Stimulus preprocessing for holographic neural networks (CROSBI ID 32621)
Prilog u knjizi | izvorni znanstveni rad
Podaci o odgovornosti
Manger, Robert ; Plantamura, Vito Leonardo ; Souček, Branko
engleski
Stimulus preprocessing for holographic neural networks
There are two types of preprocessing which are of fundamental importance for holographic neural networks. The first type is stimulus symmetrization, which assures reasonable accuracy in reproducing the learned stimulus-response associations. The second type is stimulus expansion, which increases the number of stimulus-response associations that can accurately be encoded into a holographic neuron. In this chapter we review the standard preprocessing methods used for holographic neural networks, and also propose two new methods, i.e. one for each of the two types of preprocessing. Some situations are described where these new methods are useful, and some experimental results are listed. We believe that our proposals greatly enhance the applicability of holographic networks.
artificial neural networks, holographic neural technology, preprocessing
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Podaci o prilogu
79-90-x.
objavljeno
Podaci o knjizi
Frontier Decision Support Concepts
Plantamura, Vito Leonardo ; Souček, Branko ; Visaggio, Giuseppe
New York (NY): John Wiley & Sons
1994.
0-471-59256-0