Share Email Print

Proceedings Paper

Unipolar shift-invariant associative Hamming net
Author(s): Francis T. S. Yu; Guowen Lu; Chii-Maw Uang; Shizhuo Yin; Zhongkong Wu
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A unipolar shift-invariant associative Hamming net is described in this paper. The proposed Hamming net is a three-layer neural network, in which the first layer is a shift-invariant Hamming layer using unipolar interconnection weight matrix, the second layer is a winner- take-all layer, and the last layer is a memory-mapping layer. In experiment, a hybrid optical architecture using photorefractive holograms is proposed.

Paper Details

Date Published: 1 March 1994
PDF: 8 pages
Proc. SPIE 2237, Optical Pattern Recognition V, (1 March 1994); doi: 10.1117/12.169435
Show Author Affiliations
Francis T. S. Yu, The Pennsylvania State Univ. (United States)
Guowen Lu, The Pennsylvania State Univ. (United States)
Chii-Maw Uang, The Pennsylvania State Univ. (United States)
Shizhuo Yin, The Pennsylvania State Univ. (United States)
Zhongkong Wu, The Pennsylvania State Univ. (United States)

Published in SPIE Proceedings Vol. 2237:
Optical Pattern Recognition V
David P. Casasent; Tien-Hsin Chao, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?