Martin D. Emmerson

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We investigate empirically the performance under damage conditions of single- and multilayer perceptrons (MLP's), with various numbers of hidden units, in a representative pattern-recognition task. While some degree of graceful degradation was observed, the single-layer perceptron was considerably less fault tolerant than any of the multilayer perceptrons,(More)
The in uence of the activation function on fault tolerance property of the feedforward neural networks is empirically investigated. The simulation results show that the activation function largely in uences the fault tolerance and the generalization property of neural networks. The neural networks with symmetric sigmoid activation function is largely fault(More)
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