Titlebook: Hybrid Artificial Intelligent Systems, Part I; 5th International Co Manuel Graña Romay,Emilio Corchado,M. Teresa Garci Conference proceedin

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Recognition of Turkish Vowels by Probabilistic Neural Networks Using Yule-Walker AR Method,al density of the phones obtained from speakers is estimated. Then weighted power spectrum is calculated after power spectral density of that phone is passed through a number of band pass filters. In this way, estimated power spectrums of the phones which are obtained from speakers approximate to a

Increment

A Dynamic Bayesian Network Based Structural Learning towards Automated Handwritten Digit Recognitiosification of handwritten digit characters. The structure of these models is partly inferred from the training data of each class of digit before performing parameter learning. Classification results are presented for the four described models.

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A Dual Network Adaptive Learning Algorithm for Supervised Neural Network with Contour Preserving Clnsists of two supervised neural networks running simultaneously. One is used for training data and the other is used for testing data. The accuracy of the classification is improved from the previous works by adding outpost vectors generated from prior samples. The testing function is able to test d

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Classification of Wood Pulp Fibre Cross-Sectional Shapes, and Mahalanobis Discriminant Analysis (MLDA). The discriminant analyses were applied to identify and classify several fibre cross-sectional shapes, including e.g. intact, collapsed, touching and fibrillated fibres. The discriminant analyses perform differently, giving clear indications of their sui

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model probabilistic dependence between variables. In classical bayesian networks, performing exact as well as approximate inferences are NP-Hard. Quantum circuit developed to represent bayesian network can be used to perform inference, but it is prone to quantum noise and strictly limited by the ma

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