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Importance Sampling for Objective Function Estimations in Neural Detector Training Driven by Genetic Algorithms.

, , , , and . Neural Process. Lett., 32 (3): 249-268 (2010)

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Basic-Evolutive Algorithms for Neural Networks Architecture Configuration and Training., and . ISCAS, page 125-130. IEEE, (1995)A comparison of criterion functions for a neural network applied to binary detection., , and . ICNN, page 329-333. IEEE, (1995)Neyman-Pearson Neural Detectors., and . IWANN (2), volume 2085 of Lecture Notes in Computer Science, page 111-118. Springer, (2001)Adaptive Importance Sampling Technique for Neural Detector Training., and . ICANN, volume 2415 of Lecture Notes in Computer Science, page 1037-1042. Springer, (2002)Optimal structures for high speed and low roundoff noise digital filters., , and . ICASSP, page 1897-1900. IEEE Computer Society, (1991)Quasi-optimum detection results using a neural network., and . ICNN, page 1929-1932. IEEE, (1996)Performance improvements for a neural network detector., , and . ICNN, page 492-495. IEEE, (1995)Comparison of a neural network detector vs Neyman-Pearson optimal detector., and . ICASSP, page 3573-3576. IEEE Computer Society, (1996)Importance Sampling Techniques in Neural Detector Training., and . ECML, volume 2167 of Lecture Notes in Computer Science, page 431-441. Springer, (2001)Performance Analysis of Neural Network Detectors by Importance Sampling Techniques., and . Neural Processing Letters, 9 (3): 257-269 (1999)