System Realization Using Associative Memory Building Blocks

Mark Carlotto; David Izraelevitz

doi:10.1117/12.969758

1 March 1990 System Realization Using Associative Memory Building Blocks

Mark Carlotto, David Izraelevitz

Proceedings Volume 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques; (1990) https://doi.org/10.1117/12.969758
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

A data-based model of associative memory is described which uses statistical inference techniques to estimate an output response from a set of inputs and a database of previously stored patterns. The model is easily scaled in terms of the number of patterns that can be stored in the database as well as the number of fields in a pattern. Other features include the ability to change the input and output fields, to adjust the amount of generalization performed by the associative memory, and to control the size of the database by pruning redundant or conflicting patterns. Applications of associative memories to a wide variety of problems are illustrated to motivate their use as general system building blocks. Implementations in hardware and software are discussed.

Citation Download Citation

Mark Carlotto and David Izraelevitz "System Realization Using Associative Memory Building Blocks", Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); https://doi.org/10.1117/12.969758

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