A Mathematical Theory of Communication (information theory)

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He measured information in bits using entropy, separating a message's content from its meaning, and modeled communication as a source, channel, and receiver subject to noise. He proved that every channel has a maximum reliable rate (its capacity) and that codes exist to approach it with arbitrarily few errors, and gave limits on lossless compression. These results underpin modern data compression, error-correcting codes, and digital communication and storage.