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02_-_Week_-_03_y_04_Fuzzy_sets_2_y_Operaciones_

02_-_Week_-_03_y_04_Fuzzy_sets_2_y_Operaciones_ - Fuzzy...

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Unformatted text preview: Fuzzy Membership Functions Fuzzy Operations Fuzzy Union Fuzzy Intersection Fuzzy Complement CSCI3406 Fuzzy Logic Week 3 (17/10/2005) Week 4 (24/10/2005) Some info for LAB • Work on an m-file (open m-file for each task, write your programme, save the file (e.g., lab2task1), then execute the file. Now, this file has become a function in MATLAB) (see the first week’s slides - Week 1 ) • Use help < help < function function > > (e.g., help newfis) If you don’t know how to use the function. It gives you information about how to use the function and what parameters it requires Fuzzy Membership Functions • One of the key issues in all fuzzy sets is how to determine fuzzy membership functions • The membership function fully defines the fuzzy set • A membership function provides a measure of the degree of similarity of an element to a fuzzy set • Membership functions can take any form, but there are some common examples that appear in real applications • Membership functions can – either be chosen by the user arbitrarily, based on the user’s experience (MF chosen by two users could be different depending upon their experiences, perspectives, etc.) – Or be designed using machine learning methods (e.g., artificial neural networks, genetic algorithms, etc.) • There are different shapes of membership functions; triangular, trapezoidal, piecewise-linear, Gaussian, bell-shaped, etc. • Triangular membership function – a, b and c represent the x coordinates of the three vertices of µ A ( x ) in a fuzzy set A (a: lower boundary and c: upper boundary where membership degree is zero, b: the centre where membership degree is 1) ≥ ≤ ≤-- ≤ ≤-- ≤ = c x if c x b if b c x c b x a if a b a x a x if x A ) ( μ a b c x µ A ( x ) 1 •...
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02_-_Week_-_03_y_04_Fuzzy_sets_2_y_Operaciones_ - Fuzzy...

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