Lyapunov Functionals and Stability of Stochastic Difference by Leonid Shaikhet

By Leonid Shaikhet

Hereditary platforms (or platforms with both hold up or after-effects) are universal to version tactics in physics, mechanics, regulate, economics and biology. a massive point of their learn is their balance. balance stipulations for distinction equations with hold up may be acquired utilizing a Lyapunov sensible.
Lyapunov Functionals and balance of Stochastic distinction Equations describes a common approach to Lyapunov sensible development to enquire the steadiness of discrete- and continuous-time stochastic Volterra distinction equations. the tactic permits the research of the measure to which the steadiness homes of differential equations are preserved of their distinction analogues.
The textual content is self-contained, starting with easy definitions and the mathematical basics of Lyapunov sensible development and relocating on from specific to basic balance effects for stochastic distinction equations with consistent coefficients. effects are then mentioned for stochastic distinction equations of linear, nonlinear, not on time, discrete and non-stop kinds. Examples are drawn from quite a few actual platforms together with inverted pendulum keep an eye on, learn of epidemic improvement, Nicholson’s blowflies equation and predator–prey relationships.
Lyapunov Functionals and balance of Stochastic distinction Equations is essentially addressed to specialists in balance conception yet may also be of use within the paintings of natural and computational mathematicians and researchers utilizing the tips of optimum keep watch over to check financial, mechanical and organic structures.

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25), 1,r+1 is the algebraic adjunct of the element of the first line and (r + 1)th column of the determinant (r) n , γij are defined by the identity n n−1 (r) qkm Dik (λ)Dj m (−λ) ≡ (−1)n−1 k,m=1 γij λ2(n−r−1) , r=0 28 1 Short Introduction to Stability Theory of Deterministic Functional qkm are the elements of the matrix Q, and Dik (λ) are the algebraic adjuncts of the determinant D(λ) = a11 − λ . . ... an1 ... a1n .... 10 Consider the second-order scalar differential equation x(t) ¨ + a x(t) ˙ + bx(t) = 0.

L, Qi (t), i = 1, . . , k, Rj (t), j = 0, . . , m, R(s, t), s ≥ t ≥ 0, are nonnegative definite matrices, τi (t), i = 1, . . , k, t ≥ 0, are differentiable nonnegative functions with τ˙i (t) ≤ τˆi < 1, Ki (s), i = 1, . . , n, νi (s), i = 0, . . , l, μj (s), j = 0, . . 37) t where K is the diagonal matrix with elements ki , i = 1, . . , x G(t)x ≤ −c|x|2 , c > 0, x ∈ Rn . 9) is asymptotically mean-square stable. 38) 42 2 Stochastic Functional Differential Equations and Procedure Proof Put ∞ l V2 (t, xt ) = t dνi (s) x (θ )Si (θ )x(θ ) dθ i=1 0 t−s ∞ n + k t dKi (s) i=1 0 t−s ∞ m + xi2 (θ ) dθ + t dμj (s) j =0 0 t−s ∞ + i=1 t−s x (s)Qi (s)x(s) ds t−τi (t) x (τ )R(τ + s, θ )x(τ ) dθ dτ.

51) Suppose that q 2 = B 2 − A2 > 0. 50), ¨ = Aβ(t) ˙ − B β(−t ˙ β(t) − τ) = A Aβ(t) + Bβ(−t − τ ) − B Aβ(−t − τ ) + Bβ(t + τ − τ ) = −q 2 β(t) or ¨ + q 2 β(t) = 0. 53) and two homogeneous linear dependent equations for C1 and C2 C1 (A + B cos qτ ) − C2 (q + B sin qτ ) = 0, C1 (q − B sin qτ ) + C2 (A − B cos qτ ) = 0. 54) we have C2 = C1 A + B cos qτ q − B sin qτ = −C1 . 53) and excluding C1 , we obtain G= A sin qτ − q cos qτ . 43). 55). Suppose now that q 2 = A2 − B 2 > 0. 52), we obtain the ¨ − q 2 β(t) = 0 with the general solution β(t) = C1 eqt + C2 e−qt .

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