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Let (M,d) be a metric space with a fixed origin O. P. Lévy defined Brownian motion X(a); a ∈ M as 0. X(O) = 0. 1. X(a) - X(b) is subject to the Gaussian law of mean 0 and variance d(a,b). He gave an example for $M=S^m$, the m-dimensional sphere. Let $Y\left(B\right);B\in ℬ\left(S^m\right)$ be the Gaussian random measure on $S^m$, that is, 1. Y(B) is a centered Gaussian system, 2. the variance of Y(B) is equal of μ(B), where μ is the uniform measure on $S^m$, 3. if B₁ ∩ B₂ = ∅ then Y(B₁) is independent of Y(B₂). 4. for $B_i$, i = 1,2,..., $B_i\cap B_j=\varnothing$, i ≠ j, we...