000			04343nam a22003615i 4500
001			292098
003			MX-SnUAN
005			20160429154937.0
007			cr nn 008mamaa
008			150903s2006 xxk| o |||| 0|eng d
020			_a9781846280955 _99781846280955
024	7		_a10.1007/b138725 _2doi
035			_avtls000343643
039		9	_a201509031102 _bVLOAD _c201405070514 _dVLOAD _y201402061201 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
100	1		_aCalafiore, Giuseppe. _eeditor. _9315553
245	1	0	_aProbabilistic and Randomized Methods for Design under Uncertainty / _cedited by Giuseppe Calafiore, Fabrizio Dabbene.
264		1	_aLondon : _bSpringer London, _c2006.
300			_axiii, 457 páginas 21 ilustraciones _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aChance-Constrained and Stochastic Optimization -- Scenario Approximations of Chance Constraints -- Optimization Models with Probabilistic Constraints -- Theoretical Framework for Comparing Several Stochastic Optimization Approaches -- Optimization of Risk Measures -- Robust Optimization and Random Sampling -- Sampled Convex Programs and Probabilistically Robust Design -- Tetris: A Study of Randomized Constraint Sampling -- Near Optimal Solutions to Least-Squares Problems with Stochastic Uncertainty -- The Randomized Ellipsoid Algorithm for Constrained Robust Least Squares Problems -- Randomized Algorithms for Semi-Infinite Programming Problems -- Probabilistic Methods in Identification and Control -- A Learning Theory Approach to System Identification and Stochastic Adaptive Control -- Probabilistic Design of a Robust Controller Using a Parameter-Dependent Lyapunov Function -- Probabilistic Robust Controller Design: Probable Near Minimax Value and Randomized Algorithms -- Sampling Random Transfer Functions -- Nonlinear Systems Stability via Random and Quasi-Random Methods -- Probabilistic Control of Nonlinear Uncertain Systems -- Fast Randomized Algorithms for Probabilistic Robustness Analysis.
520			_aIn many engineering design and optimization problems, the presence of uncertainty in the data is a central and critical issue. Different fields of engineering use different ways to describe this uncertainty and adopt a variety of techniques to devise designs that are at least partly insensitive or robust to uncertainty. Probabilistic and Randomized Methods for Design under Uncertainty examines uncertain systems in control engineering and general decision or optimization problems for which data is not known exactly. Gathering contributions from the world’s leading researchers in optimization and robust control; this book highlights the interactions between these two fields, and focuses on new randomised and probabilistic techniques for solving design problems in the presence of uncertainty: Part I describes general theory and solution methodologies for probability-constrained and stochastic optimization problems, including chance-constrained optimization, stochastic optimization and risk measures; Part II focuses on numerical methods for solving randomly perturbed convex programs and semi-infinite optimization problems by probabilistic techniques such as constraint sampling and scenario-based optimization; Part III details the theory and applications of randomized techniques to the analysis and design of robust control systems. Probabilistic and Randomized Methods for Design under Uncertainty will be of interest to researchers, academics and postgraduate students in control engineering and operations research as well as professionals working in operations research who are interested in decision-making, optimization and stochastic modeling.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aDabbene, Fabrizio. _eeditor. _9315554
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9781846280948
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b138725 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c292098 _d292098