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Since fuzzy neural networks (FNN) have been successfully applied to classification problems, this paper proposes a principal component analysis (PCA) and linear discriminant analysis (LDA) based FNN to achieve the image classification. In PCA, it can convert a set of observations into a set of linearly uncorrelated variables called principal components. In LDA, the weights are updated by seeking directions...
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...
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