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Analysis

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Part of the book series: Advanced Textbooks in Control and Signal Processing ((C&SP))

In this chapter stochastic models are analyzed in various ways. The following issues will be treated.

  • Linear filtering and its effect on the spectrum. Complex-valued signals will be allowed (Section 4.2).

  • Spectral factorization (Section 4.3), permitting complex-valued signals.

  • A review of linear continuous-time models and their properties (Section 4.4), and sampling of such models (Section 4.5).

  • Some aspects on the positive real part of the spectrum (Section 4.6).

  • Properties of the bispectrum when stochastic signals are filtered (Section 4.7).

  • Algorithms for covariance calculations based on finite-order models (Section 4.8).

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Bibliography

  • There is a rich literature on continuous-time stochastic systems. An excellent book with profound mathematics combined with engineering application is Åström, K.J., 1970. Introduction to Stochastic Control Theory. Academic Press, New York.

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  • See also Jazwinski, A.H., 1970. Stochastic Processes and Filtering Theory, Academic Press, New York.

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  • Another book dealing with stochastic dynamic models is the classical text Box. G.E.P., Jenkins, G.W., 1976. Time Series Analysis: Forecasting and Control, second ed. Holden-Day, San Francisco.

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  • A comprehensive treatment is also given in Brown, R.G., 1983. Introduction to Random Signal Analysis and Kaiman Filtering. John Wiley & Sons, New York.

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  • The Kalman-Yakubovich lemma is important in several system theoretic contexts. For example, see Anderson, B.D.O., Vongpanitlerd, S., 1973.: Network Analysis and Synthesis. Prentice-Hall, Englewood Cliffs, NJ.

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  • Narendra, K.S., Taylor, J.H., 1973. Frequency Domain Criteria for Absolute Stability. Academic Press, New York.

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  • Algorithms similar to the one presented in Section 4.8.2 are given in Demeure, C.J., Mullis, C.T., 1989. The Euclid algorithm and fast computation of cross-covariance and autocovariance sequences. IEEE Transactions on Acoustics, Speech and Signal Processing. ASSP-37, 545–552.

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  • The algorithms presented in Section 4.8.4 is based on Ježek, J., 1990. Conversion of the polynomial continuous-time model to the delta discrete-time and vice versa. Proc. 11th IFAC World Congress, Tallinn, 1990.

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  • For an efficient algorithm for spectral factorization in the polynomial approach, see Kučera, V., 1979. Discrete Linear Control. John Wiley & Sons, Chichester.

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© 2002 Springer-Verlag London

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Söderström, T. (2002). Analysis. In: Discrete-time Stochastic Systems. Advanced Textbooks in Control and Signal Processing. Springer, London. https://doi.org/10.1007/978-1-4471-0101-7_4

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  • DOI: https://doi.org/10.1007/978-1-4471-0101-7_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-649-3

  • Online ISBN: 978-1-4471-0101-7

  • eBook Packages: Springer Book Archive

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