Abstract
In this paper, we try to analyze several conventional neuro-fuzzy learning algorithms, which are widely used in recent fuzzy applications for tuning fuzzy rules, and give a summarization of their properties in detail. Some of these properties show that the uses of the conventional neuro-fuzzy learning algorithms are difficult or inconvenient sometimes for constructing an optimal fuzzy system model in practical fuzzy applications.
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