|
|
|
|
LEADER |
00000cam a22000002a 4500 |
001 |
ocm50773216 |
003 |
OCoLC |
005 |
20150815141129.0 |
008 |
051013s2003 njua 00 eng d |
035 |
|
|
|a (Sirsi) i9780471330523
|
040 |
|
|
|a DLC
|c DLC
|d UV#
|
020 |
|
|
|a 0471330523
|
042 |
|
|
|a pcc
|
050 |
|
4 |
|a QA274
|b S62
|
082 |
0 |
0 |
|a 519.2
|2 21
|
100 |
1 |
|
|a Spall, James C.
|9 369904
|
245 |
1 |
0 |
|a Introduction to stochastic search and optimization :
|b estimation, simulation, and control /
|c James C. Spall.
|
260 |
|
|
|a Hoboken, N.J. :
|b Wiley-Interscience,
|c c2003.
|
300 |
|
|
|a xx, 595 p. :
|b il. ;
|c 26 cm.
|
490 |
0 |
0 |
|a Wiley-Interscience series in discrete mathematics and optimization
|
504 |
|
|
|a Bibliografía: p. 558-579.
|
505 |
0 |
|
|a Stochastic search and optimization : motivation and supporting results -- Direct methods for stochastic search -- Recursive estimation for linear models -- Stochastic approximation for nonlinear root-finding -- Stochastic gradient form of stochastic approximation -- Stochastic approximation and the finite-difference method -- Simultaneous perturbation stochastic approximation -- Annealing-type algorithms -- Evolutionary computation I : genetic algorithms -- Evolutionary computation II : general methods and theory -- Reinforcement learning via temporal differences -- Statistical methods for optimization in discrete problems -- Model selection and statistical information -- Simulation-based optimization I : regeneration, common random numbers, and selection methods -- Simulation-based optimization II : stochastic gradient and sample path methods -- Markov chain Monte Carlo -- Optimal design for experimental inputs.
|
650 |
|
4 |
|a Procesos estocásticos.
|9 4569
|
650 |
|
4 |
|a Teoría de la búsqueda.
|9 357896
|
650 |
|
4 |
|a Optimización matemática.
|
902 |
|
|
|a DGBUV
|
901 |
|
|
|a Z0
|b UV#
|
596 |
|
|
|a 2
|
942 |
|
|
|c LIBRO
|6 _
|
999 |
|
|
|c 185386
|d 185386
|