A Bayesian method of estimating the power spectra of stationary random processes is proposed. Initially we estimate the true spectra via the log pe-riodogram but due to the inadequacies of the periodogram when the true spectrum has a high dynamic range and/or is rapidly varying for such problems we use the multitaper spectrum estimates which have known error distributions. Piecewise polynomials...

in this paper, we study the existence of generalized solutions for the infinite dimensional nonlinear stochastic differential inclusions $dx(t) in f(t,x(t))dt +g(t,x(t))dw_t$ in which the multifunction $f$ is semimonotone and hemicontinuous and the operator-valued multifunction $g$ satisfies a lipschitz condition. we define the it^{o} stochastic integral of operator set-valued stochastic pr...

Dynamic Bayesian networks (DBNs) are a powerful and exible methodology for representing and computing with probabilistic models of stochastic processes. In the past decade, there has been increasing interest in applying them to practical problems, and this thesis shows that they can be used eeectively in the eld of automatic speech recognition. A principle characteristic of dynamic Bayesian net...

An alternative approach towards dynamic programming (DP) is presented: Recursions. A basic deterministic model and solution function are defined and the model is generalized to include stochastic processes, with the traditional stochastic DP model as a special case. Heuristic rules are included in the models simply as restrictions on decision spaces and a small slaughter pig marketing planning ...

An alternative approach towards dynamic programming (DP) is presented: Recursions. A basic deterministic model and solution function are defined and the model is generalized to include stochastic processes, with the traditional stochastic DP model as a special case. Heuristic rules are included in the models simply as restrictions on decision spaces and a small slaughter pig marketing planning ...

Larson, B.A., 1992. Principles of stochastic dynamic optimization in resource management: the continuous-time case. Agric. Econ., 7: 91-107. A wide range of problems in economics, agriculture, and natural resource management have been analyzed using continuous-time optimal control models, where the state variables change over time in a stochastic manner. Using a firm-level investment model and ...

in this research, both resource allocation and reactive resource allocation problems in multi-server dynamic pert networks are analytically modeled, where new projects are expected to arrive according to a poisson process, and activity durations are also known as independent random variables with exponential distributions. such system is represented as a queuing network, where multi servers at ...