Information Theory: from Coding to Learning
Y. Polyanskiy, Y. WuThis textbook introduces the subject of information theory at a level suitable for advanced
undergraduate and graduate students. It develops both the classical Shannon theory and recent
applications in statistical learning. There are five parts covering foundations of information mea-
sures; (lossless) data compression; binary hypothesis testing and large deviations theory; channel
coding and channel capacity; lossy data compression; and, finally, statistical applications. There
are over 150 exercises included to help the reader learn about and bring attention to recent
discoveries in the literature.
సంవత్సరం:
2022
భాష:
english
పేజీల సంఖ్య:
620
ఫైల్:
PDF, 4.91 MB
IPFS:
,
english, 2022
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