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Communication Systems

Simon Haykin
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TLDR
This best-selling, easy to read book offers the most complete discussion on the theories and principles behind today's most advanced communications systems.
Abstract
This best-selling, easy to read book offers the most complete discussion on the theories and principles behind today's most advanced communications systems. Throughout, Haykin emphasizes the statistical underpinnings of communication theory in a complete and detailed manner. Readers are guided though topics ranging from pulse modulation and passband digital transmission to random processes and error-control coding. The fifth edition has also been revised to include an extensive treatment of digital communications.

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Journal ArticleDOI

Cognitive radio: brain-empowered wireless communications

TL;DR: Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks: radio-scene analysis, channel-state estimation and predictive modeling, and the emergent behavior of cognitive radio.
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Capacity Limits of Optical Fiber Networks

TL;DR: In this article, the capacity limit of fiber-optic communication systems (or fiber channels?) is estimated based on information theory and the relationship between the commonly used signal to noise ratio and the optical signal-to-noise ratio is discussed.
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Detection of blood vessels in retinal images using two-dimensional matched filters

TL;DR: The concept of matched filter detection of signals is used to detect piecewise linear segments of blood vessels in these images and the results are compared to those obtained with other methods.
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Turbo equalization: principles and new results

TL;DR: It is shown that the performance of the new approaches to combining equalization based on linear filtering, with decoding is similar to the trellis-based receiver, while providing large savings in computational complexity.
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Minimum mean squared error equalization using a priori information

TL;DR: This work explores a number of low-complexity soft-input/soft-output (SISO) equalization algorithms based on the minimum mean square error (MMSE) criterion and shows that for the turbo equalization application, the MMSE-based SISO equalizers perform well compared with a MAP equalizer while providing a tremendous complexity reduction.