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2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES '95)
Error Estimation and Error Bounds for Neural Networks
Dunedin, New Zealand
November 20-November 23
ISBN: 0-8186-7174-2
Hualou Liang, Chinese Academy of Sciences
Guiliang Dai, Chinese Academy of Sciences
A method is proposed to estimate the standard error of predicted values in multilayer perceptron(MLP). It is based on likelihood theory. It holds for all feedforward networks, irrespective of the topology or the specific task at hand. In addition, the bounds on a neural network with perturbed weights and inputs is analytically derived. The bounds obtained are applicable to both digital and analog network implementations. By computer simulation, the validity of the proposed methods has been illustrated.
Index Terms:
Neural network, Error estimation, Error bounds
Citation:
Hualou Liang, Guiliang Dai, "Error Estimation and Error Bounds for Neural Networks," annes, pp.42, 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES '95), 1995
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