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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Druckformat: 1064-2315
ISSN Online: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v28.i5-6.180
pages 152-158

Examining Bp Modification in Neural Arrays of Different Dimensionalities

Walid A. Salameh
Dept. of Mathematical Sciences-Computer Science Branch JUST, P.O. Box 3030, Irbid-Jordan


The backpropagation neural network is the most popular network architecture. A better weight update for this learning rule would be possible if we could compensate for future changes to these weights in earlier layers. To do so, we address some modifications of the backpropagation learning algorithm that use the expected value of the source. These modifications are examined in neural arrays of different dimensionalities by means of computer simulation. A method of using these networks as pattern classifiers is proposed and simulated.

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