A New Method for Response Integration in Modular Neural Networks using Type-2 Fuzzy Logic for Biometric Systems

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 applied to 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 the results of a type-2 fuzzy logic approach for response integration that improves performance over type-1 fuzzy logic approaches.