56 resultados para Second-order Systems Of Ordinary Differential Equations


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We consider a finite state automata based method of solving a system of linear Diophantine equations with coefficients from the set {-1,0,1} and solutions in {0,1}.

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Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

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2000 Mathematics Subject Classification: 26A33, 33C60, 44A15, 35K55

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This article presents the principal results of the doctoral thesis “Direct Operational Methods in the Environment of a Computer Algebra System” by Margarita Spiridonova (Institute of mathematics and Informatics, BAS), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 23 March, 2009.

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MSC 2010: 34A37, 34B15, 26A33, 34C25, 34K37

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2000 Mathematics Subject Classification: Primary 90C29; Secondary 90C30.

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2000 Mathematics Subject Classification: 34K15, 34C10.

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AMS subject classification: 49J52, 90C30.

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2010 Mathematics Subject Classification: 35Q15, 31A25, 37K10, 35Q58.

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2000 Mathematics Subject Classification: 62G32, 62G20.

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2000 Mathematics Subject Classification: 45G15, 26A33, 32A55, 46E15.