectures based upon biological information processing principles. This paper gives an overview of NAIP and its relationship to the previous work in neural modeling from which its fundamental principles are derived. It also presents a theorem concerning the stability of response of a slab (a two dimensional array of identical simple processing units) to time-invariant (spatial) patterns. An experiment (via computer emulation) demonstrating classification of a spatial pattern by a simple, but complete NAIP architecture is described. A concept for hardware implementation of NAIP architectures is briefly discussed.

Citation Download Citation

Robert Hecht-Nielsen "Neural Analog Information Processing", Proc. SPIE 0298, Real-Time Signal Processing IV, (30 July 1982); https://doi.org/10.1117/12.932522

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available