11 Hamming, Learning to Learn: Coding Theory II, 20 April 1995
Channel: Hamming on Hamming: Learning to Learn
Date: 2018-02-22

Two things should be clear from the previous lecture. First, that we want the average length L of the message sent to be as small as we can make it (to save the use of facilities). Second, it must be a statistical theory since we cannot know the messages that are to be sent, but we can know some of the statistics by using past messages plus the inference that the future will probably be like the past. For the simplest theory, which is all we can discuss here, we will need the probabilities of the individual symbols occurring in a message. How to get these is not part of the theory, but can be obtained by the inspection of past experience, or imaginative guessing about the future use of the proposed system you are designing.

00:00 Encoders(Source and Channel)
03:46 In the decoding tree
07:01 What an in relying problem is
11:00 When you optimize a design are there other characteristics you want
16:15 Huffman Code
18:50 2 out of 5 code
23:44 Probability one error
27:22 How can I go further?
33:58 Human noise error correction
36:06 There are an enormous number of codes devised by various people
40:33 You could do great work
43:34 End

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