Techniques for high-performance analog neural networks

David P. Casasent; Leonard Neiberg; Sanjay S. Natarajan

doi:10.1117/12.135106

1 March 1992 Techniques for high-performance analog neural networks

David P. Casasent, Leonard Neiberg, Sanjay S. Natarajan

Proceedings Volume 1608, Intelligent Robots and Computer Vision X: Neural, Biological, and 3-D Methods; (1992) https://doi.org/10.1117/12.135106
Event: Robotics '91, 1991, Boston, MA, United States

Abstract

We consider analog neural network implementations (using VLSI or optical technologies) with limited accuracy and various noise and nonlinearity error sources. Algorithms and techniques to achieve high performance (good recognition P'_c% and large storage capacity) on such systems are considered. The adaptive clustering neural net (ACNN) and robust Ho-Kashyap (HK-2) associative processor (AP) are the neural networks considered in detail.

Citation Download Citation

David P. Casasent, Leonard Neiberg, and Sanjay S. Natarajan "Techniques for high-performance analog neural networks", Proc. SPIE 1608, Intelligent Robots and Computer Vision X: Neural, Biological, and 3-D Methods, (1 March 1992); https://doi.org/10.1117/12.135106

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