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2020 | OriginalPaper | Chapter

Nonlinearity Estimation of Digital Signals

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Abstract

Assessing the nonlinearity of one signal, system, or dependence of one signal on another is of great importance in the design process. The article proposes an algorithm for simplified nonlinearity estimation of digital signals. The solution provides detailed information to constructors about existing nonlinearities, which in many cases is sufficient to make the correct choice of processing algorithms. The programming code of the algorithm is presented and its implementation is demonstrated on a set of basic functions. Several steps to further development of the proposed approach are outlined.

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Literature
5.
go back to reference Bar-Shalom, Y., Forthmann, T.: Tracking and Data Association. Academic Press, San Diego (1988) Bar-Shalom, Y., Forthmann, T.: Tracking and Data Association. Academic Press, San Diego (1988)
6.
go back to reference Bar-Shalom, Y. (ed.): Multitarget-Multisensor Tracking: Advanced Applications. Norwood, Chicago (1990) Bar-Shalom, Y. (ed.): Multitarget-Multisensor Tracking: Advanced Applications. Norwood, Chicago (1990)
7.
go back to reference Bar-Shalom, Y., Li, X.R.: Multitarget-Multisensor Tracking: Principles and Techniques. Artech House, Boston (1993) Bar-Shalom, Y., Li, X.R.: Multitarget-Multisensor Tracking: Principles and Techniques. Artech House, Boston (1993)
9.
go back to reference Blom, H.A.P., Bloem, E.A.: Joint IMM and coupled PDA to track closely spaced targets and to avoid track coalescence. In: Proceedings of the Seventh International Conference on Information Fusion, pp. 130–137 (2005) Blom, H.A.P., Bloem, E.A.: Joint IMM and coupled PDA to track closely spaced targets and to avoid track coalescence. In: Proceedings of the Seventh International Conference on Information Fusion, pp. 130–137 (2005)
10.
go back to reference Beale, E.M.L.: Confidence regions in non-linear estimation. J. Roy. Stat. Soc. Ser. B (Methodol.) 22(1), 41–88 (1960)MathSciNetMATH Beale, E.M.L.: Confidence regions in non-linear estimation. J. Roy. Stat. Soc. Ser. B (Methodol.) 22(1), 41–88 (1960)MathSciNetMATH
11.
go back to reference Desoer, C.A., Wang, Y.T.: Foundations of feedback theory for nonlinear dynamical systems. IEEE Trans. Circ. Syst. 27(2), 104–123 (1980)MathSciNetCrossRef Desoer, C.A., Wang, Y.T.: Foundations of feedback theory for nonlinear dynamical systems. IEEE Trans. Circ. Syst. 27(2), 104–123 (1980)MathSciNetCrossRef
13.
go back to reference Emancipator, K., Kroll, M.H.: A quantitative measure of nonlinearity. Clin. Chem. 39(5), 766–772 (1993)CrossRef Emancipator, K., Kroll, M.H.: A quantitative measure of nonlinearity. Clin. Chem. 39(5), 766–772 (1993)CrossRef
14.
go back to reference Tugnait, J.K.: Testing for linearity of noisy stationary signals. IEEE Trans. Signal Process. 42(10), 2742–2748 (1994)CrossRef Tugnait, J.K.: Testing for linearity of noisy stationary signals. IEEE Trans. Signal Process. 42(10), 2742–2748 (1994)CrossRef
15.
go back to reference Allgower, F.: Definition and Computation of a Nonlinearity Measure. IFAC Nonlinear Control Systems Design, Tahoe City, California, USA (1995) Allgower, F.: Definition and Computation of a Nonlinearity Measure. IFAC Nonlinear Control Systems Design, Tahoe City, California, USA (1995)
16.
go back to reference Helbig, A., Marquardt, W., Allgower, F.: Nonlinearity measures: definition, computation and applications. J. Process Control 10, 113–123 (2000)CrossRef Helbig, A., Marquardt, W., Allgower, F.: Nonlinearity measures: definition, computation and applications. J. Process Control 10, 113–123 (2000)CrossRef
17.
go back to reference Barnett, A.G., Wolff, R.C.: A time-domain test for some types of nonlinearity. IEEE Trans. Signal Process. 53(1), 26–33 (2005) MathSciNetCrossRef Barnett, A.G., Wolff, R.C.: A time-domain test for some types of nonlinearity. IEEE Trans. Signal Process. 53(1), 26–33 (2005) MathSciNetCrossRef
18.
go back to reference Hosseini, S.M., Johansen, T.A., Fatehi, A.: Comparison of nonlinearity measures based on time series analysis for nonlinearity detection. Model. Identif. Control 32(4), 123–140 (2011). ISSN 1890-1328CrossRef Hosseini, S.M., Johansen, T.A., Fatehi, A.: Comparison of nonlinearity measures based on time series analysis for nonlinearity detection. Model. Identif. Control 32(4), 123–140 (2011). ISSN 1890-1328CrossRef
19.
go back to reference Haber, R.: Nonlinearity test for dynamic process. In: IFAC Identification and system Parameter Estimation (1985) Haber, R.: Nonlinearity test for dynamic process. In: IFAC Identification and system Parameter Estimation (1985)
21.
22.
go back to reference Shi, W., Cheung, C.: Performance evaluation of line simplification algorithms for vector generalization. Cartographic J. 43(1), 27–44 (2006)CrossRef Shi, W., Cheung, C.: Performance evaluation of line simplification algorithms for vector generalization. Cartographic J. 43(1), 27–44 (2006)CrossRef
Metadata
Title
Nonlinearity Estimation of Digital Signals
Author
Kiril Alexiev
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-39237-6_5

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