Abstract
Signal processing involves techniques for manipulating a signal in order to minimize the effects of noise, to correct all kinds of unwanted distortions, and to separate out various components of interest. Most signal processing algorithms include the design and realization of filters. A filter can be described as a system that transforms signals. System theory provides the mathematical background for filter design and realization. A filter has an input and an output, with the output signal y(t) being modified with respect to the input signal x(t) (Fig. 6.1). The signal transformation can be carried out through a mathematical process known as convolution or, if filters are involved, as filtering.
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Alexander ST (1986) Adaptive Signal Processing: Theory and Applications. Springer, Berlin Heidelberg New York
Buttkus B (2000) Spectral Analysis and Filter Theory in Applied Geophysics. Springer, Berlin Heidelberg New York
Cowan CFN, Grant PM (1985) Adaptive Filters. Prentice Hall, Englewood Cliffs, New Jersey
Grünigen DH (2004) Digitale Signalverarbeitung, mit einer Einführung in die kontinuierlichen Signale und Systeme, Dritte bearbeitete und erweiterte Auflage. Fachbuchverlag Leipzig, Leipzig
Hattingh M (1988) A new Data Adaptive Filtering Program to Remove Noise from Geophysical Time- or Space Series Data. Computers & Geosciences 14(4):467–480
Haykin S (2003) Adaptive Filter Theory. Prentice Hall, Englewood Cliffs, New Jersey
Kalman R, Bucy R (1961) New Results in Linear Filtering and Prediction Theory. ASME Tans. Ser. D Jour. Basic Eng. 83:95–107
Sibul LH (1987) Adaptive Signal Processing. IEEE Press
The Mathworks (2010) Signal Processing Toolbox – User’s Guide. The MathWorks, Natick, MA
Trauth MH (1998) Noise Removal from Duplicate Paleoceanographic Time-Series: The Use of adaptive Filtering Techniques. Mathematical Geology 30(5):557–574
Weeks, M (2007) Digital Signal Processing Using MATLAB and Wavelts. Infinity Science Press, Jones and Bartlett Publishers, Boston Toronto London Singapor
Widrow B, Hoff Jr. M (1960) Adaptive Switching Circuits. IRE WESCON Conv. Rev. 4:96–104
Widrow B, Glover JR, McCool JM, Kaunitz J, Williams CS, Hearn RH, Zeidler JR, Dong E, Goodlin RC (1975) Adaptive Noise Cancelling: Principles and Applications. Proc. IEEE63(12):1692–1716
Wiener N (1949) Extrapolation, Interpolation and Smoothing of Stationary Time Series, with Engineering Applications. MIT Press, Cambridge, Mass (reprint of an article originally issued as a classified National Defense Research Report, February, 1942)
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Trauth, M.H. (2010). Signal Processing. In: MATLAB® Recipes for Earth Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12762-5_6
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DOI: https://doi.org/10.1007/978-3-642-12762-5_6
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