On Stability and Stabilizability of Singular Stochastic Systems with Delays

This paper deals with the class of continuous-time singular linear systems with Markovian jump parameters and time delays. Sufficient conditions on the stochastic stability and stochastic stabilizability are developed. A design algorithm for a state feedback controller which guarantees that the closed-loop dynamics will be regular, impulse free, and stochastically stable is proposed in terms of the solutions to linear matrix inequalities. The research of this author was supported by NSERC Grant RGPIN36444-02. The research of this author was supported by the Program for a New Century of Excellent Talents in the Universities and by the Foundation for the Authors of National Excellent Doctoral Dissertations of P. R. China, Grant 200240. The research of this author was supported by HKU Grant RGC 7029/05P.     

POSITIVE SOLUTIONS FOR p-LAPLACIAN DYNAMIC EQUATIONS ON TIME SCALES

The three-point boundary value problems of p-Laplacian dynamic equations on time scales are investigated. By using Krasnosel＇skii＇s fixed-point theorem and fixed-point index theorem, criteria are achieved for the existence of at least one, two or 2n positive solutions. Furthermore, some examples are included to illustrate the main theorems.     

Smolukhovsky problem for electrons in a metal

We find an analytic solution of the Smolukhovsky problem of the temperature and electric potential jumps in a metal under the action of the temperature gradient normal to the surface. We take the character of the electron energy accommodation on the surface into account. We find the analytic expressions for the electric field generated by heat processes, for the temperature distribution, and for the electric potential.Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 142, No. 1, pp. 93–111, January, 2005.     

Bayesian Analysis of Extreme Values by Mixture Modeling

Modeling of extreme values in the presence of heterogeneity is still a relatively unexplored area. We consider losses pertaining to several related categories. For each category, we view exceedances over a given threshold as generated by a Poisson process whose intensity is regulated by a specific location, shape and scale parameter. Using a Bayesian approach, we develop a hierarchical mixture prior, with an unknown number of components, for each of the above parameters. Computations are performed using Reversible Jump MCMC. Our model accounts for possible grouping effects and takes advantage of the similarity across categories, both for estimation and prediction purposes. Some guidance on the specification of the prior distribution is provided, together with an assessment of inferential robustness. The method is illustrated throughout using a data set on large claims against a well-known insurance company over a 15-year period.     

Experimental verification of the gas-hydraulic analogy with reference to the dam-break problem

The results of an experimental study of dam-break waves for both a dry and a flooded bottom in the lower pool are compared with the first approximation of shallow-water theory. It is shown that this approximation adequately describes the height and velocity of the hydraulic jump in the lower pool for a flooded bottom, does not describe the undulations, and is inconsistent with the experimental data on the perturbation propagation velocity in the upper and, for a dry bottom, in the lower pool.Translated from Izvestiya Rossiiskoi Academii Nauk, Mekhanika Zhidkosti i Gaza, No. 5, 2004, pp. 143–152. Original Russian Text Copyright © 2004 by Bukreev, Gusev, A. A. Malysheva, and I. A. Malysheva.     

On strongly jump traceable reals

In this paper we show that there is no minimal bound for jump traceability. In particular, there is no single order function such that strong jump traceability is equivalent to jump traceability for that order. The uniformity of the proof method allows us to adapt the technique to showing that the index set of the c.e. strongly jump traceables is -complete.     

具有跳跃的随机神经网络的均方稳定性

研究了一类新的具有脉冲跳跃的Hopfield神经网络系统模型,其中脉冲时刻的跳跃是由一般的随机序列所引起,通过运用Lyapunov函数方法,获取了一些新的均方稳定性结果.由于脉冲的跳跃使得不稳定的神经网络变成稳定,因而所得的结果也可以运用到其他相关领域.     

Genetic Algorithm for the Jump Number Scheduling Problem

This paper introduces genetic algorithms for the jump number scheduling problem. Given a set of tasks subject to precedence constraints, the problem is to construct a schedule to minimize the number of jumps. We show that genetic algorithms outperform the previously known Knuth and Szwarcfiter's exhaustive search algorithm when applied to some classes of orders in which no polynomial time algorithms exist in solving the jump number problem. Values for various parameters of genetic jump number algorithms are tested and results are discussed.     

Convexity and characterization of optimal policies in a dynamic routing problem

An infinite horizon, expected average cost, dynamic routing problem is formulated for a simple failure-prone queueing system, modelled as a continuous time, continuous state controlled stochastic process. We prove that the optimal average cost is independent of the initial state and that the cost-to-go functions of dynamic programming are convex. These results, together with a set of optimality conditions, lead to the conclusion that optimal policies are switching policies, characterized by a set of switching curves (or regions), each curve corresponding to a particular state of the nodes (servers).     

Stochastic solution of the linearized Boltzmann equation

For the linearized Boltzmann equation with finite cross section, the solution is represented as an integral over the paths of a Markov jump process. The integral is only shown to converge conditionally, where the limiting process is defined by an increasing sequence of stopping times. The notion of local martingale plays an important role. A number of related kinetic models are also mentioned.Supported by NSF Grant GP 28576.