Design of Sigmoid Activation Functions for Fuzzy Cognitive Maps via Lyapunov Stability Analysis

Fuzzy cognitive maps (FCMs) are used to support decision-making, and the decision processes are performed by inference of FCMs. The inference greatly depends on activation functions such as sigmoid function, hyperbolic tangent function, step function, and threshold linear function. However, the sigm...

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Bibliographic Details
Published inIEICE Transactions on Information and Systems Vol. E93.D; no. 10; pp. 2883 - 2886
Main Authors LEE, In Keun, KWON, Soon Hak
Format Journal Article
LanguageEnglish
Published The Institute of Electronics, Information and Communication Engineers 2010
Subjects
activation function
fuzzy cognitive map
Lyapunov stability analysis
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Summary:Fuzzy cognitive maps (FCMs) are used to support decision-making, and the decision processes are performed by inference of FCMs. The inference greatly depends on activation functions such as sigmoid function, hyperbolic tangent function, step function, and threshold linear function. However, the sigmoid functions widely used for decision-making processes have been designed by experts. Therefore, we propose a method for designing sigmoid functions through Lyapunov stability analysis. We show the usefulness of the proposed method through the experimental results in inference of FCMs using the designed sigmoid functions.
ISSN:0916-8532
1745-1361
DOI:10.1587/transinf.E93.D.2883