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Optimization of Signal-to-Noise Ratio in Linear Systems

Abstract

Useful, deterministic signals passing through various transmission devices often acquire extraneous random components due to, say, thermal noise in conducting materials, radio clutter or aurora borealis magnetic field fluctuations in the atmosphere, or deliberate jamming in warfare. If there exists some prior information about the nature of the original useful signal and the contaminating random noise it is possible to devise algorithms to improve the relative power of the useful compenent of the signal or, in other words, to increase the signal-to-noise ratio of the signal, by passing it through a filter designed for the purpose. In this short chapter, we give a few examples of such designs just to show how the previously introduced techniques of analysis of random signals can be applied in this context.

Keywords

White Noise Detection Time Impulse Response Function Output Noise Filter Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 32.
    N. Wiener’s original Extrapolation, Interpolation, and Smoothing of Stationary Time Series, MIT Press and Wiley, New York, 1950, is still very readable, but also see Chapter 10 of A. Papoulis, Signal Analysis, McGraw-Hill, New York, 1977.Google Scholar

Copyright information

© Birkhäuser Boston 2006

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