Stability, sensitivity and sensitivity of characterizations
Stabilization of nonlinear stochastic systems without unforced dynamics via time-varying feedback
In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest of this...
Stabilization of nonlinear stochastic systems without unforced dynamics via time-varying feedback
In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest of this...
Stabilization of Volterra equations by noise.
Stable convergence of generalized stochastic integrals and the principle of conditioning.
Stable laws and domains of attraction in free probability theory.
Stable probability measures on Banach spaces
Stable random fields and geometry
Let (M,d) be a metric space with a fixed origin O. P. Lévy defined Brownian motion X(a); a ∈ M as 0. X(O) = 0. 1. X(a) - X(b) is subject to the Gaussian law of mean 0 and variance d(a,b). He gave an example for , the m-dimensional sphere. Let be the Gaussian random measure on , that is, 1. Y(B) is a centered Gaussian system, 2. the variance of Y(B) is equal of μ(B), where μ is the uniform measure on , 3. if B₁ ∩ B₂ = ∅ then Y(B₁) is independent of Y(B₂). 4. for , i = 1,2,..., , i ≠ j, we...
Stable-1/2 bridges and insurance
We develop a class of non-life reserving models using a stable-1/2 random bridge to simulate the accumulation of paid claims, allowing for an essentially arbitrary choice of a priori distribution for the ultimate loss. Taking an information-based approach to the reserving problem, we derive the process of the conditional distribution of the ultimate loss. The "best-estimate ultimate loss process" is given by the conditional expectation of the ultimate loss. We derive explicit expressions for the...
Standard and nonstandard representability of positive uncertainty orderings
Axioms are given for positive comparative probabilities and plausibilities defined either on Boolean algebras or on arbitrary sets of events. These axioms allow to characterize binary relations representable by either standard or nonstandard measures (i. e. taking values either on the real field or on a hyperreal field). We also study relations between conditional events induced by preferences on conditional acts.
Standard and retrial queueing systems: a comparative analysis.
We describe main models and results of a new branch of the queueing theory, theory of retrial queues, which is characterized by the following basic assumption: a customer who cannot get service (due to finite capacity of the system, balking, impatience, etc.) leaves the service area, but after some random delay returns to the system again. Emphasis is done on comparison with standard queues with waiting line and queues with losses. We give a survey of main results for both single server M/G/1 type...
Standard representation of multivariate functions on a general probability space.
Standard stochastic coalescence with sum kernels.
Stanovení střední velikosti částic struktury kovů a slitin
Stastistic of the winding of geodesics on a Riemann surface with finite area and constant negative curvature.
In this paper we show that the windings of geodesics around the cusps of a Riemann surface of a finite area, behave asymptotically as independent Cauchy variables.
State classification for a class of interacting superprocesses with location dependent branching.
State dependent multitype spatial branching processes and their longtime behavior.
State estimation under non-Gaussian Lévy noise: A modified Kalman filtering method
The Kalman filter is extensively used for state estimation for linear systems under Gaussian noise. When non-Gaussian Lévy noise is present, the conventional Kalman filter may fail to be effective due to the fact that the non-Gaussian Lévy noise may have infinite variance. A modified Kalman filter for linear systems with non-Gaussian Lévy noise is devised. It works effectively with reasonable computational cost. Simulation results are presented to illustrate this non-Gaussian filtering method.
State space collapse for queueing networks.
State tameness: a new approach for credit constrains.