Abstract
There is probably no aspect of probability theory that is easier to learn than its Fourier aspect. All of the linear theory [4.1] involving convolutions, Dirac delta functions, transfer theorems, and even sampling theorems has its counterparts in probability theory.
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Chapter 4
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Additional Reading
Araujo, A., E. Gine: The Central Limit Theorem for Real and Banach Valued Random Variables (Wiley, New York 1980)
Lukacs, E.: Characteristic Functions, 2nd ed. (Griffin, London 1970)
Moran, P. A. P.: An Introduction to Probability Theory (Clarendon, Oxford 1968)
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© 1983 Springer-Verlag Berlin Heidelberg
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Frieden, B.R. (1983). Fourier Methods in Probability. In: Probability, Statistical Optics, and Data Testing. Springer Series in Information Sciences, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-96732-0_4
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DOI: https://doi.org/10.1007/978-3-642-96732-0_4
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