Information Theory and Networks

 
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  • Various files used in each lecture
    lecture01: Intro
    lecture02: A Brief History of Networks
    lecture03: Revision: Probability Theory
    lecture04: Uncertainty and Entropy
    lecture05: Entropy
    lecture06: Entropy and Mutual Information
      is available, e.g., at \href{Project Gutenberg}{http://www.gutenberg.org/}
    lecture07: Communications and storage -- simple coding
    lecture08: Decodability
    lecture09: Compression and Coding
    lecture10: Sampling with Fair Coins
    lecture11: Coding Language
      \item English word frequencies follow \href{http://en.wikipedia.org/wiki/Zipf's_law}{Zipf's law}
    lecture12: Coding Language
    lecture13: Limits of Stochastic Processes
    lecture14: Practical Compression
    lecture15: Stream Coding
    lecture16: Gambling and Information Theory
    lecture17: Gambling with Side Information
    lecture18: Information Theory and the Stock Market
    lecture19: Complexity
    lecture20: Kolmogorov Complexity
    lecture21: Kolmogorov Complexity and Probability
    lecture22: Error Correction Codes
    lecture23: Channel Information Capacity
    lecture24: Channel Capacity
    lecture25: Coding with Noise
    lecture26: Coding with Noise
    lecture27: A Brief History of Networks
    lecture28: Network Coding
    lecture29: Cryptography and Information Theory
    lecture30: Cryptography and Information Theor
    lecture31: Information Theory and Estimation
    lecture32: Information Theory, the Universe and Everything
    lecture33: Information Theory, the Universe and Everything
    lecture34: Information Theory, the Universe and Everything


  • Matlab files from each lecture
    lecture01: Intro
    lecture02: A Brief History of Networks
    lecture03: Revision: Probability Theory
    lecture04: Uncertainty and Entropy
    lecture05: Entropy lecture06: Entropy and Mutual Information
    lecture07: Communications and storage -- simple coding
    lecture08: Decodability
    lecture09: Compression and Coding
    lecture10: Sampling with Fair Coins
    lecture11: Coding Language
      \verbatiminput{/home/mroughan/Classes/Transformations/2008/Matlab/james.txt}
    lecture12: Coding Language
    lecture13: Limits of Stochastic Processes
    lecture14: Practical Compression
    lecture15: Stream Coding
    lecture16: Gambling and Information Theory
    lecture17: Gambling with Side Information
    lecture18: Information Theory and the Stock Market
    lecture19: Complexity
    lecture20: Kolmogorov Complexity
    lecture21: Kolmogorov Complexity and Probability
    lecture22: Error Correction Codes
    lecture23: Channel Information Capacity
    lecture24: Channel Capacity
    lecture25: Coding with Noise
    lecture26: Coding with Noise
    lecture27: A Brief History of Networks
    lecture28: Network Coding
    lecture29: Cryptography and Information Theory
    lecture30: Cryptography and Information Theor
    lecture31: Information Theory and Estimation
    lecture32: Information Theory, the Universe and Everything
    lecture33: Information Theory, the Universe and Everything
    lecture34: Information Theory, the Universe and Everything



Matthew Roughan

Last modified: Thu Oct 31 11:46:23 2013