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By defining fuzzy valued simple functions and giving L1(μ) approximations of fuzzy valued integrably bounded functions by such simple functions, the paper analyses by L1(μ)-norm the approximation capability of four-layer feedforward regular fuzzy neural networks to the fuzzy valued integrably bounded function F : Rn → FcO(R). That is, if the transfer functionσ: R→R is non-polynomial and integrable function on each finite interval, F may be innorm approximated by fuzzy valued functions defined as to anydegree of accuracy. Finally some real examples demonstrate the conclusions.
By defining fuzzy valued simple functions and giving L1 (μ) approximations of fuzzy valued integrities bounded functions by such simple functions, the paper analyzes by L1 (μ) -norm the approximation capabilities of four-layer feedforward regular fuzzy neural networks to the fuzzy valued Integral bounded function F: Rn → FcO (R). That is, if the transfer functionσ: R → R is non-polynomial and integrable function on each finite interval, F may be innorm approximated by fuzzy valued functions defined as to any degree of accuracy Finally some real examples demonstrate the conclusions.