Titlebook: Soft Computing and Fractal Theory for Intelligent Manufacturing; Oscar Castillo,Patricia Melin Book 2003 Springer-Verlag Berlin Heidelberg

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Type-2 Fuzzy Logic, type-2 fuzzy sets. We can say that type-2 fuzzy logic is a generalization of conventional fuzzy logic (type-1) in the sense that uncertainty is not only limited to the linguistic variables but also is present in the definition of the membership functions.

stratum-corneum

Unsupervised Learning Neural Networks,ome detail competitive learning networks, Kohonen self-organizing networks, learning vector quantization, and Hopfield networks. We will also show some examples of these networks to illustrate their possible application in solving real-world problems.

學(xué)術(shù)討論會

Adaptive Control of Non-Linear Plants,the parameters of the fuzzy system for control. A specific non-linear plant is used to test the hybrid approach for adaptive control. A particular stepping motor was used as test bed in the experiments. The results of the neuro-fuzzy approach were good, both in accuracy and efficiency.

Interregnum

anesthesia

Type-1 Fuzzy Logic,pe-2 fuzzy sets as well as their operations will be discussed in the next chapter. For this reason, in this chapter we will focus only on type-1 fuzzy logic. Since research on fuzzy set theory has been underway for over 30 years now, it is practically impossible to cover all aspects of current devel

PHAG

Type-2 Fuzzy Logic,s a set in which we also have uncertainty about the membership function. Of course, type-2 fuzzy systems consist of fuzzy if-then rules, which contain type-2 fuzzy sets. We can say that type-2 fuzzy logic is a generalization of conventional fuzzy logic (type-1) in the sense that uncertainty is not o

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