By Monica Borda
The paintings introduces the basics in regards to the discrete details conception (measures of discrete details, mathematical modeling of discrete memoryless/memory resources and of discrete transmission channels) and the coding concept with its major elements: compression, mistakes keep an eye on and encryption. the knowledge of the theoretical topic is supported by means of many examples. One specific emphasis is wear the reason of Genomic Coding. Many examples through the booklet are selected from this actual quarter and a number of other elements of the booklet are dedicated to this intriguing implication of coding. The booklet is attention-grabbing and hugely worthy for tutorial reasons for college students and all those that want fundamentals in info thought and coding.
Monica E. Borda is Professor in details thought and Coding, Cryptography and Genomic sign Processing on the Technical college of Cluj-Napoca, Romania, having greater than 30 years event of schooling and study within the themes lined via the ebook. She has carried out study and Ph.D. thesis in coding conception, nonlinear sign and photo processing, picture watermarking, genomic sign processing, having authored and coauthored greater than a hundred examine papers in nationwide and foreign journals and convention complaints. She is writer and coauthor of five books within the pointed out fields.
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Extra info for Fundamentals in Information Theory and Coding
They get BER=10-5 at Eb = 0,7 dB with spectral efficiency of 0,5 bit/second/Hz . N0 4) The same capacity can be obtained using different values for ξ and B: we can use a narrow bandwidth B1 and a channel with a very good SNR ξ1 (this case corresponds to system 1 shown in Fig. 8); a noisy channel with a small ξ2 requires a wider bandwidth B2 (system 2, Fig. 8) to provide the same capacity. 83) gives a theoretical limit of the maximum transmissible deci• sion rate. On real channels: D max real < C .
A. N. Kolmogorov  showed that the mathematical expression of the information entropy is identical as form with the entropy in physics, but it would be an exaggeration to consider that all the theories from physics related to entropy contain, by themselves, elements of the information theory. Both notions have in common the fact that they measure the non-determination degree of a system, but their applications can be found in completely different spheres of knowledge. 12) is a quantitative expression of the information.
V. X and Y as marginal probabilities, as shown in Fig. b. 41) Knowing the received symbols yj, we cannot state that the uncertainty regarding the transmitted symbols was totally eliminated, because of the channel noise. Uncertainty still exists even after receiving the yj symbols. The average value of this residual uncertainty is denoted by H(X/Y) and signifies the input conditioned by output entropy; it is also called equivocation, being a measure of the equivocal that still exists regarding the input, when the output is known.
Fundamentals in Information Theory and Coding by Monica Borda