A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems

被引：6

作者：

Urias, Jerica ^{[1
]}

Hidalgo, Denisse ^{[1
]}

Melin, Patricia ^{[1
]}

Castillo, Oscar ^{[1
]}

机构：

[1] Tijuana Inst Technol, Tijuana, Mexico

来源：

ANALYSIS AND DESIGN OF INTELLIGENT SYSTEMS USING SOFT COMPUTING TECHNIQUES | 2007年 / 41卷

关键词：

D O I：

10.1007/978-3-540-72432-2_2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We describe in this paper 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 paper results of a type-2 fuzzy approach for response integration that improves performance over type-1 fuzzy logic approaches.

引用

页码：5 / +

页数：2

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