Explaining Entropy Rates in Markov Chains

A technical article explores how entropy, a measure of randomness or information, applies to Markov chains, which model sequences of events where the next state depends on the current one. It explains the mathematical concept of entropy rate for these stochastic processes, making advanced probability theory accessible to a technical audience. This is useful for readers interested in information theory, data compression, and statistical modeling.

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