Information source (mathematics)

In mathematics, an information source is a sequence of random variables ranging over a finite alphabet Γ, having a stationary distribution. The uncertainty, or entropy rate, of an information source is defined as H { X } = lim n → ∞ H ( X n | X 0 , X 1 , … , X n − 1 ) {\displaystyle H\{\mathbf {X} \}=\lim _{n\to \infty }H(X_{n}|X_{0},X_{1},\dots ,X_{n-1})} where X 0 , X 1 , … , X n {\displaystyle X_{0},X_{1},\dots ,X_{n}} is the sequence of random variables defining the information source, and H ( X n | X 0 , X 1 , … , X n − 1 ) {\displaystyle H(X_{n}|X_{0},X_{1},\dots ,X_{n-1})} is the conditional information entropy of the sequence of random variables.

Source: Wikipedia — Information source (mathematics) (CC BY-SA 4.0)

Information source (mathematics)

In mathematics, an information source is a sequence of random variables ranging over a finite alphabet Γ, having a stationary distribution. The uncertainty, or entropy rate, of an information source is defined as H { X } = lim n → ∞ H ( X n | X 0 , X 1 , … , X n − 1 ) {\displaystyle H\{\mathbf {X} \}=\lim _{n\to \infty }H(X_{n}|X_{0},X_{1},\dots ,X_{n-1})} where X 0 , X 1 , … , X n {\displaystyle X_{0},X_{1},\dots ,X_{n}} is the sequence of random variables defining the information source, and H ( X n | X 0 , X 1 , … , X n − 1 ) {\displaystyle H(X_{n}|X_{0},X_{1},\dots ,X_{n-1})} is the conditional information entropy of the sequence of random variables.

Source: Wikipedia "Information source (mathematics)" · CC BY-SA 4.0

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