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Please use this identifier to cite or link to this item: http://elib.bsu.by/handle/123456789/50782
Title: Neural Network Simulation Of Δ-Correlated Stochastic Signals
Authors: Nazarov, P. V.
Popleteev, A. M.
Lutkovski, V. M.
Apanasovich, V. V.
Keywords: ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Информатика
Issue Date: 2004
Publisher: Минск: БГУ
Abstract: Artificial neural networks (ANNs) are widely used as "black-box" models of complex processes and systems. Although the neural network simulation of deterministic processes is a well-known area, ANN simulation of stochastic ones is still at the frontier of the ANN methodology. In the current work, the method of ANN simulation of д-correlated stochastic signals is proposed. The main advantage of the scheme is the utilization of a standard multilayer perceptron instead of complex stochastic ANN structures. The network receives input parameters of simulation together with basic random values and generates the desired stochastic signal.
URI: http://elib.bsu.by/handle/123456789/50782
Appears in Collections:2004. Международная конференция “Моделирование процессов и систем”

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