Titlebook: Stochastic Differential Systems; Proceedings of the 3 Norbert Christopeit,Kurt Helmes,Michael Kohlmann Conference proceedings 1986 Springer

PED

书目名称Stochastic Differential Systems影响因子(影响力)




书目名称Stochastic Differential Systems影响因子(影响力)学科排名




书目名称Stochastic Differential Systems网络公开度




书目名称Stochastic Differential Systems网络公开度学科排名




书目名称Stochastic Differential Systems被引频次




书目名称Stochastic Differential Systems被引频次学科排名




书目名称Stochastic Differential Systems年度引用




书目名称Stochastic Differential Systems年度引用学科排名




书目名称Stochastic Differential Systems读者反馈




书目名称Stochastic Differential Systems读者反馈学科排名

吞下

senile-dementia

Stochastic maximum principle in the problem of optimal absolutely continuous change of measure,aracterized by a situation when the choice of the control determines the absolutely continuous change of some basic measure. In contrast to the case of diffusion Markov processes ([1], [2]), these equations, generally speaking, are not ordinary differential equations here. We base the derivation on

Absenteeism

A solution to the partially observed control problem of linear systems, with non-quadratic cost, a probabilistic manner -by density control method- that the partially observed control problem has a separated optimal policy amongst the admissible controls defined to be all the processes adapted to the observation‘s filtration.

使闭塞

Control of piecewise-deterministic processes via discrete-time dynamic programming,inuous. By considering the sequence of states visited by the process at its jump times, it is shown that a discounted infinite horizon control problem can be reformulated as a discrete-time Markov decision problem (the ‘positive’ case). Under certain continuity assumptions it is shown that an optima

ENNUI

使绝缘

Vsd168

Viscosity solutions in partially observed control,equation and Mortensen‘s equation was revealed. In [1] it was pointed out that the dynamic programming techniques do not give us an existence theorem (- as it would be in the completely observed case -), but it was shown that the value function is a lower bound for the solution of Mortensen‘s equati

Canyon

Filibuster

Stochastic maximum principle in the problem of optimal absolutely continuous change of measure,a non-linear equation for the martingale component of the value process ([3]) and an expression for the differential of the maximum of the semi-martingales. The method can be also applied to the case with jump components in the martingales defining measure densities, but we shall restrict ourselves by the continuous case.