A proof of the data compression theorem of Slepian and Wolf for ergodic sources (Corresp.)

TLDR: It is established that the Slepian-Wolf theorem is true without change for arbitrary ergodic processes \{(X_i,Y_i)\}_{i=1}^{\infty} and countably infinite alphabets.

Abstract: If \{(X_i, Y_i)\}_{i=1}^{\infty} is a sequence of independent identically distributed discrete random pairs with (X_i, Y_i) ~ p(x,y) , Slepian and Wolf have shown that the X process and the Y process can be separately described to a common receiver at rates R_X and R_Y hits per symbol if R_X + R_Y > H(X,Y), R_X > H(X\midY), R_Y > H(Y\midX) . A simpler proof of this result will be given. As a consequence it is established that the Slepian-Wolf theorem is true without change for arbitrary ergodic processes \{(X_i,Y_i)\}_{i=1}^{\infty} and countably infinite alphabets. The extension to an arbitrary number of processes is immediate.