Section 3 introduces the novel class of fuzzy degraded hyperellipsoidal composite neural networks (FDHECNN's). The hybrid training algorithm is given in section.
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May 31, 2005 · In most of expert systems, crisp or fuzzy if-then rules are generally derived from human experts using linguistic information. However, the ...
A neural fuzzy system learning with fuzzy training data (fuzzy if-then rules) is proposed in this paper. This system is able to process and learn numerical ...
This paper describes a neuro-fuzzy controller that can mimic the way a human controller might function. The controller comprises an artificial neural ...
Oct 20, 2016 · An architecture of a new neuro-fuzzy system is proposed. The basic idea of this approach is to tune both synaptic weights and membership ...
In this paper we propose a new self-learning complex neuro-fuzzy system (CNFS) using complex fuzzy sets (CFSs). We design a class of Gaussian complex fuzzy ...
A neural fuzzy system learning with fuzzy training data (fuzzy if-then rules) is proposed in this paper. This system is able to process and learn numerical ...
This kind of self-leaming neurefuzy system has advantages over backpropagation networks and conventional fuuy systems in the following way: (I) the learning ...
The basic idea of this approach is to tune both synaptic weights and membership functions with the help of the supervised learning and self-learning paradigms.
This paper presents a neural network-based system which is trained in such a way that it provides an appealing solution to the problem of knowledge acquisition ...