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In [16], complexity has been considered as a subjective characteristic that is represented by a fuzzy interpretation of edges in an image.
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A fuzzy set interpretation is incorporated into the network design to handle imprecise information.
Next, a fuzzy system based on logical interpretation of if then rules and with parametric conclusions is presented.
The following examples are given to illustrate a possible interpretation of the previous conditions in order to study the dynamic of a fuzzy system that can appear in fuzzy decision making.
A probability interpretation of the above notions is as follows: a set Ω is the set of elementary events; a fuzzy set from the system M is a fuzzy event; the value (m(f)) is the probability of a fuzzy event f; a fuzzy event (f') is the opposite event to a fuzzy event f; and weakly separated fuzzy events are interpreted as mutually exclusive events.
A fuzzy dog seeks inspiration.
He walks a fuzzy line.
It's a fuzzy path.
That is a fuzzy forecast.
A fuzzy sameness blurs the descriptions.
But Daume is a fuzzy, uninteresting figure.
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