semilinear stochastic evolution equations with multiplicative l'evy noise are considered‎. ‎the drift term is assumed to be monotone nonlinear and with linear growth‎. ‎unlike other similar works‎, ‎we do not impose coercivity conditions on coefficients‎. ‎we establish the continuous dependence of the mild solution with respect to initial conditions and also on coefficients. ‎as corollaries of ...

A stochastic process ξ(t) = ξ(t,ω) (−∞ < t < ∞) with values in R is said to be stationary (in the strict sense) if for every finite sequence of numbers t1, . . . , tn the joint distribution of the random variables ξ(t1 + h), . . . , ξ(tn + h) is independent of h. If we replace the arbitrary number h by a multiple of a fixed number θ , h= kθ (k =±1,±2, . . . ), we get the definition of a periodi...

Suppose a certain variable Xt is measured at discrete equally spaced time points t = 1, ... , T and we want to make assertions on the energy distribution of the frequencies in a harmonic analysis. This energy distribution may for example be used to code the data if Xt is a speech signal or to make a prediction if the Xt are economic data. Instead of using a deterministic approach applied scient...

A stationary theory of quantum stochastic processes of second order is outlined. It includes KMS processes in wide sense like the equilibrium finite temperature quantum noise given by the Planck’s spectral formula. It is shown that for each stationary noise there exists a natural output process which is identical to the noise in the infinite temperature limit, and flipping with the noise if the...

This paper analyzes empirical income distributions and proposes a simple stochastic model to explain the stationary distribution and deviations from it. Using the individual tax returns data in the U.S. and Japan for 40 years, we first summarize the shape of income distribution by an exponential decay up to about the 90th percentile of income and a power decay for the top 1 percent. We then pro...