In mathematics, the spectral abscissa of a matrix or a bounded linear operator is the greatest real part of the matrix's spectrum (its set of eigenvalues).[1] It is sometimes denoted . As a transformation , the spectral abscissa maps a square matrix onto its largest real eigenvalue.[2]

Matrices

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Let λ1, ..., λs be the (real or complex) eigenvalues of a matrix ACn × n. Then its spectral abscissa is defined as:

 

In stability theory, a continuous system represented by matrix   is said to be stable if all real parts of its eigenvalues are negative, i.e.  .[3] Analogously, in control theory, the solution to the differential equation   is stable under the same condition  .[2]

See also

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References

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  1. ^ Deutsch, Emeric (1975). "The Spectral Abscissa of Partitioned Matrices" (PDF). Journal of Mathematical Analysis and Applications. 50: 66–73. doi:10.1016/0022-247X(75)90038-4 – via CORE.
  2. ^ a b Burke, J. V.; Lewis, A. S.; Overton, M. L. (2000). "OPTIMIZING MATRIX STABILITY" (PDF). Proceedings of the American Mathematical Society. 129 (3): 1635–1642. doi:10.1090/S0002-9939-00-05985-2.
  3. ^ Burke, James V.; Overton, Micheal L. (1994). "DIFFERENTIAL PROPERTIES OF THE SPECTRAL ABSCISSA AND THE SPECTRAL RADIUS FOR ANALYTIC MATRIX-VALUED MAPPINGS" (PDF). Nonlinear Analysis, Theory, Methods & Applications. 23 (4): 467–488. doi:10.1016/0362-546X(94)90090-6 – via Pergamon.