分布参数神经网络与偏微分方程求解
DISTRIBUTED PARAMETER NEURAL NETWORKS FOR SOLVING PARTIAL DIFFERENTIAL EQUATIONS
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摘要: 本文提出一类用于求解偏微分方程的分布参数神经网络,并且在连续时空上研究了它的动态特性。最后还给出了两个模拟试验,用于检验这类神经网络的有效性。Abstract: Novel distributed parameter neural networks are proposed for solving partial differential equations, and their dynamic performances are studied in Hilbert space. The locally connected neural networks are obtained by separating distributed parameter neural networks. Two simulations are also given. Both theoretical and practical results illustrate that the distributed parameter neural networks are effective and efficient for solving partial differential equation problems.
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