Assuming the almost sure stability of a linear homogeneous system, we obtain sufficient conditions for the convergence to zero, in probability as well as pathwise, of solutions of the system of linear inhomogeneous stochastic differential equations. It is well known in the theory of deterministic systems that solutions of a linear inhomogeneous system approach zero if the homogeneous part of the system is exponentially stable and the inhomogeneous terms converge to zero as time goes to infinity. A similar result is considered in the current paper for the stochastic case. The author gives sufficient conditions for the convergence to zero, in probability and with probability one, of solutions of an inhomogeneous system of differential equations if the stochastic semigroup generated by the linear homogeneous part is stable with probability one. Consider a system of stochastic differential equations (1) dx(t) = ( A0x(t) + f0(t) ) dt+ m ∑ k=1 ( Akx(t) + fk(t) ) dwk(t), where Ak are (n× n) matrices; fk(t) = (fk1(t), . . . , fkn(t)), t ≥ 0, are vector functions; wr(t), t ≥ 0, are independent one-dimensional Wiener processes; x(t) = (x1(t), . . . , xn(t)), t ≥ 0, is a solution written as a row vector. Denote by {ei}i=1 an orthonormal basis in R and by 〈x, y〉 = n ∑ i=1 xiyi and ‖x‖ = 〈x, x〉 the scalar product and norm of vectors in R, respectively. Let H s be a stochastic semigroup of nondegenerate operators, H s = H t rH r s , 0 ≤ s ≤ r ≤ t, such that (see [7]) dH s = A0H t s dt+ m ∑ k=1 AkH t s dwk(t), H s s = I, s ≤ t. 2000 Mathematics Subject Classification. Primary 60H10; Secondary 34F05. c ©2008 American Mathematical Society 41 License or copyright restrictions may apply to redistribution; see http://www.ams.org/journal-terms-of-use 42 OLEKSANDER IL’CHENKO We assume that the semigroup H s is stable with probability one; that is, P { lim t→+∞ H 0x = 0 } = 1 for all x ∈ R. It is known (see [5, 7]) that the stability with probability one of the semigroup H s is equivalent to the exponential p-stability of H s for sufficiently small p > 0; that is, there are constants D = D(p) > 0 and λ = λ(p) > 0 such that (2) sup ‖x‖=1 E ∥∥Ht sx∥∥p ≤ De−λp(t−s), p ∈ (0, p0). A solution x(t), t ≥ 0, of system (1) can be represented in the following form: x(t) = H 0x+ ∫ t 0 ( H u )( f0(u)− m ∑ k=1 Akfk(u) ) du+ m ∑ k=1 H 0 ∫ t 0 ( H 0 )−1 fk(u) dwk(u) (3) (see [4, 6]). To study the behavior of x(t) as t → +∞, one needs to estimate the distributions of terms on the right hand side of (3). The following two auxiliary results contain necessary estimates. Lemma 1. Let condition (2) hold. If φ(t), t ≥ 0, is a continuous vector function, then, for arbitrary e > 0 and θ > 0, there exists a constant L e} ≤ L k ∑ i=0 e−(λ−θ)(k−i)p ( sup i≤u≤i+1 ‖φ(u)‖ )p for all k ∈ Z+. Proof of Lemma 1. We make use of the following obvious inequalities: M k ∑ i=0 e−θ(k+1−i) 0, k ∈ Z+, (4) ∥∥Ht sζ∥∥ ≤ n ∑ i=1 ∥∥Ht sei∥∥ ‖ζ‖, ζ = ζ(ω) ∈ R. (5) Taking into account (4) we obtain the bound (6) P { sup k≤t≤k+1 ∥∥∥∥∫ t 0 H uφ(u) du ∥∥∥∥ > e} ≤ P { sup k≤t≤k+1 ∥∥∥∥k−1 ∑
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