Handwritten character recognition using the hybrid learning rule

Richard J. Wood; Michael A. Gennert

doi:10.1117/12.130847

16 December 1992 Handwritten character recognition using the hybrid learning rule

Richard J. Wood, Michael A. Gennert

Proceedings Volume 1766, Neural and Stochastic Methods in Image and Signal Processing; (1992) https://doi.org/10.1117/12.130847
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

The hybrid learning rule is a novel learning rule that combines the Hebbian learning rule and the back propagation algorithm. This novel learning rule was applied to the problem of isolated handwritten character recognition. The problem domain was limited to ten letters, which may be rotated or translated. The performance of the hybrid learning rule on this problem domain was measured and compared to the performance of the back propagation algorithm. While the hybrid learning rule failed to outperform the back propagation algorithm, it does generate receptive fields similar to those found by other researchers.

Citation Download Citation

Richard J. Wood and Michael A. Gennert "Handwritten character recognition using the hybrid learning rule", Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); https://doi.org/10.1117/12.130847

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