Estimation of parameters for Hilbert space-valued partially observable stochastic processes

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Zakai Equations for Hilbert Space Valued Processes*

versity A state process is described by either a discrete time Hilbert space valued process, or a stochastic differential equation in Hilbert space. The state is observed through a finite dimensional process. Using a change of measure and a Fusive theorem the Zakai equation is obtained in discrete or continuous time. A risk sensitive state estimate is also defined.

متن کامل

Rate of convergence for Hilbert space valued processes

Consider a stationary, linear Hilbert space valued process. We establish Berry-Essen type results with optimal convergence rates under sharp dependence conditions on the underlying coefficient sequence of the linear operators. The case of non-linear Bernoulli-shift sequences is also considered. If the sequence is m-dependent, the optimal rate (n/m)1/2 is reached. If the sequence is weakly geome...

متن کامل

Reconstructing Model Parameters in Partially-Observable Discrete Stochastic Systems

The analysis of partially-observable discrete stochastic systems reconstructs the unobserved behavior of real-world systems. An example for such a system is a production facility where indistinguishable items are produced by two machines in stochastically distributed time intervals and are then tested by a single quality tester. Here, the source of each defective item can be reconstructed later...

متن کامل

Learning Without State-Estimation in Partially Observable Markovian Decision Processes

Reinforcement learning RL algorithms pro vide a sound theoretical basis for building learning control architectures for embedded agents Unfortunately all of the theory and much of the practice see Barto et al for an exception of RL is limited to Marko vian decision processes MDPs Many real world decision tasks however are inherently non Markovian i e the state of the environ ment is only incomp...

متن کامل

Dynamic Programming for Partially Observable Stochastic Games

We develop an exact dynamic programming algorithm for partially observable stochastic games (POSGs). The algorithm is a synthesis of dynamic programming for partially observable Markov decision processes (POMDPs) and iterative elimination of dominated strategies in normal form games. We prove that it iteratively eliminates very weakly dominated strategies without first forming the normal form r...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Multivariate Analysis

سال: 1986

ISSN: 0047-259X

DOI: 10.1016/0047-259x(86)90026-6