Titlebook: Adaptive and Natural Computing Algorithms; 8th International Co Bartlomiej Beliczynski,Andrzej Dzielinski,Bernarde Conference proceedings 2

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https://doi.org/10.1007/978-3-662-38375-9 error and support vector (SV) classifiers. Unfortunately, both classifiers cannot be obtained automatically in multi-category case. We suggest designing .(.-1)/2 pair-wise SLPs and combine them in a special way. Experiments using .=24 class chromosome and .=10 class yeast infection data illustrate

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Gait and Stance Control System,f Data Handling (GMDH) neural network. The main objective is to show how to employ the Least Mean Square (LMS) and the Outer Bounding Ellipsoid (OBE) algorithm to obtain the corresponding model uncertainty.

HALL

https://doi.org/10.1007/978-3-319-30022-1an architecture based on the fast cosine transform, type II and IV are built and applied for extraction of features used as a classification base for a multilayer perceptron. The results of the tests show that adaptation of the neural network allows to obtain a better transform in the feature extrac

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https://doi.org/10.1007/978-3-319-30022-1 carried out in the visual cortex. The visual cortex for the movement detection, consist of two layered networks, called the primary visual cortex (V1),followed by the middle temporal area (MT), in which nonlinear functions will play important roles in the visual systems. These networks will be deco

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https://doi.org/10.1007/978-94-011-7376-6ion scheme. We prove that each subsequent Hermite function extends frequency bandwidth of the approximator within limited range of well concentrated energy. By introducing a scalling parameter we may control that bandwidth.

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Control of Microorganisms by Destruction,nowledge this kind of research has not been reported until know. We give formal conditions under which the memory is still able to correctly recall a pattern of the fundamental set of patterns either from a non-altered or a noisy version of it. Experiments are also given to show the efficiency of th

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Questions, Answers and Theories introduce some new terms and concepts to define the ., and we show the procedure of constructing the .. We then describe a new method . (Learning based on Associative Frequent Network) for mining frequent itemsets and potentially patterns, which are considered as a useful pattern logically over the

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Studies in Comparative Politicshe theory, structure and learning principles of the network proposed were all described. Further chapters include the application of a system of two proposed neural networks for the solution of a two-dimensional Euclides’ travelling salesman problem. The feature of the neural network system proposed