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Proceedings Paper

Stabilizing bidirectional associative memory with Principles in Independent Component Analysis and Null Space (PICANS)
Author(s): James P. LaRue; Yuriy Luzanov
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Paper Abstract

A new extension to the way in which the Bidirectional Associative Memory (BAM) algorithms are implemented is presented here. We will show that by utilizing the singular value decomposition (SVD) and integrating principles of independent component analysis (ICA) into the nullspace (NS) we have created a novel approach to mitigating spurious attractors. We demonstrate this with two applications. The first application utilizes a one-layer association while the second application is modeled after the several hierarchal associations of ventral pathways. The first application will detail the way in which we manage the associations in terms of matrices. The second application will take what we have learned from the first example and apply it to a cascade of a convolutional neural network (CNN) and perceptron this being our signal processing model of the ventral pathways, i.e., visual systems.

Paper Details

Date Published: 23 May 2013
PDF: 19 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87451Z (23 May 2013); doi: 10.1117/12.2017742
Show Author Affiliations
James P. LaRue, JADCO Signals (United States)
Yuriy Luzanov, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)

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