Structure of Fuzzy Control Module with Neural Network

The paper deals with the fuzzy control module's structure, which has the property that is deficit in "conventional" uncertain systems -the skill to learn. This is attained by offering the control module in the form of a neural-like multilayer network. At the same time, this system is free from the main disadvantage of neural networks -the knowledge distribution. All parameters and weights retain their physical understanding, which makes it likely to examine the information gathered by the system in the process of learning.

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