A study of the action of wild fires on remote forests

A stochastic model is developed to describe interaction of fires and vegetation in remote forest regions to demonstrate that, given certain circumstances, fires have a dominant effect on the long term, as well as the short term, forest structure. The model describes interactions peculiar to rainforest regions of Tasmania, Australia, but can be adapted to any situation where a similar dependence of vegetation on fires exists.     

Criticality conditions for some random environment population processes

Some random environment population processes are considered. Using a coupling argument, a criticality condition is obtained. The criticality parameter governs whether the process dies out or fluctuates about a positive finite constant, which is explicitly computed.     

Nonhomogeneous markov chains with desired properties - the nearest markovian model

A new class of operators performing an optimization (optimization operators or, simply, optimators) which generate transition matrices with required properties such as ergodicity, recurrence etc., is considered and their fundamental features are described. Some criteria for comparing such operators by taking into account their strenght are given and sufficient conditions for both weak and strong ergodicity are derived. The nearest Markovian model with respect to a given set of observed probability vectors is then defined as a sequence of transition matrices satisfying certain constraints that express our prior knowledge about the system. Finally, sufficient conditions for the existence of such a model are given and the related algorithm is illustrated by an example.     

A stochastic system with MMPP input and an access function

In classical studies of loss systems with restricted availability, the utilization was suggested of a probabilistic loss function, defining the conditional probability of an incoming call being rejected, as a function of the number of occupations in the destination group of servers. This paper gives an exact analysis of stochastic processes of practical relevance, associated with a system with MMPP (Markov Modulated Poisson Process) input, finite queueing capacity and a general loss function, assuming exponential service times. In addition to the process defining the state of the system at any instant, the analysis of the overflow point process (associated with the rejected arriving customers), the accepted point process (associated with the accepted arriving customers), and of the departure process will be presented. Together with the exact analysis of this system, based on the matrix analytical methodology of Neuts, (1981), we will derive expressions for calculating some key-parameters of pertinent associated processes, which may also be used for their approximate modelling. Also, examples of applications and of blocking probability calculations in specific models of this class will be presented.     

Itô versus Stratonovich

A survey is given of the facts and fancies concerning the nonlinear Langevin or Itô equation. Actually, it is merely a pre-equation, which becomes an equation when an interpretation rule is added. The rules of Itô and Stratonovich differ, but both are mathematically consistent and therefore equally admissible conventions. The reason why they seem to lead to physical differences is that the Langevin approach used to arrive at the equation involves a tacit assumption. For systems with external noise this assumption can be justified, and it is then clear that the Stratonovich rule applies. Systems with internal noise, however, can only be properly described by a master equation and the Itô-Stratonovich controversy never enters. Afterward one is free to model the resulting fluctuations either with an Itô or a Stratonovich scheme, but that does not lead to any new information.     

Simulation of stochastic differential equations

A lot of discrete approximation schemes for stochastic differential equations with regard to mean-square sense were proposed. Numerical experiments for these schemes can be seen in some papers, but the efficiency of scheme with respect to its order has not been revealed. We will propose another type of error analysis. Also we will show results of simulation studies carried out for these schemes under our notion.     

The probability approach to numerical solution of nonlinear parabolic equations

A number of new layer methods for solving semilinear parabolic equations and reaction‐diffusion systems is derived by using probabilistic representations of their solutions. These methods exploit the ideas of weak sense numerical integration of stochastic differential equations. In spite of the probabilistic nature these methods are nevertheless deterministic. A convergence theorem is proved. Some numerical tests are presented. © 2002 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 18: 490–522, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/num.10020     

Organizational Modes of Large-Scale Vortices in an Axisymmetric Turbulent Jet

Large vortices occurring in the axial plane of a self-similar axisymmetric turbulent jet are educed by spatially filtering PIV data. First, the instantaneous PIV frame is convolved with a Gaussian kernel to obtain a smooth (low-pass) field. Next, the low-pass field is Galilean transformed to expose the large vortices residing near the edges of the jet. Large vortices tend to organize themselves in preferred modes; evidence of ring and helical modes is revealed by Galilean transformation of the low-pass filtered field. Both modes seem to occur prominently in jets, with the helical mode being the more frequent. The overall diameter of both ring and helical modes is comparable with the local jet width. The low-pass field occasionally exhibits arrowhead shaped structures with large entrainment at their downstream tips. Stochastic estimates computed from the Galilean-transformed low-pass filtered field indicate that jet meander and a sweep-in of ambient fluid are sufficient to reconstruct large vortices. The frequency of occurrence of modes agrees with previously quoted results. This revised version was published online in July 2006 with corrections to the Cover Date.     

Stochastic systems with cross-correlated Gaussian white noises

This paper theoretically investigates three stochastic systems with cross-correlation Gaussian white noises.Both steady state properties of the stochastic nonlinear systems and the nonequilibrium transitions induced by the cross-correlated noises are studied.The stationary solutions of the Fokker-Planck equation for three specific examples are analysed.It is shown explicitly that the cross-correlation of white noises can induce nonequilibrium transitions.     

Harmonic stochastic resonance-enhanced signal detecting in NW small-world neural network

The harmonic stochastic resonance-enhanced signal detecting in Newman-Watts small-world neural network is studied using the Hodgkin-Huxley dynamical equation with noise.If the connection probability p,coupling strength g syn and noise intensity D matches well,higher order resonance will be found and an optimal signal-to-noise ratio will be obtained.Then,the reasons are given to explain the mechanism of this appearance.