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Time series analysis using normalized PG-RBF network with regression weights.

, , , , , , and . Neurocomputing, 42 (1-4): 267-285 (2002)

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Analysis of the Functional Block Involved in the Design of Radial Basis Function Networks., , , , , , and . Neural Processing Letters, 12 (1): 1-17 (2000)A Quantitative Study of Fault Tolerance, Noise Immunity, and Generalization Ability of MLPs., , , , and . Neural Computation, 12 (12): 2941-2964 (2001)Assessing the Noise Immunity of Radial Basis Function Neural Networks., , , and . IWANN (2), volume 2085 of Lecture Notes in Computer Science, page 136-143. Springer, (2001)SCE Toolboxes for the Development of High-Level Parallel Applications., , , and . International Conference on Computational Science (2), volume 3992 of Lecture Notes in Computer Science, page 518-525. Springer, (2006)An Accurate Measure for Multilayer Perceptron Tolerance to Weight Deviations., , , , and . Neural Processing Letters, 10 (2): 121-130 (1999)A New Measurement of Noise Immunity and Generalization Ability for MLPs., , , , and . Int. J. Neural Syst., 9 (6): 511-521 (1999)Evaluating the impact of multiplicative input perturbations on radial basis function networks., , , , , and . ESANN, page 237-244. (2002)What are the Main Functional Block Involved in the Design of Adaptive Neuro-Fuzzy Inference Systems?, , , and . IJCNN (6), page 551-558. IEEE Computer Society, (2000)0-7695-0619-4.Advances in bioinformatics using soft-computing paradigms., , , , , , , , and . IWBBIO, page 1634-1643. Copicentro Editorial, (2014)Evolving Machine Microprograms: Application to the CODE2 Microarchitecture., , , , , , and . DCAI, volume 50 of Advances in Soft Computing, page 461-470. Springer, (2008)