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Results: 1-14 |
Results: 14
ANALOG COMPUTATION WITH DYNAMICAL-SYSTEMS
Authors: SIEGELMANN HT FISHMAN S
Citation: Ht. Siegelmann et S. Fishman, ANALOG COMPUTATION WITH DYNAMICAL-SYSTEMS, Physica. D, 120(1-2), 1998, pp. 214-235
COMPUTATIONAL CAPABILITIES OF RECURRENT NARX NEURAL NETWORKS
Authors: SIEGELMANN HT HORNE BG GILES CL
Citation: Ht. Siegelmann et al., COMPUTATIONAL CAPABILITIES OF RECURRENT NARX NEURAL NETWORKS, IEEE transactions on systems, man and cybernetics. Part B. Cybernetics, 27(2), 1997, pp. 208-215
MULTIPROCESSOR DOCUMENT ALLOCATION - A GENETIC ALGORITHM APPROACH
Authors: FRIEDER O SIEGELMANN HT
Citation: O. Frieder et Ht. Siegelmann, MULTIPROCESSOR DOCUMENT ALLOCATION - A GENETIC ALGORITHM APPROACH, IEEE transactions on knowledge and data engineering, 9(4), 1997, pp. 640-642
A NOVEL NEURAL SYMBOLIC HYBRID APPROACH TO HEURISTICALLY OPTIMIZED FUEL ALLOCATION AND AUTOMATED REVISION OF HEURISTICS IN NUCLEAR-ENGINEERING/
Authors: SIEGELMANN HT NISSAN E GALPERIN A
Citation: Ht. Siegelmann et al., A NOVEL NEURAL SYMBOLIC HYBRID APPROACH TO HEURISTICALLY OPTIMIZED FUEL ALLOCATION AND AUTOMATED REVISION OF HEURISTICS IN NUCLEAR-ENGINEERING/, Advances in engineering software, 28(9), 1997, pp. 581-592
THE COMPLEXITY OF LANGUAGE RECOGNITION BY NEURAL NETWORKS
Authors: SIEGELMANN HT GILES CL
Citation: Ht. Siegelmann et Cl. Giles, THE COMPLEXITY OF LANGUAGE RECOGNITION BY NEURAL NETWORKS, Neurocomputing, 15(3-4), 1997, pp. 327-345
COMPUTATIONAL POWER OF NEURAL NETWORKS - A CHARACTERIZATION IN TERMS OF KOLMOGOROV COMPLEXITY
Authors: BALCAZAR JL GAVALDA R SIEGELMANN HT
Citation: Jl. Balcazar et al., COMPUTATIONAL POWER OF NEURAL NETWORKS - A CHARACTERIZATION IN TERMS OF KOLMOGOROV COMPLEXITY, IEEE transactions on information theory, 43(4), 1997, pp. 1175-1183
THE DYNAMIC UNIVERSALITY OF SIGMOIDAL NEURAL NETWORKS
Authors: KILIAN J SIEGELMANN HT
Citation: J. Kilian et Ht. Siegelmann, THE DYNAMIC UNIVERSALITY OF SIGMOIDAL NEURAL NETWORKS, Information and computation, 128(1), 1996, pp. 48-56
RECURRENT NEURAL NETWORKS AND FINITE AUTOMATA
Authors: SIEGELMANN HT
Citation: Ht. Siegelmann, RECURRENT NEURAL NETWORKS AND FINITE AUTOMATA, Computational intelligence, 12(4), 1996, pp. 567-574
THE SIMPLE DYNAMICS OF SUPER TURING THEORIES
Authors: SIEGELMANN HT
Citation: Ht. Siegelmann, THE SIMPLE DYNAMICS OF SUPER TURING THEORIES, Theoretical computer science, 168(2), 1996, pp. 461-472
ANALOG COMPUTATIONAL POWER - REPLY
Authors: SIEGELMANN HT
Citation: Ht. Siegelmann, ANALOG COMPUTATIONAL POWER - REPLY, Science, 271(5247), 1996, pp. 373-373
ON THE COMPLEXITY OF TRAINING NEURAL NETWORKS WITH CONTINUOUS ACTIVATION FUNCTIONS
Authors: DASGUPTA B SIEGELMANN HT SONTAG E
Citation: B. Dasgupta et al., ON THE COMPLEXITY OF TRAINING NEURAL NETWORKS WITH CONTINUOUS ACTIVATION FUNCTIONS, IEEE transactions on neural networks, 6(6), 1995, pp. 1490-1504
COMPUTATION BEYOND THE TURING LIMIT
Authors: SIEGELMANN HT
Citation: Ht. Siegelmann, COMPUTATION BEYOND THE TURING LIMIT, Science, 268(5210), 1995, pp. 545-548
ON THE COMPUTATIONAL POWER OF NEURAL NETS
Authors: SIEGELMANN HT SONTAG ED
Citation: Ht. Siegelmann et Ed. Sontag, ON THE COMPUTATIONAL POWER OF NEURAL NETS, Journal of computer and system sciences, 50(1), 1995, pp. 132-150
ANALOG COMPUTATION VIA NEURAL NETWORKS
Authors: SIEGELMANN HT SONTAG ED
Citation: Ht. Siegelmann et Ed. Sontag, ANALOG COMPUTATION VIA NEURAL NETWORKS, Theoretical computer science, 131(2), 1994, pp. 331-360
Risultati: 1-14 |