Computational Intelligence: Foundations and Applications, by Da Ruan, Tianrui Li, Yang Xu, Guoqing Chen, Etienne E. Kerre

By Da Ruan, Tianrui Li, Yang Xu, Guoqing Chen, Etienne E. Kerre

FLINS, initially an acronym for Fuzzy common sense and clever applied sciences in Nuclear technology, is now prolonged to Computational Intelligence for utilized learn. The contributions to the 9th within the sequence of FLINS meetings conceal state of the art study, improvement, and know-how for computational intelligence platforms -- either from foundations and functions points-of-view.

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K)(∃j) Ak (pj ) > 0. (4) Then the (discrete) F-transform of f is introduced as follows. 3. Let a function f be given at nodes p1 , . . , pl ∈ [a, b] and A1 , . . , An , n < l, be basic functions which constitute a fuzzy partition of [a, b]. We say that the n-tuple of real numbers [F1 , . . , Fn ] is the discrete F-transform of f with respect to A1 , . . , An if Fk = l j=1 f (pj )Ak (pj ) . l j=1 Ak (pj ) (5) Similarly to the integral F-transform, we may show that the components of the discrete F-transform are the weighted mean values of the given function where the weights are given by the basic functions.

Inference methods Recall the general approximate reasoning scheme: Condition: IF X is Aj THEN Y is Bj , j = 1, . . , m Observation: X is A (6) Conclusion: Y is B Elaboration of the scheme (6) depends on the interpretation of the rules (4). If the interpretation is a relation then the inference scheme provides good approximation of some function (for the details see14,16 ). The linguistic interpretation requires a special inference method — the Perception-based Logical Deduction (PbLD) which is a specific inference method dealing with the genuine meaning of evaluative linguistic expressions.

A) (b) Fig. 1. The original image “Cameraman” (a) is compressed and reconstructed by the F-transform method (picture b). 25. 3. Application of the F-Transform to Image Fusion Image fusion aims at integration complementary multiview information into one new image with the best possible quality. The term “quality” depends on the demands of specific application. , in remote sensing and in astronomy in order to achieve high spatial and spectral resolution by combining images from two sensors, one of which has high spatial resolution and the other one high spectral resolution.

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