A Generalized Unstructured Artificial Neural Network Architecture: A First Study
In this document, we will present an unstructured neural network based on the mathematics of holographic storage. This work was inspired when we discovered there are similarities between brain waves and the wave propagation and subsequent interference patterns seen in holograms. We then analyzed the mathematics to produce a general mathematical description of the holographic process. From this analysis we are able to show how the holographic process can be used as an associative memory network. Additionally, the process may also be used as a regular feed-forward network. The most striking aspect of these networks is that, using the holographic process, the a priori knowledge of the system may be better utilized to tailor the neural network for a particular problem. This aspect, makes this neural network formation process particularly useful for control.
R. S. Woodley and L. Acar, "A Generalized Unstructured Artificial Neural Network Architecture: A First Study," Proceedings of the American Control Conference (2002, Anchorage, AK), vol. 5, pp. 3829-3834, Institute of Electrical and Electronics Engineers (IEEE), May 2002.
The definitive version is available at https://doi.org/10.1109/ACC.2002.1024525
American Control Conference (2002: May 8-10, Anchorage, AK)
Electrical and Computer Engineering
Keywords and Phrases
Associative Memory Network; Neural Networks; Unstructured Neural Network
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
© 2002 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.