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Books on the topic 'Random noise theory'

Author: Grafiati

Published: 4 June 2021

Last updated: 27 July 2024

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1

White noise distribution theory. Boca Raton: CRC Press, 1996.

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2

Middleton, D. First-order non-gaussian class C interference models and their associated threshold detection algorithms. [Boulder, CO: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1987.

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3

Middleton, D. First-order non-gaussian class C interference models and their associated threshold detection algorithms. [Boulder, CO: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1987.

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4

Middleton, D. First-order non-gaussian class C interference models and their associated threshold detection algorithms. [Boulder, CO: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1987.

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5

Middleton, D. First-order non-gaussian class C interference models and their associated threshold detection algorithms. [Boulder, CO: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1987.

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6

Hans-Jürgen, Zepernick, ed. Pseudo random signal processing: Theory and application. Hoboken, NJ: Wiley, 2005.

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7

Etten, Wim C. Van. Introduction to Random Signals and Noise. New York: John Wiley & Sons, Ltd., 2006.

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8

Kotelʹnikov, V. A. Teorii͡a︡ potent͡s︡ialʹnoĭ pomekhoustoĭchivosti. Moskva: "Radio i svi͡a︡zʹ", 1998.

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9

Loecher, Markus. Noise sustained patterns: Fluctuations and nonlinearities. Singapore: World Scientific, 2004.

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10

Jacobsen, Gunnar. Noise in digital optical transmission systems. Boston: Artech House, 1994.

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11

Zhigli͡avskiĭ, A. A. Obnaruzhenie razladki sluchaĭnykh prot͡sessov v zadachakh radiotekhniki. Leningrad: Izd-vo Leningradskogo universiteta, 1988.

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12

L, Root William, and IEEE Communications Society, eds. An introduction to the theory of random signals and noise. New York: IEEE Press, 1987.

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13

Howard, Roy M. A signal theoretic introduction to random processes. Hoboken, New Jersey: John Wiley & Sons, Inc., 2015.

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14

1960-, Abbott Derek, Society of Photo-optical Instrumentation Engineers., and Sociedad Española de Optica, eds. Fluctuations and noise in biological, biophysical, and biomedical systems II: 26-28 May, 2004, Maspalomas, Gran Canaria, Spain. Bellingham, Wash: SPIE, 2004.

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15

R, Doering Charles, Kiss L. B, and Shlesinger Michael F, eds. Proceedings of the First International Conference on Unsolved Problems of Noise in Physics, Biology, Electronic Technology and Information Technology. Singapore: World Scientific, 1997.

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16

Center, Langley Research, ed. Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1985.

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17

Jeanne, Olivier. Noise trading and exchange rate regimes. Cambridge, MA: National Bureau of Economic Research, 1999.

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18

Jeanne, Olivier. Noise trading and exchange rate regimes. Wellington, New Zealand: Reserve Bank of New Zealand, 1999.

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19

name, No. Fluctuations and noise in photonics and quantum optics: 2-4 June, 2003, Santa Fe, New Mexico, USA. Bellingham, WA: SPIE, 2003.

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20

Rozov, A. K. Ot͡s︡enivanie parametrov sluchaĭnykh signalov v avtomaticheskikh sistemakh. Leningrad: "Mashinostroenie," Leningradskoe otd-nie, 1990.

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21

B, Weissman Michael, Israeloff Nathan E. 1961-, Kogan A. Shulim, and Society of Photo-optical Instrumentation Engineers., eds. Noise as a tool for studying materials: 2-4 June, 2003, Santa Fe, New Mexico, USA. Bellingham, Wash: SPIE, 2003.

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22

Ridolfi, Luca. Noise-induced phenomena in the environmental sciences. Cambridge: Cambridge University Press, 2011.

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23

Neeser, Fredy D. Communication theory and coding for channels with intersymbol interference. Konstanz: Hartung-Gorre Verlag, 1994.

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24

Brown, Robert Grover. Introduction to random signals and applied Kalman filtering. 2nd ed. New York: J. Wiley, 1992.

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25

Brown, Robert Grover. Introduction to random signals and applied Kalman filtering. New York: John Wiley, 1992.

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26

Brown, Robert Grover. Introduction to random signals and applied Kalman filtering: With MATLAB exercises and solutions. 3rd ed. New York: Wiley, 1997.

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27

Massimo, Macucci, Society of Photo-optical Instrumentation Engineers., European Optical Society, Società italiana di ottica e fotonica., and SPIE Europe, eds. Noise and fluctuations in circuits, devices, and materials: 21-24 May 2007, Florence, Italy. Bellingham, Wash: SPIE, 2007.

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28

D, Whalen Anthony, and Whalen Anthony D, eds. Detection of signals in noise. 2nd ed. San Diego: Academic Press, 1995.

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29

Herrmann, Samuel. Stochastic resonance: A mathematical approach in the small noise limit. Providence, Rhode Island: American Mathematical Society, 2014.

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30

Kuo, Hui-Hsiung. White Noise Distribution Theory. Taylor & Francis Group, 2018.

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31

Kuo, Hui-Hsiung. White Noise Distribution Theory. Taylor & Francis Group, 2018.

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32

Kuo, Hui-Hsiung. White Noise Distribution Theory. Taylor & Francis Group, 2018.

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33

Kuo, Hui-Hsiung. White Noise Distribution Theory. Taylor & Francis Group, 2018.

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34

Obata, Nobuaki. White Noise Calculus and Fock Space. Springer, 1994.

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35

Obata, Nobuaki. White Noise Calculus and Fock Space. Springer London, Limited, 2006.

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36

Detection of a chi-square fluctuating target in Gaussian noise. Washington, DC: Naval Research Laboratory, 1994.

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37

Innovation Approach to Random Fields: Application of White Noise Theory. World Scientific Publishing Co Pte Ltd, 2004.

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38

Innovation Approach to Random Fields: Application of White Noise Theory. World Scientific Publishing Co Pte Ltd, 2004.

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39

Bouchaud, Jean-Philippe. Random matrix theory and (big) data analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198797319.003.0006.

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This chapter reviews methods from random matrix theory to extract information about a large signal matrix C (for example, a correlation matrix arising in big data problems), from its noisy observation matrix M. The chapter shows that the replica method can be used to obtain both the spectral density and the overlaps between noise-corrupted eigenvectors and the true ones, for both additive and multiplicative noise. This allows one to construct optimal rotationally invariant estimators of C based on the observation of M alone. This chapter also discusses the case of rectangular correlation matri

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40

(Editor), R. Katilius, ed. Noise in Physical Systems and 1/F Fluctuations: Proceedings of 13th International Conference Palanga, Lithuania 29 May-3 June 1995. World Scientific Pub Co Inc, 1995.

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41

Katilius, R. Noise in Physical Systems and 1/F Fluctuations: Proceedings of the 13th International Conference. World Scientific Publishing Co Pte Ltd, 1995.

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42

Katilius, R. Noise in Physical Systems and 1/F Fluctuations: Proceedings of the 13th International Conference. World Scientific Publishing Co Pte Ltd, 1995.

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43

Booker, Henry G., Anthony D. Whalen, and Nicholas Declaris. Detection of Signals in Noise. Elsevier Science & Technology Books, 2013.

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44

Finger, Adolf, and Hans-Jurgen Zepernick. Pseudo Random Signal Processing: Theory and Application. Wiley & Sons, Incorporated, John, 2013.

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45

Finger, Adolf, and Hans-Jurgen Zepernick. Pseudo Random Signal Processing: Theory and Application. Wiley & Sons, Limited, John, 2013.

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46

Finger, Adolf, and Hans-Jurgen Zepernick. Pseudo Random Signal Processing: Theory and Application. Wiley & Sons, Incorporated, John, 2013.

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47

Finger, Adolf, and Hans-Jurgen Zepernick. Pseudo Random Signal Processing: Theory and Application. Wiley & Sons, Incorporated, John, 2013.

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48

Finger, Adolf, and Hans-Jurgen Zepernick. Pseudo Random Signal Processing: Theory and Application. Wiley & Sons, Incorporated, John, 2013.

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49

Etten, Wim C. Van. Introduction to Random Signals and Noise. Wiley & Sons, Incorporated, John, 2007.

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50

Etten, Wim C. Van. Introduction to Random Signals and Noise. Wiley & Sons, Limited, John, 2006.

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