High-order neural network employing adaptive architecture

Ronald Michaels

doi:10.1117/12.140108

1 July 1992 High-order neural network employing adaptive architecture

Ronald Michaels

Proceedings Volume 1710, Science of Artificial Neural Networks; (1992) https://doi.org/10.1117/12.140108
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

For the two category classification problem a method of creating an adaptive architecture network (AANET) is presented and discussed. The principal means of adaptation of this network is the modification of its architecture. AANET is constructed using the repeated application of the outer product expansion, the Karhunen-Loeve expansion, and the Ho- Kashyap algorithm. A multilayer AANET may then be transformed into an equivalent single layer network by passing a vector x having symbolic terms through the network.

Citation Download Citation

Ronald Michaels "High-order neural network employing adaptive architecture", Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); https://doi.org/10.1117/12.140108

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