Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Buchtitelbild

2016 | OriginalPaper | Buchkapitel

1. Introduction

verfasst von : Silvia Maria Alessio

Erschienen in: Digital Signal Processing and Spectral Analysis for Scientists

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This introductory chapter discusses the meaning of the words that appear in the book’s title. It then gives a concise description of the historical background in which the techniques introduced in the book were developed. The structure of the book is also presented and commented on. Finally, some possible further readings are suggested.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Fußnoten
1
In numerical analysis, “precision” is the resolution of the representation of the measured quantity, typically defined by the number of decimal digits; more precisely, resolution is the smallest change in the underlying physical quantity that produces a response in the measurement instrument. It must be noted that in the fields of science and statistics, the word “precision” traditionally has a very different meaning. It refers to repeated measurements of the same quantity and is related to reproducibility and repeatability. It is the degree to which repeated measurements under unchanged conditions provide the same results. On the other hand, the “accuracy” of a measurement is the degree of closeness of the measurement of a quantity to the true value of the quantity.
 
2
Photo by Dicklyon (Own work) [CC BY-SA 3.0 (http://​creativecommons.​org/​licenses/​by-sa/​3.​0)], via Wikimedia Commons.
 
3
Sunspots are temporary phenomena on the photosphere of the Sun that appear visibly as dark spots compared to surrounding regions. They are generated by strong magnetic fields that are created in the interior of the Sun and inhibit convective motions, thus forming areas of reduced surface temperature. Of all solar features, the sunspots are the most easily observed and were thus studied since the invention of the telescope by Galileo in 1609. This invention was based on previous work by Hans Lipperhey, a German spectacle maker, in 1608. Sunspots were first observed telescopically in late 1610 by the English astronomer Thomas Harriot and by the Frisian astronomers Johannes and David Fabricius, who published a description in 1611. The sunspot number series is one of the most popular indexes of solar activity and allowed for observing the well know 11-year period of Solar activity, known as the Schwabe cycle.
 
Literatur
Bartlett, M.S.: Smoothing periodograms from time series with continuous spectra. Nature 161, 686–687 (1948)CrossRef
Bartlett, M.S.: An Introduction to Stochastic Processes, with Special Reference to Methods and Applications. Cambridge University Press, Cambridge (1955)MATH
Blackman, R.B., Tukey, J.W.: The Measurement of Power Spectra from the Point of View of Communications Engineering. Dover, New York (1965)MATH
Bloomfield, P.: Fourier Analysis of Time Series: An Introduction. Wiley, New York (2000)CrossRefMATH
Box, G.E.P., Jenkins, G.M.: Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco (1970)MATH
Burg, J.P.: Maximum entropy spectral analysis. In: 37th Annual International Meeting, Society of Exploration Geophysics, Oklahoma City, OK, USA (1967)
Burg, J.P.: A new analysis technique for time series data. In: Childers, D.G. (ed.) Modern Spectrum Analysis. NATO Advanced Study Institute of Signal Processing with Emphasis on Underwater Acoustics. IEEE Press, Enschede, The Netherlands (1968)
Burrus, C.S., Gopinath, R.A., Guo, H.: Introduction to Wavelets and Wavelet Transforms: A Primer. Prentice Hall, Upper Saddle River (1997)
Burt, P.J., Adelson, E.H.: The laplacian pyramid as a compact image code. IEEE Trans. Commun. 31(4), 532–540 (1983)CrossRef
Butterworth, S.: On the theory of filter amplifiers. Wirel. Eng. 7, 536–541 (1930)
Buys-Ballot, C.H.: D: Les changéments periodiques de température. Kemint et Fills, Utrecht (1847)
Cauer, W.: Siebshaltungen. V.D.I. Verlag, G.m.b.H., Berlin (1931)
Cauer, W.: Ausgangsseitig Leerlaufende Filter. ENT 16(6), 161–163 (1939)
Cauer, W.: Synthesis of Linear Communication Networks (translated from the German by Knausenberger, G.E., Warfield, J.N.). McGraw-Hill, New York (1958)
Chebyshev, P.L.: Théorie des mécanismes connus sous le nom de parallélogrammes. Mémoires des Savants étrangers présentées à l’Académie Impériale des Sciences de Saint-Pétersbourg 7, 539–586 (1854)
Chebyshev, P.L., Oeuvres, I.: L’Académie Impériale des Sciences, Saint-Pétersbourg (1899). Reprinted by Chelsea (1962)
Cooley, J.W., Tukey, J.W.: An algorithm for the machine calculation of complex fourier series. Math. Comp. 19, 297–301 (1965)MathSciNetCrossRefMATH
Crochiere, R.E., Weber, S.A., Flanagan, J.L.: Digital coding of speech in sub-bands. AT&T Tech. J. 55(8), 1069–1085 (1976)
Daniell, P.J.: Discussion on the symposium on autocorrelation in time series. J. R. Stat. Soc. (Suppl.) 8, 88–90 (1946)
Daubechies, I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inf. Theory 36, 961–1005 (1990)MathSciNetCrossRefMATH
Daubechies, I.: Ten lectures on wavelets. In: CBMS-NSF Regional Conference Series in Applied Mathematics, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, USA (1992)
Donoho, D.L.: Unconditional bases are optimal bases for data compression and for statistical estimation. Appl. Comput. Harmonic Anal. 1(1), 100–115 (1993)MathSciNetCrossRefMATH
Einstein, A.: Method for the determination of the statistical values of observations concerning quantities subject to irregular fluctuations. Arch. Sci. Phys. Natur. 4(37), 254–256 (1914)
Gabor, D.: Theory of communication. J. Inst. Electr. Eng. 93, 429–457 (1946)
Ghil, M., Allen, M.R., Dettinger, M.D., Ide, K., Kondrashov, D., Mann, M.E., Robertson, A.W., Saunders, A., Tian, Y., Varadi, F., Yiou, P.: Advanced spectral methods for climatic time series. Rev. Geophys. 40(1), 1.1–1.41 (2002)
Goswami, J.C., Chan, A.K.: Fundamentals of Wavelets: Theory, Algorithms, and Applications. Wiley, New York (2011)CrossRefMATH
Grenander, U., Rosenblatt, M.: Statistical spectral analysis of time series arising from stationary stochastic processes. Ann. Math. Stat. 24, 537–558 (1953)MathSciNetCrossRefMATH
Grenander, U., Rosenblatt, M.: Some Problems in Estimating the Spectrum of a Time Series. In: Proceeding of Third Berkeley Symposium on Mathematics, Statistics and Probability. vol. 1, pp. 77–93. University of California Press, Oakland, CA, USA (1956)
Grenander, U., Rosenblatt, M.: Statistical Analysis of Stationary Time Series. Wiley, New York (1957)MATH
Grossmann, A., Morlet, J.: Decomposition of hardy functions into square integrable wavelets of constant shape. SIAM J. Math. Anal. 15, 723–736 (1984)MathSciNetCrossRefMATH
Grossmann, A., Morlet, J., Paul, T.: Transformations associated to square integrable group representations. J. Math. Phys. 26, 2473–2479 (1985)MathSciNetCrossRefMATH
Hamming, R.W.: Numerical Methods for Scientists and Engineers. Dover Publications, New York (1987)MATH
Guo, H.: Wavelets for approximate fourier transform and data compression. Ph.D. thesis, ECE Department, Rice University, Houston (1997)
Hamming, R.W., Tukey, J.W.: Measuring noise color. Unpublished Memorandum, Bell Telephone Laboratories (1949). Also in: The Collected Works of John W. Tukey, 1143–1153 (1985)
Hayes, M.H.: Statistical Digital Signal Processing and Modeling. Wiley, New York (2008)
Henderson, K.W., Kautz, W.H.: Transient responses of conventional filters. IRE Trans. Cir. Theory CT-5(4), 333–347 (1958)
Hwei, P.H.: Schaum’s Outline of Signals and Systems. McGraw-Hill, New York (2013)
Kanasewich, E.R.: Time Sequence Analysis in Geophysics. Prentice-Hall, Englewood Cliffs (1981)
Kay, S.M.: Fundamentals of Statistical Signal Processing—Volume I: Estimation Theory. Prentice-Hall, Upper Saddle River (1993)
Knott, C.G.: On lunar periodicities in earthquake frequency. Proc. R. Soc. 60, 457–466 (1897)CrossRefMATH
Kolmogorov, A.N.: Interpolation and extrapolation of stationary random sequences. Izv. Akad. Nauk SSSR Ser. Mat. 5, 3–14 (1941)
Lagrange, J.L.: Recherches sur la manière de former de tables de planètes d’apres les seules observations. In: Oeuvres complètes de Lagrange, Tome VI, 507–627 (1873)
Levinson, N.: The Wiener RMS error criterion in filter design and prediction. J. Math. Phys. 25, 261–278 (1947)CrossRef
Mallat, S.G.: A theory for multiresolution signal decomposition : the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11, 674–693 (1989a)
Mallat, S.G.: Multiresolution approximation and wavelet orthonormal bases of L2. Trans. Am. Math. Soc. 315, 69–87 (1989b)MATH
Mallat, S.G.: Multifrequency channel decompositions of images and wavelet models. IEEE Trans. Acoust. Speech Signal Process. 37, 2091–2110 (1989c)
Mallat, S.: A Wavelet Tour of Signal Processing. Academic Press, Waltham (2008)MATH
Meyer, Y.: Wavelets and Operators. Cambridge University Press, Cambridge (1990)MATH
Marple, S.L.: Digital Spectral Analysis. Prentice-Hall, Englewood Cliffs (1987)
McClellan, J.H., Parks, T.W.: A personal history of the Parks-McClellan algorithm. IEEE Proc. Signal Process. 22, 82–86 (2005)CrossRef
Metropolis, N.C.: The beginning of the Monte Carlo method, pp. 125–130, in: Stanislaw Ulam 1909–1984. Los Alamos Science, 15, Special Issue, Report LA-UR-87-3600, Los Alamos Scientific Laboratory, Los Alamos, NM, USA (1987)
Misiti, M., Misiti, Y., Oppenheim, G., Poggi, J.-M. (eds.): Wavelets and their Applications. Wiley-ISTE, New York (2007)MATH
Mitra, S.K.: Digital Signal Processing—A Computer-Based Approach. McGraw-Hill, New York (2010)
Montgomery, D.C., Jennings, C.L., Kulahci, M.: Introduction to Time Series Analysis and Forecasting. Wiley, New York (2008)MATH
Morlet, J., Arens, G., Fourgeau, I., Giard, D.: Wave propagation and sampling theory. Geophysics 47(2), 203–221 (1982)CrossRef
Norton, E.L.: Constant resistance networks with applications to filter groups. Bell Syst. Tech. J. 16, 178–193 (1937)CrossRef
Nyquist, H.: Certain topics in telegraph transmission theory. Trans. AIEE, 47, 617–644 (1928). Reprint as classic paper in: Proc. IEEE, 90(2) (2002)
Oppenheim, A.V., Schafer, R.W.: Discrete-Time Signal Processing. Prentice Hall, Englewood Cliffs (2009)MATH
Oppenheim, A.V., Willsky, A.S., Hamid, S.: Signals and Systems. Prentice Hall, Englewood Cliffs (1996)
Paarmann, L.D.: Design and Analysis of Analog Filters—A Signal Processing Perspective. Kluwer, Dordrecht (2001)
Parks, T.W., Burrus, C.S.: Digital Filter Design. Wiley, New York (1987)MATH
Parks, T., McClellan, J.: Chebyshev approximation for nonrecursive digital filters with linear phase. IEEE Trans. Circ. Theory 19(2), 189–194 (1972)CrossRef
Parzen, E.: On consistent estimates of the spectrum of a stationary time series. Ann. Math. Stat. 28(2), 329–348 (1957a)
Parzen, E.: On choosing an estimate of the spectral density function of a stationary time series. Ann. Math. Stat. 28(4), 921–932 (1957b)
Percival, D.B., Walden, A.T.: Spectral Analysis for Physical Applications. Cambridge University Press, Cambridge (1993)CrossRefMATH
Porat, B.: A Course in Digital Signal Processing. Wiley, New York (1996)
Prandoni, P., Vetterli, M.: Signal Processing for Communications. EPFL Press, Lausanne (2008)
Proakis, J.G., Manolakis, D.G.: Digital Signal Processing—Principles, Algorithms and Applications. Prentice-Hall, Englewood Cliffs (2006)
Qian, S.: Introduction to Time-Frequency and Wavelet Transforms. Prentice Hall, Upper Saddle River (2001)
Ragazzini, J.R., Zadeh, L.A.: The analysis of sampled-data systems. Trans. Am. Inst. Elec. Eng. 71(II), 225–234 (1952)
Remez, E.Y.: Sur la détermination des polynômes d’approximation de degré donné. Comm. Soc. Math. Kharkov 10, 41–63 (1934a)
Remez, E.Y.: Sur un procédé convergent d’approximations successives pour déterminer les polynômes d’approximation. Compt. Rend. Acad. Sci. 198, 2063–2065 (1934b)MATH
Remez, E.Y.: Sur le calcul effectiv des polynômes d’approximation de Tschebyscheff. Compt. Rend. Acad. Sci. 199, 337–340 (1934c)
Saito, N.: Simultaneous noise suppression and signal compression using a library of orthonormal bases and the minimum description length criterion. In: Foufoula-Georgiou, E., Kumar, P. (eds.) Wavelets in Geophysics. Academic Press, San Diego (1994)
Schuster, A.: On lunar and solar periodicities of earthquakes. Proc. R. Soc. 61, 455–465 (1897)CrossRefMATH
Schuster, A.: On the investigation of hidden periodicities with application to a supposed 26 day period of meteorological phenomena. Terr. Magn. 3, 13–41 (1898)CrossRef
Shannon, C.E.: Communication in the presence of noise. Proc. Inst. Radio Eng. 37(1), 10–21 (1949). Reprint as classic paper in: Proc. IEEE, 86(2) (1998)
Shenoi, B.A.: Introduction to Digital Signal Processing and Filter Design. Wiley, New York (2005)CrossRef
Stephenson, F.W.: RC Active Filter Design Handbook. Wiley, New York (1985)
Stewart, B., Dodgson, W.: Preliminary report to the committee on solar physics and on a method of detecting the unknown inequalities in a series of observations. Proc. R. Soc. 29, 106–122 (1879)CrossRef
Stoica, P., Moses, R.: Spectral Analysis of Signals. Prentice Hall, Upper Saddle River (2005)
Stokes, G.G.: Note on the paper by Stewart and Dodgson. Proc. R. Soc. 29, 122–123 (1879)
Storer, J.E.: Passive Network Synthesis. McGraw-Hill, New York (1957)
Thomson, W.: On an instrument for calculating the integral of the product of two given functions. Proc. R. Soc. 24, 266–268 (1876)CrossRefMATH
Thomson, D.J.: Spectrum estimation and harmonic analysis. Proc. IEEE 70, 1055–1096 (1982)CrossRef
Thomson, D.J.: Time series analysis of holocene climate data. Philos. Trans. R. Soc. London A 330, 601–616 (1990a)CrossRef
Thomson, D.J.: Quadratic-inverse spectrum estimates: applications to palaeoclimatology. Philos. Trans. R. Soc. London A 332, 539–597 (1990b)MathSciNetCrossRefMATH
Tustin, A.: A method of analysing the behaviour of linear systems in terms of time series. J. Inst. Electr. Eng. IIA 94(1), 130–142 (1947)
Vaidyanathan, P.P.: The Theory of Linear Prediction. Morgan & Claypool, San Rafael (2008)MATH
Vautard, R., Ghil, M.: Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series. Physica D 35, 395–424 (1989)MathSciNetCrossRefMATH
Vautard, R., Yiou, P., Ghil, M.: Singular-spectrum analysis: a toolkit for short, noisy chaotic signals. Physica D 58, 95–126 (1992)CrossRef
Vetterli, M., Kovaĉević, J.: Wavelets and Subband Coding. Prentice Hall, Upper Saddle River (1995)
Walker, G.: On periodicity in series of related terms. Proc. R. Soc. London A 131, 518–532 (1931)CrossRefMATH
Weinberg, L.: Network Analysis and Synthesis. McGraw-Hill, New York (1962)
Whittaker, E.T., Robinson, G.: The Calculus of Observations. Blackie and Sons, London (1944)
Wiener, N.: Extrapolation, Interpolation and Smoothing of Stationary Time Series. Wiley, New York (1949)MATH
Wiener, N., Masani, P.: The prediction theory of multivariate stochastic processes. Part 1: Acta Math. 98, 111–150 (1957); Part 2: Acta Math. 99, 93–137 (1958)
Whittle, P.: Hypothesis Testing in Time Series Analysis. Almquist and Wiksell, Uppsala (1951)MATH
Wold, H.O.: A: A Study on the Analysis of Stationary Time Series. Almqvist and Wiksell, Stockholm (1954)MATH
Yule, G.U.: On a method for investigating periodicities in disturbed series with special reference to Wolf’s sunspot numbers. Philos. Trans. R. Soc. London A 26, 267–298 (1927)CrossRefMATH
Metadaten
Titel
Introduction
verfasst von
Silvia Maria Alessio
Copyright-Jahr
2016
Buch
Digital Signal Processing and Spectral Analysis for Scientists

Print ISBN: 978-3-319-25466-1

Electronic ISBN: 978-3-319-25468-5

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-25468-5_1

Neuer Inhalt

    Bildnachweise