Fuzzy transform from a neural network point of view
نویسندگان
چکیده
The paper deals with the F-transform technique which was introduced as a method for an approximate representation of continuous functions which is appropriate for many applications. In the terminology of neural networks, the F-transform uses so called off-line (batch) learning. However, for certain applications an on-line (incremental) learning algorithm has to be implemented. We study the F-transform from a neural network point of view and introduce an on-line learning based on the gradient descent method. Moreover, we introduce an on-line algorithm tuning the fuzzy partition used in the F-transform method.
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