Skip to main content
Log in

On the numerical solution of nonlinear eigenvalue problems

Über die numerische Lösung nichtlinearer Eigenwertprobleme

  • Published:
Computing Aims and scope Submit manuscript

Abstract

We consider the numerical solution of the nonlinear eigenvalue problemA(λ)x=0, where the matrixA(λ) is dependent on the eigenvalue parameter λ nonlinearly. Some new methods (the BDS methods) are presented, together with the analysis of the condition of the methods. Numerical examples comparing the methods are given.

Zusammenfassung

Wir betrachten die numerische Lösung des nichtlinearen EigenwertproblemsA(λ)x=0, wobei die MatrixA(λ) in nichtlinearer Weise vom Eigenwertparameter λ abhängt. Einige neue Methoden (die BDS Methoden) werden zusammen mit einer Untersuchung der Bedingungen dieser Methoden vorgestellt. Numerische Beispiele, welche diese Methoden vergleichen, werden präsentiert.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Andrew, A.L.: Eigenvalue problems with nonlinear dependence on the eigenvalue parameter: a bibiography. Technical Report, Department of Mathematics, La Trobe University, Bundoora, Victoria, Australia 1974.

    Google Scholar 

  2. Andrew, A.L., Chu, K.-w.E., Lancaster, P.: Derivatives of eigenvalues and eigenvectors of matrix functions. SIAM J. Matrix Anal. Appl.14, 903–926 (1993).

    Article  Google Scholar 

  3. Chu, K.-w.E.: Deferred correction for the ordinary differential equation eigenvalue problem. Bull. Austral. Math. Soc.26, 445–454 (1982).

    Google Scholar 

  4. Chu, K.-w.E.: Bordered matrices, singular systems and ergodic Markov chains. SIAM J. Sci. Stat. Comp.11, 688–701 (1990).

    Article  Google Scholar 

  5. Chu, K.-w.E.: Numerical solution of nonlinear eigenvalue problems for rectangular matrices. Applied Mathematics Reports and Preprints, Mathematics Department, Monash University, Report Number 94/49, 1994.

  6. Chu, K.-w.E., Govaerts, W., Spence, A.: Matrices with rank deficiency two in eigenvalue problems and dynamical systems. SIAM J. Numer. Anal.31, 524–539 (1994).

    Article  Google Scholar 

  7. Chu, K.-w.E., Spence, A.: The improvement of approximate solutions of the integral equation eigenvalue problem. J. Austral. Math. Soc. (Ser. B)8, 474–487 (1981).

    Google Scholar 

  8. Golub, G., Van Loan, C.F.: 1989, Matrix computations, 2nd ed. Baltimore: Johns Hopkins University Press 1989.

    Google Scholar 

  9. Griewank, A., Reddien, G.: Characterization and computation of generalized turning points. SIAM J. Numer. Anal.21, 176–185 (1984).

    Article  Google Scholar 

  10. Haftka, R.T., Adelman, H.M.: Recent developments in structural sensitivity analysis. Struct. Optim.1, 137–151 (1989).

    Article  Google Scholar 

  11. Jennings, L.S., Osborne, M.R.: Generalized eigenvalue problems for rectangular matrices. J. Inst. Math. Appl.20, 443–458 (1977).

    Google Scholar 

  12. Khazanov, V.B., Kublanovskaya, V.N.: Spectral problems for matrix pencils: methods and algorithms. II. Sov. J. Numer. Anal. Math. Modelling.3, 467–485 (1988).

    Google Scholar 

  13. Lancaster, P.: A generalized Rayleigh quotient iteration for lambda-matrices. Arch. Rat. Mech. Anal.8, 309–322 (1961).

    Google Scholar 

  14. Lancaster, P.: Some applications of the Newton-Raphson methods to nonlinear matrix problems. Proc. R. Soc. London Ser. A271, 324–331 (1963).

    Google Scholar 

  15. Lancaster, P.: Algorithms for lambda-matrices. Numer. Math.6, 388–394 (1964).

    Article  Google Scholar 

  16. Lancaster, P.: Lambda-matrices and vibrating systems. Oxford: Pergamon Press 1966.

    Google Scholar 

  17. Lancaster, P.: A review of numerical methods for eigenvalue problems nonlinear in the parameter. ISNM38, 43–67 (1977).

    Google Scholar 

  18. Neumaier, A.: Residual inverse iteration for the nonlinear eigenvalue problem. SIAM J. Numer. Anal.22, 914–923 (1985).

    Article  Google Scholar 

  19. Peters, G., Wilkinson, J.H.: Inverse iteration, ill-conditioned equations and Newton's method. SIAM Rev.21, 339–360 (1979).

    Article  Google Scholar 

  20. Ruhe, A.: Algorithms for the nonlinear eigenvalue problem. SIAM J. Numer. Anal.10, 674–689 (1973).

    Article  Google Scholar 

  21. Symm, H.J., Wilkinson, J.H.: Realistic error bounds for a simple eigenvalue and its associate eigenvector. Numer. Math.35, 113–126 (1980).

    Article  Google Scholar 

  22. Wilkinson, J.H.: The algebraic eigenvalue problem. Oxford: Oxford University Press 1965.

    Google Scholar 

  23. Wobst, R.: The generalized eigenvalue problem and accoustic surface wave computations. Computing39, 57–69 (1987).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Andrew, A.L., Chu, E.K. & Lancaster, P. On the numerical solution of nonlinear eigenvalue problems. Computing 55, 91–111 (1995). https://doi.org/10.1007/BF02238095

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02238095

AMS Subject Classifications

Key words

Navigation