A nonlinear projection neural network for solving interval quadratic programming problems and its stability analysis.
Wu, Huaiqin, Shi, Rui, Qin, Leijie, Tao, Feng, He, Lijun (2010)
Mathematical Problems in Engineering
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Wu, Huaiqin, Shi, Rui, Qin, Leijie, Tao, Feng, He, Lijun (2010)
Mathematical Problems in Engineering
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Margaris, Athanasios, Kotsialos, Efthymios, Styliadis, Athansios, Roumeliotis, Manos (2004)
Acta Universitatis Apulensis. Mathematics - Informatics
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Piotr Szymczyk, Sylwia Tomecka-Suchoń, Magdalena Szymczyk (2015)
International Journal of Applied Mathematics and Computer Science
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In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector) are neural network inputs for automatic classification of a special kind of geologic structure-a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from...
Jiří Beneš (1990)
Kybernetika
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Joldeş, Remus, Ileană, Ioan, Olteanu, Emil (2003)
Acta Universitatis Apulensis. Mathematics - Informatics
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Krzysztof Patan (2010)
International Journal of Applied Mathematics and Computer Science
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The paper deals with a specific kind of discrete-time recurrent neural network designed with dynamic neuron models. Dynamics are reproduced within each single neuron, hence the network considered is a locally recurrent globally feedforward. A crucial problem with neural networks of the dynamic type is stability as well as stabilization in learning problems. The paper formulates local stability conditions for the analysed class of neural networks using Lyapunov's first method. Moreover,...
D. Zhang, Q. Jiang, X. Li (2005)
Mathware and Soft Computing
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This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. The forecasting...
Olteanu, Emil, Joldeş, Remus, Rotar, Corina (2004)
Acta Universitatis Apulensis. Mathematics - Informatics
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Miloš Kudělka, Šárka Zehnalová, Zdeněk Horák, Pavel Krömer, Václav Snášel (2015)
International Journal of Applied Mathematics and Computer Science
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Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. We introduce a method for measuring the strength of the relationship between two nodes of a network and for their ranking. This method is applicable to all kinds of networks, including directed and weighted networks. The approach extracts dependency relations among the network's nodes...
O. Ávila Åkerberg, M. J. Chacron (2010)
Mathematical Modelling of Natural Phenomena
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The interplay between intrinsic and network dynamics has been the focus of many investigations. Here we use a combination of theoretical and numerical approaches to study the effects of delayed global feedback on the information transmission properties of neural networks. Specifically, we compare networks of neurons that display intrinsic interspike interval correlations (nonrenewal) to networks that do not (renewal). We find that excitatory...