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We describe in this chapter a new method for response integration in modular neural networks using type-2 fuzzy logic. The modular neural networks were used in human person recognition. Biometric authentication is used to achieve person recognition. Three biometric characteristics of the person are used: face, fingerprint, and voice. A modular neural network of three modules is used. Each module is a local expert on person recognition based on each of the biometric measures. The response integration method of the modular neural network has the goal of combining the responses of the modules to improve the recognition rate of the individual modules. We show in this chapter the results of a type-2 fuzzy approach for response integration that improves performance over type-1 fuzzy logic approaches.
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© 2007 Springer-Verlag Berlin Heidelberg
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Castillo, O., Melin, P. (2007). 6 Method for Response Integration in Modular Neural Networks with Type-2 Fuzzy Logic. In: Type-2 Fuzzy Logic: Theory and Applications. Studies in Fuzziness and Soft Computing, vol 223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76284-3_6
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DOI: https://doi.org/10.1007/978-3-540-76284-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76283-6
Online ISBN: 978-3-540-76284-3
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