Summary and Info
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.
More About the Author
Thomas M. Cover [ˈkoʊvər] (August 7, 1938 – March 26, 2012) was an information theorist and professor jointly in the Departments of Electrical Engineering and Statistics at Stanford University.