Elements of Information Theory (Hardcover)

An Introduction to Information Theory by John R. Pierce  (13)  $10.36

Pattern Recognition and Machine Learning (Information Science and Statistics) by Christopher M. Bishop  (38)  $63.10

The Mathematical Theory of Communication by Claude E Shannon  (12)  $19.80

Information Theory, Inference & Learning Algorithms by David J. C. MacKay  (7)  $57.40

The Elements of Statistical Learning by T. Hastie  (25)  $73.20

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Product Description
Following a brief introduction and overview, early chapters cover the basic algebraic relationships of entropy, relative entropy and mutual information, AEP, entropy rates of stochastics processes and data compression, duality of data compression and the growth rate of wealth. Later chapters explore Kolmogorov complexity, channel capacity, differential entropy, the capacity of the fundamental Gaussian channel, the relationship between information theory and statistics, rate distortion and network information theories. The final two chapters examine the stock market and inequalities in information theory. In many cases the authors actually describe the properties of the solutions before the presented problems.

Book Info
Up-to-date introduction to the field of information theory and its applications to communication theory, statistics, computer science, probability theory and the theory of investment. DLC: 1. Information theory.

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