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Fuzzy neural networks (FNN) have been successfully applied to classification problems. In this study, we design a FNN-based chip to achieve the face recognition of mobile-robots. The underlying notion of the proposed FNN is to split the generation of fuzzy rules into linear discriminant analysis (LDA) and Gaussian mixture model (GMM). In LDA, the weights are updated by seeking directions that are...
This paper proposes fuzzy neural networks (FNN) for speech endpoint detection. The underlying notion of the proposed FNN is to split the generation of fuzzy rules into linear discriminant analysis (LDA) and Gaussian mixture model (GMM). In LDA, the weights are updated by seeking directions that are efficient for discrimination. In GMM, the parameter learning adopts the gradient descent method to reduce...
A maximizing-discriminability-based self-organizing fuzzy network (MDSOFN) that can classify highly confusable patterns is proposed in this paper. The underlying notion of the proposed MDSOFN is to split the generation of fuzzy rules into linear discriminant analysis (LDA) and Gaussian mixture model (GMM). In LDA, the weights are updated by seeking directions that are efficient for discrimination...
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