Math 2.0

Linear and multilinear algebra; matrix theory Definition

Hurwitz-stable matrix

Builds on Square matrixEigenvalue

Definition

Let AA be an n×nn \times n square matrix with real or complex entries. The matrix AA is Hurwitz-stable if every eigenvalue λ\lambda of AA satisfies Re⁡λ<0\operatorname{Re} \lambda < 0.

Remarks

Equivalently, etA→0e^{tA} \to 0 as t→∞t \to \infty, that is, the origin is asymptotically stable for x′=Axx' = Ax. Then there are C≥1C \ge 1 and α>0\alpha > 0 with ∥etA∥≤Ce−αt\norm{e^{tA}} \le C e^{-\alpha t} for all t≥0t \ge 0. A real matrix AA is Hurwitz-stable if and only if, for one (equivalently, every) positive definite matrix QQ, the Lyapunov equation ATP+PA=−QA^T P + P A = -Q has a positive definite solution PP.

Example: A=(−120−3)A = \begin{pmatrix} -1 & 2 \\ 0 & -3 \end{pmatrix}. It is triangular, so its eigenvalues are its diagonal entries −1-1 and −3-3, both with negative real part.

Non-example: A=(01−10)A = \begin{pmatrix} 0 & 1 \\ -1 & 0 \end{pmatrix}. Its eigenvalues are ±i\pm i, with real part 00, so AA is not Hurwitz-stable; the solutions of x′=Axx' = Ax are rotations that do not decay.

For a real matrix, the condition can be tested on the coefficients of the characteristic polynomial by the Routh–Hurwitz criterion.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Hurwitz-stable_matrix
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MSC15A18, 34D20
DefinesHurwitz-stable matrix
UsesSquare matrix, Eigenvalue
Changed2 November 2026

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