Download Classical and Quantum Information Theory: An Introduction by Emmanuel Desurvire PDF

By Emmanuel Desurvire

Details idea lies on the middle of recent know-how, underpinning all communications, networking, and knowledge garage platforms. This publication units out, for the 1st time, a whole review of either classical and quantum info thought. all through, the reader is brought to key effects with out turning into misplaced in mathematical info. starting chapters current the elemental thoughts and numerous purposes of Shannon's entropy, relocating directly to the center gains of quantum info and quantum computing. themes similar to coding, compression, error-correction, cryptography and channel potential are coated from classical and quantum viewpoints. applying a casual but scientifically exact technique, Desurvire presents the reader with the information to appreciate quantum gates and circuits. hugely illustrated, with a variety of useful examples and end-of-chapter workouts, this article is perfect for graduate scholars and researchers in electric engineering and laptop technological know-how, and practitioners within the telecommunications undefined. additional assets and instructor-only recommendations can be found at www.cambridge.org/9780521881715.

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Extra resources for Classical and Quantum Information Theory: An Introduction for the Telecom Scientist

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It can be shown by integration in Eq. 75, 1, and 2. 27% of the bell surface concerns events falling within two standard deviations (±σ ) of the mean (N ). 7 of the total bell surface, respectively. , an analog oscilloscope) provides a continuous signal. It is interesting to see what a succession of such sampling measurements looks like in the real world. 1, as generated by a computer program. We observe that, as expected, the values of x are randomly distributed above and below the x axis. The sampling points form a cloud that is denser near the axis, defining a region of width 2σ .

This second histogram has a smoother envelope, because there are more data in each of the integer bins. 1), showing the outcome for random variables x (top) and x 2 (bottom). 8 Histogram of the 200 sampling points x shown in Fig. 7, as converted into y = 100x, and corresponding Gaussian distribution envelope p(y). The inset shows a denser histogram corresponding to the same x data with z = 50x. 32 Probability distributions reason, the envelope shape is closer to that of a bell. To obtain a smooth histogram envelope that would closely fit the Gaussian bell curve, one would need to acquire 104 –105 sampling points and arrange them into hundreds of histogram bins.

X N } do not have equal likelihood: p(xi ) = number of possibilities for event i . 4) This general definition has been used in the three previous examples. The single coin tossing or single die casting are characterized by equiprobable events, in which case the PDF is said to be uniform. In the case of the two-dice roll, the PDF is nonuniform with a triangular shape, and peaks about the event x = 7, as we have just seen. Here we are reaching a subtle point in the notion of probability, which is often mistaken or misunderstood.

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