Structure identification of fuzzy model
Fuzzy Sets and Systems
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
International Journal of Approximate Reasoning
Neuro-linguistic approach to pattern recognition
Fuzzy Sets and Systems
Neuro-fuzzy reasoning for occluded object recognition
Fuzzy Sets and Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-dimensional fuzzy reasoning
Fuzzy Sets and Systems
A quadratic programming approach in estimating similarity relations
IEEE Transactions on Fuzzy Systems
Neural networks designed on approximate reasoning architecture and their applications
IEEE Transactions on Neural Networks
Design of adaptive fuzzy model for classification problem
Engineering Applications of Artificial Intelligence
Speaker verification using combinational features and adaptive neuro-fuzzy inference systems
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
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To tackle the pattern classification problems first we give a new interpretation to the multidimensional fuzzy implication (MFI). This new interpretation of MFI is used for multidimensional fuzzy reasoning (MFR) for pattern classification. We realize the new interpretation through multilayer perceptron. The learning scheme of the network is based on genetic algorithm (GA). A weight smoothing scheme is also proposed to improve neural network's generalization capability. The smoothing constraint is incorporated into the objective function of the network to reflect the neighborhood correlation and to seek those solutions which have smooth connection weights. At the learning stage of the neural network fuzzy linguistic statements have been used. Once learned, the nonfuzzy features of a pattern can be classified using a fuzzy masking. The performance of the proposed scheme is tested through synthetic data. Finally, we apply the proposed scheme to the vowel recognition problem of one Indian language.