WII? (2a) Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits





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Published on Aug 20, 2013

What is Information? - Part 2a - Introduction to Information Theory:

Script: http://crackingthenutshell.com/what-i...

- Claude Shannon - Bell Labs - Father of Information Theory

- A Mathematical Theory of Communication - 1948

- Book, co-written with Warren Weaver

- How to transmit information efficiently, reliably & securely through a given channel (e.g. tackling evesdropping)

- Applications. Lossless data compression (ZIP files). Lossy data compression (MP3, JPG). Cryptography, thermal physics, quantum computing, neurobiology

- Shannon's definition not related to meaningfulness, value or other qualitative properties - theory tackles practical issues

- Shannon's information, a purely quantitative measure of communication exchanges

- Shannon's Entropy. John von Neumann. Shannon's information, information entropy - avoid confusion with with thermodynamical entropy

- Shannon's Entropy formula. H as the negative of a certain sum involving probabilities

- Examples: fair coin & two-headed coin

- Information gain = uncertainty reduction in the receiver's knowledge

- Shannon's entropy as missing information, lack of information

- Estimating the entropy per character of the written English language

- Constraints such as "I before E except after C" reduce H per symbol

- Taking into account redundancy & contextuality

- Redundancy, predictability, entropy per character, compressibility

- What is data compression? - Extracting redundancy

- Source Coding Theorem. Entropy as a lower limit for lossless data compression.

- ASCII codes

- Example using Huffman code. David Huffman. Variable length coding

- Other compression techniques: arithmetic coding

- Quality vs Quantity of information

- John Tukey's bit vs Shannon's bit

- Difference between storage bit & information content. Encoded data vs Shannon's information

- Coming in the next video: error correction and detection, Noisy-channel coding theorem, error-correcting codes, Hamming codes, James Gates discovery, the laws of physics, How does Nature store Information, biology, DNA, cosmological & biological evolution


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