The purpose of this paper is to elucidate the problem of testing for the absence of correlation between the trajectories of two stochastic processes. It is assumed that the process is homogeneous on a pre-specified partition of the index set. The hypothesis testing methodology developed in this article consists in estimating codispersion coefficients on each subset of the partition, and in test...

In this paper, we consider the stochastic proole scheduling problem of a partially ordered set of tasks on uniform processors. The set of available processors varies in time. The running times of the tasks are independent random variables with exponential distributions. We obtain a suucient condition under which a list policy stochastically minimizes the makespan within the class of preemptive ...

We discuss the problem of parameter estimation in nonlinear stochastic di€erential equations (SDEs) based on sampled time series. A central message from the theory of integrating SDEs is that there exist in general two time scales, i.e. that of integrating these equations and that of sampling. We argue that therefore, maximum likelihood estimation is computationally extremely expensive. We disc...

a r t i c l e i n f o a b s t r a c t Keywords: Stochastic resonance Sub-threshold signal External noise Arrayed system In–out correlation Stochastic resonance offers the possibility of signal amplification by the addition of noise. This curious, interesting phenomenon has received considerable attention since the 1990s. Since such effect has the potential to improve the signal processing perfo...

Paleomagnetic data on geomagnetic reversals are divided into two general categories: times of occurrence, and records of directional and/or intensity changes for transitions at individual locations. Despite considerable efforts expended in acquiring paleomagnetic reversal records, a detailed picture of the reversal process is still lacking, along with any means of clearly identifying when the m...

We consider stochastic differential equations driven by some Volterra processes. Under time reversal, these equations are transformed into past dependent stochastic differential equations driven by a standard Brownian motion. We are then in position to derive existence and uniqueness of solutions of the Volterra driven SDE considered at the beginning.

The problem of information extraction from discrete stochastic time series, produced with some finite sampling frequency, using flicker-noise spectroscopy, a general framework for information extraction based on the analysis of the correlation links between signal irregularities and formulated for continuous signals, is discussed. It is shown that the mathematical notions of Dirac δ and Heavisi...

flow shop sequencing problem is included in np-hard problems and a number of heuristic methods have been developed to solve it. most of these methods are offered for the crisp processing time. however fuzzy algorithm is appropriate for the problems with fuzzy processing time. this paper presents a method in which an algorithm is used to minimize make span of flow shop with fuzzy processing time...

Brownian networks are a class of stochastic system models that can arise as heavy traffic approximations for stochastic processing networks. In earlier work we developed the “equivalent workload formulation” of a generalized Brownian network: denoting by Z t the state vector of the generalized Brownian network at time t, one has a lower dimensional state descriptor W t =MZ t in the equivalent w...

Deterministic approaches to stochastic computing (SC) have been recently proposed to remove the random fluctuation and correlation problems of SC and so produce completely accurate results with stochastic logic. For many applications of SC, such as image processing and neural networks, completely accurate computation is not required for all input data. Decision-making on some input data can be ...