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Theorem 1 S. Let be a nonempty separable complete subset of a metric space and a continuous random operator satisfying condition (A).
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Let ((Omega,Sigma,mu)) be a complete probability measure space and E be a nonempty subset of a separable Banach space X.
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Let F be a nonempty subset of a separable Banach space X and T: Ω × F → F be a random map.
Let ((Omega,xi,mu)) be a complete probability measure space, E be a nonempty subset of a separable Banach space X, and (T Omegatimes Erightarrow E) be a random operator.
Theorem 3.3 Let M be a nonempty bounded closed convex subset of a separable Banach space X and let A, B : Ω × M → X be two random operators satisfying, for each ω ∈ Ω, (i) A is weakly-strongly continuous; (ii) B is nonexpansive; (iii) A ( ω, x ) + B ( ω, x ) ∈ Ω × M for every x ∈ M. .
Let ( Ω, F, μ ) be a complete finite measure space, let Y be a complete, separable metric space, and let T : Ω → 2 Y be a nonempty valued correspondence with a measurable graph, i.e., G T ∈ F ⊗ β ( Y ).
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The only substantive requirement introduced by (5) is that there be a nonempty positive analogy.
Let be a nonempty poset.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com