Markov Random Fields
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چکیده
1. Markov property The Markov property of a stochastic sequence {Xn}n≥0 implies that for all n ≥ 1, Xn is independent of (Xk : k / ∈ {n− 1, n, n + 1}), given (Xn−1, Xn+1). Another way to write this is: Xn ⊥ (Xk : k / ∈ ∂{n}) | (Xk : k ∈ ∂{n}) where ∂{n} is the set of neighbors of site n. We would like to now generalize this Markov property from one-dimensional index sets to more arbitrary domains.
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