A Sensitivity-Based Improving Learning Algorithm for Madaline Rule II

Shuiming Zhong, Yu Xue, Yunhao Jiang, Yuanfeng Jin, Jing Yang, Ping Yang, Yuan Tian and Mznah Al-Rodhaan

Mathematical Problems in Engineering, 2014, vol. 2014, 1-8

Abstract:

This paper proposes a new adaptive learning algorithm for Madalines based on a sensitivity measure that is established to investigate the effect of a Madaline weight adaptation on its output. The algorithm, following the basic idea of minimal disturbance as the MRII did, introduces an adaptation selection rule by means of the sensitivity measure to more accurately locate the weights in real need of adaptation. Experimental results on some benchmark data demonstrate that the proposed algorithm has much better learning performance than the MRII and the BP algorithms.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:219679

DOI: 10.1155/2014/219679

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