Titlebook: Electrical Engineering and Intelligent Systems; Sio-Iong Ao,Len Gelman Book 2013 Springer Science+Business Media, LLC 2013 Computational I

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https://doi.org/10.1007/978-3-322-83664-9of feature extraction, ROI is divided into a suitable number of nonoverlapping windows of different sizes. Three types of features, viz. Sigmoid, energy, and entropy features, are extracted. These three sets of features are used for the authentication of users using Euclidean distance and support vector machine (SVM) as the classifiers.

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Partial Exploration of State Spaces and Hypothesis Test for Unsuccessful Search,ble of generating the result of a random sampling for the case when a metric in each state is assumed to be normally distributed. It is designed for the case of unsuccessful search, for using a hypothesis test and providing completeness in the analysis.

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Sio-Iong Ao,Len GelmanCovers recent advances in robot navigation and task allocation in robot teams.Discusses detector for color images and using pattern substitution.Presents research on fuzzy nets, fuzzy optimization, an

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Lecture Notes in Electrical Engineeringhttp://image.papertrans.cn/e/image/305726.jpg

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Duality in Complex Stochastic Boolean Systems,to the 2. binary .-tuples .of 0s and 1s. In this paper, different duality properties of the intrinsic order graph are rigorously analyzed in detail. The results can be applied to many CSBSs arising from any scientific, technical, or social area.

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Learning of Type-2 Fuzzy Logic Systems by Simulated Annealing with Adaptive Step Size,t parts of the rules for a Mamdani model. Simulated annealing is combined with a method to reduce the computations associated with it using adaptive step sizes. The results of the proposed methods are compared to results of a type-1 fuzzy logic system (T1FLS).

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Besteuerung der Unternehmensleistungen, being reasoned by the meta-interpreter, which provides a query answering mechanism to infer information. A comparative study of related works has revealed a merit of the meta-logical representation approach that separates the meta level knowledge from the object level one.

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