Volterra characterization of neural networks
Volterra characterization of neural networks
复制标题
神经网络的 Volterra 表征
DOI：
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发表时间：
1991
期刊：
影响因子：
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通讯作者：
H. Meadows
中科院分区：
文献类型：
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作者：
N. Hakim;J. J. Kaufman;G. Cerf;H. Meadows
分析了非线性系统的Volterra理论在神经网络中的应用。给出了单隐层前馈神经网络和递归神经网络的Volterra核的有效计算公式。作者还讨论了递归神经网络结构的函数表示问题，并描述了一类可以用该模型逼近的系统。计算机模拟结果表明，神经网络的Volterra展开式特征在最优结构选择和学习与泛化的评估中是有用的。
The authors analyze the application of the Volterra theory of nonlinear systems to neural networks. Expressions for efficiently computing the Volterra kernels of both a single hidden layer feedforward neural network and a recurrent one are presented. The authors also address the issue of functional representation of the recurrent neural network architecture and delineate a class of systems that can be approximated by this model. Computer simulations are also presented which indicate that neural networks characterization by their Volterra expansion may be useful in optimal architecture selection and assessment of learning and generalization.<<ETX>>