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The Mathematical Theory of Communication (Claude E. Shannon)
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#Shannonentropy #Sourcecoding #Channelcapacity #Noisychannelcoding #Markovsourcemodels #TheMathematicalTheoryofCommunication
The Mathematical Theory of Communication presents the work that established information theory as a distinct mathematical discipline. The 1949 book brings together Claude E. Shannon’s foundational 1948 Bell System Technical Journal articles and an explanatory essay by Warren Weaver intended to make their significance more accessible. It is not a general guide to interpersonal communication or a handbook of electronics. Its purpose is to identify the abstract structure common to any system that produces messages, encodes them as signals, sends them through a channel, and reconstructs them at a destination. Shannon deliberately separates the technical problem of transmitting symbols accurately from questions of meaning or value. From that move follow quantitative concepts that became central to digital technology: the bit, entropy, redundancy, channel capacity, and coding. The book asks what messages can be compressed, what noise can be overcome, and what limits no engineering ingenuity can surpass. Its arguments are compact and mathematically demanding, but they provide the conceptual basis for modern data compression, error correction, storage, and telecommunications.
- Amazon USA Store: https://www.amazon.com/dp/0252725484?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/The-Mathematical-Theory-of-Communication-Claude-E-Shannon.html
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- Read more: https://english.9natree.com/read/0252725484/
#Shannonentropy #Sourcecoding #Channelcapacity #Noisychannelcoding #Markovsourcemodels #TheMathematicalTheoryofCommunication
The Mathematical Theory of Communication presents the work that established information theory as a distinct mathematical discipline. The 1949 book brings together Claude E. Shannon’s foundational 1948 Bell System Technical Journal articles and an explanatory essay by Warren Weaver intended to make their significance more accessible. It is not a general guide to interpersonal communication or a handbook of electronics. Its purpose is to identify the abstract structure common to any system that produces messages, encodes them as signals, sends them through a channel, and reconstructs them at a destination. Shannon deliberately separates the technical problem of transmitting symbols accurately from questions of meaning or value. From that move follow quantitative concepts that became central to digital technology: the bit, entropy, redundancy, channel capacity, and coding. The book asks what messages can be compressed, what noise can be overcome, and what limits no engineering ingenuity can surpass. Its arguments are compact and mathematically demanding, but they provide the conceptual basis for modern data compression, error correction, storage, and telecommunications.
