Optimality results for dividend problems in insurance.
Optimisation stochastique : méthodes de descente
Optimization of consumption with partial observation-Jensen inequality method
A solution to a model of optimal consumption with partial observation considered in [LOS] is presented. The approach is based on the Jensen inequality and does not require application of the filtering equation.
Optimization of Discrete-Time, Stochastic Systems
* This research was supported by a grant from the Greek Ministry of Industry and Technology.In this paper we study discrete-time, finite horizon stochastic systems with multivalued dynamics and obtain a necessary and sufficient condition for optimality using the dynamic programming method. Then we examine a nonlinear stochastic discrete-time system with feedback control constraints and for it, we derive a necessary and sufficient condition for optimality which we then use to establish the existence...
Optimization of measurements for state estimation in parabolic distributed systems
Optimization schemes for wireless sensor network localization
Many applications of wireless sensor networks (WSN) require information about the geographical location of each sensor node. Self-organization and localization capabilities are one of the most important requirements in sensor networks. This paper provides an overview of centralized distance-based algorithms for estimating the positions of nodes in a sensor network. We discuss and compare three approaches: semidefinite programming, simulated annealing and two-phase stochastic optimization-a hybrid...
Optimization shape of variable capacitance micromotor using differential evolution algorithm.
Optimized state estimation for nonlinear dynamical networks subject to fading measurements and stochastic coupling strength: An event-triggered communication mechanism
This paper is concerned with the design of event-based state estimation algorithm for nonlinear complex networks with fading measurements and stochastic coupling strength. The event-based communication protocol is employed to save energy and enhance the network transmission efficiency, where the changeable event-triggered threshold is adopted to adjust the data transmission frequency. The phenomenon of fading measurements is described by a series of random variables obeying certain probability distribution....
Optimum feedback strategy for access control mechanism modelled as stochastic differential equation in computer network.
Option pricing in a CEV model with liquidity costs
The goal of this paper is to make an attempt to generalise the model of pricing European options with an illiquid underlying asset considered by Rogers and Singh (2010). We assume that an investor's decisions have only a temporary effect on the price, which is proportional to the square of the change of the number of asset units in the investor's portfolio. We also assume that the underlying asset price follows a CEV model. To prove existence and uniqueness of the solution, we use techniques similar...
Option pricing in the CRR model with proportional transaction costs: a cone transformation approach
Option pricing in the Cox-Ross-Rubinstein model with transaction costs is studied. Using a cone transformation approach a complete characterization of perfectly hedged options is given.
Ordonnancement de tâches sur un système multiprocesseur - modèles déterministes et modèles stochastiques
Orthogonalization, factorization, and identification as to the theory of recursive equations in linear algebra.
Parameter estimation in stochastic systems: some recent results and applications
Parameter estimation of sub-Gaussian stable distributions
In this paper, we present a parameter estimation method for sub-Gaussian stable distributions. Our algorithm has two phases: in the first phase, we calculate the average values of harmonic functions of observations and in the second phase, we conduct the main procedure of asymptotic maximum likelihood where those average values are used as inputs. This implies that the main procedure of our method does not depend on the sample size of observations. The main idea of our method lies in representing...
Parameter identification and synchronization of dynamical system by introducing an auxiliary subsystem.
Parametrization of multi-output autoregressive-regressive models for self-tuning control
Partially observed optimal controls of forward-backward doubly stochastic systems
The partially observed optimal control problem is considered for forward-backward doubly stochastic systems with controls entering into the diffusion and the observation. The maximum principle is proven for the partially observable optimal control problems. A probabilistic approach is used, and the adjoint processes are characterized as solutions of related forward-backward doubly stochastic differential equations in finite-dimensional spaces. Then, our theoretical result is applied to study a partially-observed...
Particle filter with adaptive sample size
The paper deals with the particle filter in state estimation of a discrete-time nonlinear non-Gaussian system. The goal of the paper is to design a sample size adaptation technique to guarantee a quality of a filtering estimate produced by the particle filter which is an approximation of the true filtering estimate. The quality is given by a difference between the approximate filtering estimate and the true filtering estimate. The estimate may be a point estimate or a probability density function...
Performance analysis of least squares algorithm for multivariable stochastic systems
In this paper, we consider the parameter estimation problem for the multivariable system. A recursive least squares algorithm is studied by minimizing the accumulative prediction error. By employing the stochastic Lyapunov function and the martingale estimate methods, we provide the weakest possible data conditions for convergence analysis. The upper bound of accumulative regret is also provided. Various simulation examples are given, and the results demonstrate that the convergence rate of the...