Abstract
System theory is a discipline which applies mathematical methods in order to provide a unified approach for many application areas. Such a unification is not only useful for communication between experts, but also in order to be able to carry over concepts, methods and software between areas. Also intellectually such a unified approach is mandatory since the same mathematical results are reused and the same derivations apply in the different application areas. The first aim of this contribution is to discover some common grounds in signal processing, circuit theory and some other engineering areas. Second the impact of singular value decomposition and its generalizations will be discussed. Third it will be shown how system theory can provide a unified approach to the problems and open up new avenues in these fields.
L. Vandenberghe and M. Moonen are supported by the N.F.W.O. (Belgian National Fund of Scientific Research).
Preview
Unable to display preview. Download preview PDF.
References
Willems J.C., “Dissipative dynamical systems, part I General Theory; part II Linear systems with quadratic supply rates” Arch. Rational Mech. Analysis Vol. 45 pp. 321–351; pp. 352–393, 1972.
Willems J.C., “System theoretic models for the analysis of physical systems”, Richerche di Automatica, Vol. 10, no. 2, pp. 71–106, 1979.
Willems J.C., “From times series to linear systems, parts I, II” Automatica, Vol. 21, 1986, pp. 561–580 and pp. 675–694, Vol. 23, 1987, pp. 87–115.
Anderson B.D.O. and Vongpanitlerd S., “Network analysis and synthesis”, Prentice Hall, Englewood Cliffs 1973.
Willsky A.S., “Relationships between digital signal processing and control and estimation theory”, Proc. IEEE, Vol. 66, no. 2, pp. 996–1027, 1978.
“Matlab Manual”, The Mathworks, Mass. 1985.
Mees A.I. and Sparrow C.T., “Chaos”, IEE Proc., Vol. 128, Pt. D, No. 5, Sept. 1981, pp. 201–205.
Sugarman R. and Wallich P. “The limits to simulation.” IEEE Spectrum, p. 36–41, April 1983.
Chua L.O., Komuro M., and Matsumoto T., “The double scroll family Part I, II”, IEEE Trans. on Circuits and Systems, Vol. CAS-33, Nov. 1986, pp. 1072–1097, pp. 1097–1118.
Chua L.O., “Dynamic nonlinear networks: State-of-the-art”, IEEE Trans. on Circuits and Systems, Vol. CAS-27, pp. 1014–1044, Nov. 1980.
Abraham R. and Shaw C., “Dynamics — the geometry of behaviour, part 1,2,3” The visual mathematics library, Aerial Press, Santa Cruz, CA, 1985.
Van Dooren P., “Numerical linear algebra: An increasing interest in linear system theory.”, Proc. ECCTD The Hague, 1981, pp. 243–251.
Staar J., Wemans M. and Vandewalle J., “Comparison of multivariable MBH realization algorithms in the presence of multiple poles, and noise disturbing the Markov sequence”, in “Analysis and Optimization of Systems”, ed. by A. Bensoussan and J.L. Lions, Springer Verlag, pp. 141–160, Berlin, 1980.
Staar J. and Vandewalle J., “Numerical implications of the choice of a reference node in the nodal analysis of large circuits”, Int. Journal of Circuit Theory and Applications, Vol. 9, pp. 488–492, 1981.
Staar J. and Vandewalle J., “Singular value decomposition: A reliable tool in the algorithmic analysis of linear systems.”, Journal A, Vol. 23, pp. 69–74, 1982.
Vandewalle J. and Staar J., “Modelling of linear systems: critical examples, problems of numerically reliable approaches.”, Proc. IEEE Int. Symp. on Circuits and Systems, ISCAS-82, Rome, pp. 915–918, 1982.
Vandewalle J., Vanderschoot J. and De Moor B., “Source separation by adaptive singular value decomposition.”, Proc. IEEE ISCAS Conf. Kyoto 5–7 June 1985, pp. 1351–1354.
Vanderschoot J., Callaerts D., Sansen W., Vandewalle J., Vantrappen G., Janssens J., “Two methods for optimal MECG elimination and FECG detection from skin electrode signals.”, IEEE Trans. on Biomedical Engineering, Vol. BME-34, no. 3, pp. 233–243, March 1987.
De Moor B., Vandewalle J., “Non-conventional matrix calculus in the analysis of rank deficient Hankel matrices of finite dimensions.”, System and Contr. Lett., Vol. 9, pp. 401–410, 1987.
De Moor B., Vandewalle J., “An adaptive singular value decomposition algorithm based on generalized Chebyshev recursions.” in: Mathematics in signal processing, T.S. Durrani, J.B. Abbiss, J.E. Hudson, R.N. Madan, J.G. McWirther and T.A. Moore (ed.), Clarendon Press Oxford, 1987, pp. 607–635.
De Moor B., Staar J. and Vandewalle, “Oriented energy and oriented signal-to-signal ratio concepts in the analysis of vector sequences ant time series.”, in “SVD and Signal Processing” E. Deprettere (ed.), North Holland, 1988, pp. 209–232.
Van Huffel S., Vandewalle J., “The total least squares technique: computation, properties and applications.”, in “SVD and Signal Processing” E. Deprettere (ed.), North Holland, 1988, pp. 189–207.
Vandewalle J., De Moor B., “A variety of applications of singular value decomposition in identification and signal processing.” in “SVD and Signal Processing” E. Deprettere (ed.), North Holland, 1988, pp. 43–91.
Callaerts D., Vandewalle J., Sansen W. and Moonen M., “On-line algorithm for signal separation based on SVD.” in “SVD and Signal Processing” E. Deprettere (ed.), North Holland, pp. 269–276, 1988.
De Moor B., Moonen M., Vandenberghe L. and Vandewalle J., “Identification of linear state space models with singular value decomposition using canonical correlation concepts.”, in “SVD and Signal Processing” E. Deprettere (ed.), North Holland, pp. 161–169, 1988.
De Moor B., Vandewalle J., Moonen M., Van Mieghem P. and Vandenberghe L., “A geometrical strategy for the identification of state space models of linear multivariable systems with singular value decomposition.”, Preprints 8th IFAC/IFORS Symposium on identification and system parameter estimation, Beijing, August 27–31, 1988, pp. 700–704.
Vandewalle J., “Trends in the need of mathematics for engineering and the impact on engineering education.”, SEFI, Proc. 5th European Seminar on Mathematics in Engineering Education, Plymouth, March 23–26, 1988, pp. 94–105.
De Moor B., Moonen M., Vandenberghe L. and Vandewallc J., “The application of the canonical correlation concept to the identification of linear state space models”, in A. Bensousan, J.L. Lions, (Eds) Analysis and Optimization of Systems, Springer Verlag, Heidelberg, 1988, pp. 1103–1114.
Van Belle H. en Van Brussel H., “Inleiding tot de systeemtheorie. Pleidooi voor een ruimere tocpassing.”, Het Ingenieursblad, no. 12, 1979.
Autonne L., “Sur les groupes linéaires, réelles et orthogonaux”, Bull. Soc. Math., France, Vol. 30, pp. 121–133, 1902.
De Moor B., Golub G.H., “Generalized singular value decompositions: A proposal for a standardized nomenclature.” Internal Report, Department of Computer Science, Stanford University, January 1989 (submitted for publication).
De Moor B., Golub G.H., “The restricted singular value decomposition: properties and applications.” Internal Report, Department of Computer Science, Stanford University, March 1989 (submitted for publication).
Deprettere Ed. (Editor), “SVD and Signal Processing: Algorithms, Applications and Architectures”, North Holland, 1988.
Doyle J.C. “Analysis of feedback systems with structured uncertainties.” Proc. IEE, Vol. 129, no. 6, pp. 242–250, Nov. 1982.
Eckart G., Young G., “The approximation of one matrix by another of lower rank.”, Psychometrika, 1: 211–218, 1936.
Fan M.K.H., Tits A.L., “Characterization and efficient computation of the structured singular value.”, IEEE Trans. Automatic Control, Vol. AC-31, no. 8, August 1986, pp. 734–743.
Fernando K.V., Hammarling S.J., “A Product Induced Singular Value Decomposition for two matrices and balanced realisation.”, NAG Technical Report, TR8/87.
Paige C.C., Saunders M.A., “Towards a generalized singular value decomposition.”, SIAM J. Numer. Anal., 18, pp. 398–405, 1981.
Takagi T., “On an algebraic problem related to an analytic theorem of Caratheodory and Fejer and on an allied theorem of Landau.”, Japan. J. Math., 1, pp. 83–93, 1925.
Van Loan C.F., “Generalizing the singular value decomposition.” SIAM J. Numer. Anal., 13, pp. 76–83, 1976.
Zha H., “Restricted SVD for matrix triplets and rank determination of matrices.” Scientific Report 89-2, Berlin (submitted for publication).
Damen A.A.H., Van den Hof P.M.J., Hajdasinski A.K., “Approximate realization based upon an alternative to the Hankel matrix: the Page matrix.”, Systems and Control Letters, Vol.II, No. 4, pp. 202–208, 1982.
De Moor B., “Mathematical Concepts and techniques for modelling static and dynamic systems”, Doct. Diss., K.U.Leuven, 1988.
Golub G.H. and Van Loan C.F., “Matrix computations.”, North Oxford Academic Publishing Co., Johns Hopkins University Press, 1983.
Golub G.H., Van Loan C.F., “An analysis of the total least squares problem.”, SIAM J. Numer. Anal., Vol. 17, No. 6, pp. 883–893, 1980.
Kung S.Y., “A new identification and model reduction algorithm via singular value decomposition.”, Proc. 12th Asilomar Conf. on Circuits, Systems and Computers. Pacific Grove, pp. 705–714, 1978.
Moonen M., De Moor B., Vandenberghe L., Vandewalle J., “On-and off-line identification of linear state space models”, International Journal of Control, Vol. 49, No. 1, pp. 219–232, 1989.
Van Huffel S., “Analysis of the total least squares problem and its use in parameter estimation.”, Doct. Diss. K.U.Leuven, 1987.
Van Huffel S., “Analysis and properties of the generalized total least squares problem AX ≠ B when some or all columns in A are subject to error.”, SIAM J. Matrix Anal. Appl., to appear 1989.
Zeiger H.P. and McEwen A.J., “Approximate linear realizations of given dimensions via Ho's algorithm.”, IEEE Trans. Aut. Control, vol. AC-19, (pp. 153), 1974.
Van den Hof P., “On residual-based parametrization and identification of multivariable systems”, Doct. Diss. T.U.Eindhoven, 1989.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1989 Springer-Verlag
About this chapter
Cite this chapter
Vandewalle, J., Vandenberghe, L., Moonen, M. (1989). The impact of the singular value decomposition in system theory, signal processing, and circuit theory. In: Nijmeijer, H., Schumacher, J.M. (eds) Three Decades of Mathematical System Theory. Lecture Notes in Control and Information Sciences, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0008473
Download citation
DOI: https://doi.org/10.1007/BFb0008473
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-51605-7
Online ISBN: 978-3-540-46709-0
eBook Packages: Springer Book Archive