Download e-book for iPad: A Student's Guide to Coding and Information Theory by Stefan M. Moser

By Stefan M. Moser

ISBN-10: 1107015839

ISBN-13: 9781107015838

ISBN-10: 1107601967

ISBN-13: 9781107601963

This easy-to-read consultant offers a concise advent to the engineering heritage of contemporary communique structures, from cellphones to info compression and garage. heritage arithmetic and particular engineering ideas are saved to a minimal in order that just a uncomplicated wisdom of high-school arithmetic is required to appreciate the cloth lined. The authors commence with many useful functions in coding, together with the repetition code, the Hamming code and the Huffman code. They then clarify the corresponding details thought, from entropy and mutual info to channel capability and the data transmission theorem. ultimately, they supply insights into the connections among coding concept and different fields. Many labored examples are given during the ebook, utilizing sensible functions to demonstrate theoretical definitions. routines also are incorporated, permitting readers to double-check what they've got discovered and achieve glimpses into extra complex subject matters, making this ideal for someone who wishes a brief advent to the topic

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Extra resources for A Student's Guide to Coding and Information Theory

Example text

Without knowing how many distinct 2k binary messages can be encoded, by fixing t we make sure that the codewords are immune to errors with at most t error bits. Choosing n means the codewords will be stored in n bits. Being able to pack more radius-t spheres into the n-dimensional spaces means we can have more codewords, hence larger k. This gives a general bound on k, known as the sphere bound, and stated in the following theorem. 20 (Sphere bound) have 2k ≤ Let n, k, and t be defined as above.

5 Can you show that the error might not be detected if there is more than one burst, even if each burst is of length no larger than L? 6 Alphabet plus number codes – weighted codes The codes we have discussed so far were all designed with respect to a simple form of “white noise” that causes some bits to be flipped. This is very suitable for many types of machines. However, in some systems, where people are involved, other types of noise are more appropriate. The first common human error is to interchange adjacent digits of numbers; for example, 38 becomes 83.

When being used purely for error detection, it is also a 2-errordetecting code. Moreover, in terms of the error correction or error detection capability, we have the following two theorems. The proofs are left as an exercise. 6 Let C be an (n, k) binary error-correcting code that is t-errorcorrecting. 21) + t +2 n 38 Repetition and Hamming codes n where is the binomial coefficient defined as n n! (n − )! 7 Let C be an (n, k) binary error-correcting code that is e-errordetecting. Then assuming a raw bit error probability of p, we have Pr(Undetectable error) ≤ n pe+1 (1 − p)n−e−1 e+1 n n n + pe+2 (1 − p)n−e−2 + · · · + p .

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A Student's Guide to Coding and Information Theory by Stefan M. Moser


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