By Stefan M. Moser
This easy-to-read advisor presents a concise advent to the engineering heritage of contemporary communique platforms, from cellphones to facts compression and garage. heritage arithmetic and particular engineering recommendations are stored to a minimal in order that just a uncomplicated wisdom of high-school arithmetic is required to appreciate the cloth coated. The authors commence with many functional purposes in coding, together with the repetition code, the Hamming code and the Huffman code. They then clarify the corresponding details idea, from entropy and mutual details to channel potential and the data transmission theorem. eventually, they supply insights into the connections among coding thought and different fields. Many labored examples are given through the ebook, utilizing functional functions to demonstrate theoretical definitions. workouts also are integrated, permitting readers to double-check what they've got discovered and achieve glimpses into extra complicated subject matters, making this ideal for somebody who wishes a brief creation to the topic
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Extra resources for A Student’s Guide to Coding and Information Theory
One-bit errors from the codeword. Thus, the 16 nonoverlapping spheres actually cover 16×8 = 128 points, which are all the points in the 7-dimensional binary space. We see that the (7, 4) Hamming code has the tightest possible packing of radius-1 spheres in the 7-dimensional binary space. 19 Let us consider the dual of the (7, 4) Hamming code C in this example. 12 that the dual code C ⊥ is obtained by reversing the roles of the generating matrix G and the parity-check matrix H of C . That is, we use the parity-check matrix H for encoding and the generator matrix G for checking.
Wicker, Error Control Systems for Digital Communication and Storage. Prentice Hall, Englewood Cliffs, NJ, 1994. 3 Repetition and Hamming codes The theory of error-correcting codes comes from the need to protect information from corruption during transmission or storage. Take your CD or DVD as an example. Usually, you might convert your music into MP3 files1 for storage. e. they use fewer binary digits (bits) compared with the original format on CD. Certainly, the price to pay for a smaller file size is that you will suffer some kind of distortion, or, equivalently, losses in audio quality or fidelity.
15) Thus Pr( Writing in (0 0 0) | Reading out (0 0 1)) Pr(Writing in (0 0 0) and reading out (0 0 1)) = Pr(Reading out (0 0 1)) = 1 − p. 17) Similarly, it can be shown that Pr( Writing in (1 1 1) | Reading out (0 0 1)) = p. 19) and, given that the read-out is (0 0 1), the case of writing in (1 1 1) is less likely. Hence we would guess the original data is more likely to be (0 0 0) due to its higher probability. 1. e. the ones when only one bit is in error. The same holds for the other write-in of (1 1 1).
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