A Bootstrap-like Rejection Mechanism for Multilayer Perceptron Networks
نویسندگان
چکیده
Multilayer perceptron networks (MLP) are investigated with respect to the problem of the detection of spurious patterns. A novel mechanism is proposed based on the ideas of boot-strapping that when incorporated into the standard MLP provides the network with the ability to continuously modifying its responses across the input space. The mechanism makes use of the outputs given by the network itself during its recall phase to improve performance in the rejection of spurious inputs, through a scheme of reinforcement of the classiication decisions taken by the network. A example of the 1 Neural Networks, Pattern Recognition and Image Processing. operation of this mechanism is shown in the classiication of handwritten characters.
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