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Titlebook: Neural Networks and Fuzzy Systems; Theory and Applicati Shigeo Abe Book 1997 Springer Science+Business Media New York 1997 classification.c

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楼主: Limbic-System
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Multilayered Networks,ork. Then we clarify the advantages and disadvantages of the network and discuss methods for overcoming these disadvantages while evaluating its performance for some applications: determination of the optimal structure; synthesis of the network for pattern classification; extraction of a pattern cla
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Overview of Fuzzy Systems,oximating real controlled objects by models because of the vagueness or fuzziness of the controlled objects. In addition, since most control theory is based on linear systems, it is difficult to develop control systems with good performance when real controlled objects have strong nonlinearlity.
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Fuzzy Rule Extraction for Pattern Classification from Numerical Data,ided in advance as discussed in Chapter 5, tuning of fuzzy rules by numerical data is important to improve recognition performance. In this chapter, instead of dividing the input space in advance, we discuss various fuzzy classifiers, in which first the class regions are dynamically approximated usi
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Fuzzy Rule Extraction for Function Approximation from Numerical Data,n classification discussed in Chapter 6. The first type is based on clustering of the input space [7.1]. Namely, first we divide the output space and consider each divided interval as a class. Then we divide the training data into classes according to the output values of the training data, and extr
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Composite Systems,ance obtained by using the conventional methods. But if we want to enhance performance, or if we want to automate the system which is controlled by human operators, it is usually difficult to do so using a single neural network or fuzzy system. In this situation, a combination of multiple neural net
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Overview of Neural Networks,ional computers are not suited. Here . is added to stress that the research is based on simulating human brains by computers. Hereafter neural network means an artificial neural network and . means an artificial neuron.
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