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Process Neural Networks: Theory and Applications


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Process Neural Networks - Theory and Applications proposes the concept and model of a process neural network for the first time, showing how it expands the mapping relationship between the input and output of traditional neural networks, and enhancing the expression capability for practical problems, with broad applicability to solving problems relating to process in practice. Some theoretical problems such as continuity, functional approximation capability, and computing capability, are strictly proved. The application methods, network construction principles, and optimization algorithms of process neural networks in practical fields, such as nonlinear time-varying system modeling, process signal pattern recognition, dynamic system identification, and process forecast, are introduced in detail. There are rich illustrations for information processing flow and the mapping relationship between inputs and outputs of process neural networks.Xingui He and Shaohua Xu are professors at the School of Electronic Engineering and Computer Science of Peking University.
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美金:179.00
Process Neural Networks: Theory and Applications

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