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140122 ||| eng |
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|a 9783540470151
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| 100 |
1 |
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|a Rozovskii, Boris L.
|e [editor]
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| 245 |
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|a Stochastic Partial Differential Equations and Their Applications
|h Elektronische Ressource
|b Proceedings of IFIP WG 7/1 International Conference University of North Carolina at Charlotte, NC, June 6–8,1991
|c edited by Boris L. Rozovskii, Richard B. Sowers
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| 250 |
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|a 1st ed. 1992
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 1992, 1992
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| 300 |
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|a VIII, 255 p. 2 illus
|b online resource
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| 505 |
0 |
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|a Nonstationary anderson model with lévy potential -- Stochastic partial differential equations in control of structures -- Splitting up method in the context of stochastic pde -- Generalized stochastic differential equations on (D*) -- On invariant measure for semilinear equations with dissipative nonlinearities -- Random conservation laws and global solutions of nonlinear SPDE application to the HJB SPDE of anticipative control -- Stochastic calculus with anticipation and shift transformations of wiener's measure -- A propos d'un exemple d'équation différentielle stochastique en dimension infinie -- Stochastic evolution equations with non-coercive monotone operators -- Existence of a smooth density for the filter in nonlinear filtering on manifolds -- On the itô formula for two-parameter martingales -- Central limit theorem results for a reaction-diffusion equation with fast-oscillating boundary perturbations -- On the stochastic partial differential equations of Ginzburg-Landau type -- Stochastic variational calculus -- A nuclear space-valued stochastic differential equation driven by poisson random measures -- Random vortex models and stochastic partial differential equations -- On explicit formulas for solutions of evolutionary SPDE's (a kind of introduction to the theory) -- Convolution and fourier transform of hida distributions -- Splitting-up approximation for SPDE's and SDE's with application to nonlinear filtering -- Representation and approximation of martingale measures -- Backward stochastic differential equations and quasilinear parabolic partial differential equations -- Lyapunov exponent of a stochastic wave equation -- On stochastic elliptic boundary value problems associated with gaussian markov random fields -- White noise methods for stochastic partial differentialequations
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| 653 |
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|a Control, Robotics, Automation
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| 653 |
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|a Calculus of Variations and Optimization
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| 653 |
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|a Control theory
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| 653 |
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|a Systems Theory, Control
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| 653 |
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|a System theory
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| 653 |
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|a Control engineering
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| 653 |
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|a Robotics
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| 653 |
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|a Mathematical optimization
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| 653 |
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|a Automation
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| 653 |
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|a Calculus of variations
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| 700 |
1 |
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|a Sowers, Richard B.
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
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|a Lecture Notes in Control and Information Sciences
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| 028 |
5 |
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|a 10.1007/BFb0007313
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| 856 |
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|u https://doi.org/10.1007/BFb0007313?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 629.8
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| 520 |
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|a This volume consists of 24 papers submitted for publication by the invited speakers of the IFIP International Conference on Stochastic Partial Differential Equations and their Ap- plications. Most of them are research papers, however, a few surveys written by world renowed experts are also included. The aim of the conference was to bring together mathematici- ans, physicists and engineers representing academic as well as industrial fields, interested in the theory and applica- tions of SPDE's. The field of SPDE's is one of the most dy- namically developing areas at the cross roads of several sciences. It is especially attractive for many because of its interdisciplinary character and enormous richness ofal- ready existing as well as potential applications. There were about one hundred participants registered for the conferen- ce. With rare exceptions, all of the most active researchers in the field of SPDE's throughout the world were present at the conference. The main topics for discussion at the confe- rence were: non-linear SPDE's and Markov property for random fields, modern stochastic calculuses, numerical and asympto- tic methods for SPDE's, applications of SPDE's with emphasis onnon-linear filtering, stochastic control and statistical fluid dynamics
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