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Let define a n-by-n matrix A and a non-zero vector <math>\vec{x}\in\mathbb{R}^{n}</math>. If there exists a scalar value <math>\lambda</math> which satisfies the vector equationA <math>\vec{x}=\lambda\vec{x}</math>,
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we define \lambda
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  as an eigenvalue of the matrix A
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, and the corresponding non-zero vector \vec{x}
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  is called an eigenvector of the matrix A
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. To determine eigenvalues and eigenvectors a characteristic equation D(\lambda)=det\left(A-\lambda I\right)
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  is used. Here is an example of determining eigenvectors and eigenvalues where the matrix A
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  is given by A=\left[\begin{matrix}-5 & 2\\
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2 & -2
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\end{matrix}\right].
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Then the characteristic equation D(\lambda)=\left(-5-\lambda\right)\left(-2-\lambda\right)-4=\lambda^{2}+7\lambda+6=0.
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  By solving the quadratic equation for \lambda
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, we will have two eigenvalues \lambda_{1}=-1
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  and \lambda_{2}=-6
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. By substituting \lambda's
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  into Eq [eq:1]
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Latest revision as of 11:46, 13 May 2014

Alumni Liaison

Recent Math PhD now doing a post-doctorate at UC Riverside.

Kuei-Nuan Lin