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Correlation Analysis with Discrete Time Models

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Abstract

Based on the fundamentals of the correlation analysis as outlined in Chap. 6 for the continuous-time case, the discrete-time case will now be examined more closely in this chapter. This case is required for the implementation on digital computers. The difference in the treatment of continuous-time and discrete-time signals is rather small as it only affects the calculation of the correlation functions, where basically the continuous-time integration must be replaced by the summation of discrete values. In Sect. 7.1, the estimation of the correlation function is treated again.

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References

  • Bartlett MS (1946) On the theoretical specification and sampling properties of autocorrelated time series. J Roy Statistical Society B 8(1):27–41

    MathSciNet  Google Scholar 

  • Bendat JS, Piersol AG (2010) Random data: Analysis and measurement procedures, 4th edn. Wiley-Interscience, New York

    MATH  Google Scholar 

  • Chow P, Davies AC (1964) The synthesis of cyclic code generators. Electron Eng 36:253–259

    Google Scholar 

  • Davies WDT (1970) System identification for self-adaptive control. Wiley-Interscience, London

    MATH  Google Scholar 

  • Fransaer J, Fransaer D (1991) Fast cross-correlation algorithm with application to spectral analysis. IEEE Trans Signal Process 39(9):2089–2092

    Article  Google Scholar 

  • Kammeyer KD, Kroschel K (2009) Digitale Signalverarbeitung: Filterung und Spektralanalyse mit MATLAB-Übungen, 7th edn. Teubner, Wiesbaden

    Google Scholar 

  • Pittermann F, Schweizer G (1966) Erzeugung und Verwendung von binärem Rauschen bei Flugversuchen. Regelungstechnik 14:63–70

    Google Scholar 

  • Press WH, Teukolsky SA, Vetterling WT, Flannery BP (2007) Numerical recipes: The art of scientific computing, 3rd edn. Cambridge University Press, Cambridge, UK

    MATH  Google Scholar 

  • Rader C (1970) An improved algorithm for high speed autocorrelation with applications to spectral estimation. IEEE Trans Audio Electroacoust 18(4):439–441

    Article  Google Scholar 

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Correspondence to Rolf Isermann .

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© 2011 Springer Berlin Heidelberg

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Isermann, R., Münchhof, M. (2011). Correlation Analysis with Discrete Time Models. In: Identification of Dynamic Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78879-9_7

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  • DOI: https://doi.org/10.1007/978-3-540-78879-9_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78878-2

  • Online ISBN: 978-3-540-78879-9

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