In a recent paper1) a differential equation was studied which involves a stochastic process having the property that all its cumulants are delta-correlated. It is here shown that such processes consist of a random sequence of delta functions with random coefficients. As a consequence the solutions of the differential equation are Markov processes, whose master equation can be constructed. From it closed equations for the successive moments may be obtained, and the auto-correlation is determined, in agreement with the results of reference 1. Some generalizations are given in Appendices B and C
Cumulant differential equations (CDEs) that can be employed to calculate response cumulants for line...
Abstract. We consider a discrete time periodically correlated process {X.} which is also Markov in t...
This paper develops response cumulant differential equations (CDEs) that can be used to calculate re...
A relatively straightforward formulation is presented for deriving the differential equations govern...
A relatively straightforward formulation is presented for deriving the differential equations govern...
A relatively straightforward formulation is presented for deriving the differential equations govern...
A solution method is developed for nonlinear differential equations having the following two propert...
In recent years there have been many publications studying dynamic systems subjected to non-Gaussian...
We summarize our previous results on cumular expasions for linear stochastic differential equations ...
We summarize our previous results on cumular expasions for linear stochastic differential equations ...
In recent years there have been many publications studying dynamic systems subjected to non-Gaussian...
We summarize our previous results on cumular expasions for linear stochastic differential equations ...
We summarize our previous results on cumulant expansions for linear stochastic differential equation...
We summarize our previous results on cumulant expansions for linear stochastic differential equation...
A general framework is presented for deriving the differential equations governing the evolution of ...
Cumulant differential equations (CDEs) that can be employed to calculate response cumulants for line...
Abstract. We consider a discrete time periodically correlated process {X.} which is also Markov in t...
This paper develops response cumulant differential equations (CDEs) that can be used to calculate re...
A relatively straightforward formulation is presented for deriving the differential equations govern...
A relatively straightforward formulation is presented for deriving the differential equations govern...
A relatively straightforward formulation is presented for deriving the differential equations govern...
A solution method is developed for nonlinear differential equations having the following two propert...
In recent years there have been many publications studying dynamic systems subjected to non-Gaussian...
We summarize our previous results on cumular expasions for linear stochastic differential equations ...
We summarize our previous results on cumular expasions for linear stochastic differential equations ...
In recent years there have been many publications studying dynamic systems subjected to non-Gaussian...
We summarize our previous results on cumular expasions for linear stochastic differential equations ...
We summarize our previous results on cumulant expansions for linear stochastic differential equation...
We summarize our previous results on cumulant expansions for linear stochastic differential equation...
A general framework is presented for deriving the differential equations governing the evolution of ...
Cumulant differential equations (CDEs) that can be employed to calculate response cumulants for line...
Abstract. We consider a discrete time periodically correlated process {X.} which is also Markov in t...
This paper develops response cumulant differential equations (CDEs) that can be used to calculate re...