64.5. HILBERT SPACE VALUED WIENER PROCESSES 2203

Thus (h,W (t)−W (s)) is normally distributed with mean 0 and variance (t− s)(Qh,h). Itis obvious from the definition that W (0) = 0. Also to find the covariance, consider

E ((h1,W (t)−W (s))(h2,W (t)−W (s))) ,

and use 64.5.23 to obtain this is equal to

E

(∞

∑k=1

√λ k (ψk (t)−ψk (s))(h1,ek)

∑j=1

√λ j

(ψ j (t)−ψ j (s)

)(h2,e j)

)

= limn→∞

E

(n

∑k=1

√λ k (ψk (t)−ψk (s))(h1,ek)

n

∑j=1

√λ j

(ψ j (t)−ψ j (s)

)(h2,e j)

)

= limn→∞

(t− s)n

∑k=1

λ k (h1,ek)(h2,e j) = (t− s)(Qh1,h2)

(Recall Q≡ ∑k λ kek⊗ ek.)Next I show the increments are independent. Let N be the subsequence defined above

and let W N (t) be given by the appropriate partial sum and let{

h j}m

j=1 be a finite list ofvectors of U . Then from the independence properties of ψ j explained above,

E

(exp

m

∑j=1

i(h j,W N (t j)−W N (t j−1

))U

)

E

(exp

m

∑j=1

i

(h j,

N

∑k=1

√λ kek

(ψk (t j)−ψk

(t j−1

)))U

)

= E

(exp

m

∑j=1

N

∑k=1

i√

λ k (h j,ek)U(ψk (t j)−ψk

(t j−1

)))

= E

(∏j,k

exp(

i√

λ k (h j,ek)U(ψk (t j)−ψk

(t j−1

))))

= ∏j,k

E(

exp(

i√

λ k (h j,ek)U(ψk (t j)−ψk

(t j−1

))))This can be done because of the independence of the random variables{

ψk (t j)−ψk(t j−1

)}j,k .

Thus the above equals

=m

∏j=1

exp

(−1

2

N

∑k=1

λ k (h j,ek)2U

(t j− t j−1

))

64.5. HILBERT SPACE VALUED WIENER PROCESSES 2203Thus (h, W (t) — W (s)) is normally distributed with mean 0 and variance (t — s) (Qh, /). Itis obvious from the definition that W (0) = 0. Also to find the covariance, considerE ((h1,W (t) —W (s)) (ho, W(t) -W(s))),and use 64.5.23 to obtain this is equal to£(E Vwi wel) ) (Ine) Lavo ~v;(s)) ne)= lim E (x VaR (WY; (t) — W ) (At, ex) ¥ yai(wit —yj(s s)) ne)k=1n= lim ( t—s ) Yad x (M1, €x) (A2,e;) = (t — 5) (Qh, ha)(Recall 0 = Vy Apex ® ek.)Next I show the increments are independent. Let N be the subsequence defined aboveand let W(t) be given by the appropriate partial sum and let {hj}, be a finite list ofvectors of U. Then from the independence properties of y; explained above,£ (oof (hj,W" (t3) —W™ Ww" a)y](cB (ms iE Vines (vets) wiles) |— E [oof y ix (hj,eny (We (ti) — Ve 1)nn.ll>ll=E ( exp (iV/Ax (js ee)y (We (ti) — Vi 9)Ithy(exp (ie (hj.er)y (We (ts) — We (G-1))))This can be done because of the independence of the random variables{Wi (tj) — Vy (tit) ie:Thus the above equalsm N-Tee(-5 2 Ae (hj,ex)ey a)j= k=1