The chain rule of mutual information is a mathematical property that expresses the mutual information between multiple random variables in terms of their joint distributions. It allows us to break down the mutual information into simpler components, reflecting the relationship between subsets of variables and their influences on one another. This concept is essential for understanding the capacity of communication systems and forms a critical part of achievability and converse proofs.
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