Math 2.0

Linear and multilinear algebra; matrix theory Definition

Stein equation

Builds on Square matrixHermitian matrixConjugate transposeLyapunov equationSpectral radiusPositive definite matrix

Definition

Let n≥1n \ge 1, let AA be an n×nn \times n complex matrix, and let QQ be an n×nn \times n Hermitian matrix. Write A∗A^* for the conjugate transpose of AA. The Stein equation for AA and QQ is X−AXA∗=QX - A X A^* = Q for an unknown n×nn \times n complex matrix XX.

Remarks

It is the discrete Lyapunov equation AXA∗−X+Q=0AXA^* - X + Q = 0. More generally, the name is used for X−AXB=CX - AXB = C with given AA, BB, CC. This equation has a unique solution exactly when λμ≠1\lambda \mu \ne 1 for every eigenvalue λ\lambda of AA and every eigenvalue μ\mu of BB. If the spectral radius of AA is less than 11, the unique solution is X=∑k=0∞AkQ(A∗)kX = \sum_{k=0}^{\infty} A^k Q (A^*)^k, and XX is positive definite when QQ is. Example: for n=1n = 1, A=1/2A = 1/2 and Q=3Q = 3, the equation reads X−X/4=3X - X/4 = 3, so X=4X = 4; the series gives 3∑k≥04−k=43 \sum_{k \ge 0} 4^{-k} = 4 as well. Non-example of solvability: for n=1n = 1, A=1A = 1 and Q=1Q = 1, the equation reads 0=10 = 1 and has no solution, since λλˉ=1\lambda \bar{\lambda} = 1 for the eigenvalue λ=1\lambda = 1.

Reading path

To understand this page from the ground up, read these 7 pages in order. The foundations come first.

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  1. Conjugate transpose concept
  2. Hermitian matrix concept
  3. Lyapunov equation concept
  4. Positive definite matrix concept
  5. Spectral radius concept
  6. Square matrix concept
  7. Stein equation definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Lyapunov_equation
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TagW90XPR88E8
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MSC15A24, 39B42, 93D05
DefinesStein equation
UsesSquare matrix, Hermitian matrix, Conjugate transpose, Lyapunov equation, Spectral radius, Positive definite matrix

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