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Exercise 4.16: Eigenvalues and Eigenvectors

From LNTwww

Three correlation matrices

Although the description of Gaussian random variables using vectors and matrices is actually only necessary and makes sense for more than  N=2  dimensions,  here we restrict ourselves to the special case of two-dimensional random variables for simplicity.

In the graph above,  the general correlation matrix  Kx  of the two-dimensional random variable   x=(x1,x2)T   is given,  where  σ21  and  σ22  describe the variances of the individual components.   ρ  denotes the correlation coefficient between the two components.

The random variables   y   and   z   give two special cases of  x  whose process parameters are to be determined from the correlation matrices   Ky   and   Kz   respectively.




Hints:

α=1/2arctan(2ρσ1σ2σ21σ22).
  • In particular,  note:
    • 2×2-covariance matrix has two real eigenvalues  λ1  and  λ2.
    • These two eigenvalues determine two eigenvectors  ξ1  and  ξ2.
    • These span a new coordinate system in the direction of the principal axes of the old system.


Questions

1

Which statements are true for the correlation matrix  Ky ?

Ky  describes all possible two-dimensional random variables with  σ1=σ2=σ.
The value range of the parameter  ρ   is  1ρ+1.
The value range of the parameter  ρ   is  0<ρ<1.

2

Calculate the eigenvalues of  Ky  under the condition  σ=1  and  ρ=0.

λ1 = 

 (λ1λ2)
λ2 = 

 (λ2λ1)

3

Give the eigenvalues of   Ky   under the condition   σ=1   and   0<ρ<1   What values result for  ρ=0.5,  assuming  λ1λ2?

λ1 = 

 (λ1λ2)
λ2 = 

 (λ2λ1)

4

Calculate the corresponding eigenvectors  η1  and  η2.  Which of the following statements are true?

η1  and  η2  lie in the direction of the ellipse main axes.
The new coordinates are rotated by  45.
The standard deviations with respect to the new system are  λ1  and  λ2.

5

What are the characteristics of the random variable  z  specified by  Kz?

σ1= 

σ2= 

ρ= 

6

Calculate the eigenvalues  λ1  and  λ2λ1  of the correlation matrix  Kz.

λ1 = 

 (λ1λ2)
λ2 = 

 (λ2λ1)

7

By what angle  α  is the new coordinate system  (ζ1, ζ2)  rotated with respect to the original system  (z1, z2) ?

α = 

 deg


Solution

(1)  Correct are the  proposed solutions 1 and 2:

  • Ky  is indeed the most general correlation matrix of a two-dimensional random variable with  σ1=σ2=σ.
  • The parameter  ρ  specifies the correlation coefficient.  This can take all values between  ±1  including these marginal values.


(2)  In this case, the governing equation is:

det[1λ001λ]=0(1λ)2=0λ1/2=1_.


(3)  With positive  ρ  the governing equation of the eigenvalues is:

(1λ)2ρ2=0λ22λ+1ρ2=0λ1/2=1±ρ.
  • For  ρ=0.5  one gets  λ1=1.5_  and  λ2=0.5_.
  • By the way,  the equation holds in the whole domain of definition  1ρ+1.
  • For  ρ=0   ⇒   λ1=λ2=+1    ⇒   see subtask  (2).
  • For  ρ=±1   ⇒   λ1=2  and  λ2=0.


(4)  Correct are  the proposed solutions 1 and 2.

The eigenvectors are obtained by substituting the eigenvalues  λ1  and  λ2  into the correlation matrix:

\left[ \begin{array}{cc} 1- (1+\rho) & \rho \\ \rho & 1- (1+\rho) \end{array} \right]\cdot{\boldsymbol{\eta_1}} = \left[ \begin{array}{cc} -\rho & \rho \\ \rho & -\rho \end{array} \right]\cdot \left[ \begin{array}{c} \eta_{11} \\ \eta_{12} \end{array} \right]=0
\Rightarrow\hspace{0.3cm}-\rho \cdot \eta_{11} + \rho \cdot \eta_{12} = 0\hspace{0.3cm}\Rightarrow\hspace{0.3cm}\eta_{11}= {\rm const} \cdot \eta_{12}\hspace{0.3cm}\Rightarrow\hspace{0.3cm}{\boldsymbol{\eta_1}}= {\rm const}\cdot \left[ \begin{array}{c} 1 \\ 1 \end{array} \right];
\left[ \begin{array}{cc} 1- (1-\rho) & \rho \\ \rho & 1- (1-\rho) \end{array} \right]\cdot{\boldsymbol{\eta_2}} = \left[ \begin{array}{cc} \rho & \rho \\ \rho & \rho \end{array} \right]\cdot \left[ \begin{array}{c} \eta_{21} \\ \eta_{22} \end{array} \right]=0
\Rightarrow\hspace{0.3cm}\rho \cdot \eta_{21} + \rho \cdot \eta_{22} = 0\hspace{0.3cm}\Rightarrow\hspace{0.3cm}\eta_{21}= -{\rm const} \cdot \eta_{22}\hspace{0.3cm}\Rightarrow\hspace{0.3cm}{\boldsymbol{\eta_2}}= {\rm const}\cdot \left[ \begin{array}{c} -1 \\ 1 \end{array} \right].
Rotate the coordinate system

Putting this into the  "orthonormal form",  the following holds:

{\boldsymbol{\eta_1}}= \frac{1}{\sqrt{2}}\cdot \left[ \begin{array}{c} 1 \\ 1 \end{array} \right],\hspace{0.5cm} {\boldsymbol{\eta_2}}= \frac{1}{\sqrt{2}}\cdot \left[ \begin{array}{c} -1 \\ 1 \end{array} \right].

The sketch illustrates the result:

  • The coordinate system defined by  \mathbf{\eta_1}  and  \mathbf{\eta_2}  is actually in the direction of the main axes of the original system.
  • With  \sigma_1 = \sigma_2  almost always results  (exception:   \rho= 0)  the rotation angle  \alpha = 45^\circ.
  • This also follows from the equation given in the theory section:
\alpha = {1}/{2}\cdot \arctan (2 \cdot\rho \cdot \frac{\sigma_1\cdot\sigma_2}{\sigma_1^2 -\sigma_2^2})= {1}/{2}\cdot \arctan (\infty)\hspace{0.3cm}\rightarrow\hspace{0.3cm}\alpha = 45^\circ.
  • The eigenvalues  \lambda_1  and  \lambda_2  do not denote the standard deviations with respect to the new axes, but the variances.


(5)  By comparing the matrices   \mathbf{K_x}   and   \mathbf{K_z}   we get.

  • \sigma_{1}\hspace{0.15cm}\underline{ =2},
  • \sigma_{2}\hspace{0.15cm}\underline{ =1},
  • \rho = 2/(\sigma_{1} \cdot \sigma_{2})\hspace{0.15cm}\underline{ =1}.


(6)  According to the now familiar scheme:

(4- \lambda) \cdot (1- \lambda) -4 = 0\hspace{0.3cm}\Rightarrow \hspace{0.3cm}\lambda^2 - 5\lambda = 0\hspace{0.3cm}\Rightarrow\hspace{0.3cm}\hspace{0.15cm}\underline{\lambda_{1} =5,\hspace{0.1cm} \lambda_{2} =0}.


(7)  According to the equation given on the specification sheet:

\alpha ={1}/{2}\cdot \arctan (2 \cdot 1 \cdot \frac{2 \cdot 1}{2^2 -1^2})= {1}/{2}\cdot \arctan ({4}/{3}) = 26.56^\circ.
Best possible decorrelation

The same result is obtained using the eigenvector:

\left[ \begin{array}{cc} 4-5 & 2 \\ 2 & 1-5 \end{array} \right]\cdot \left[ \begin{array}{c} \zeta_{11} \\ \zeta_{12} \end{array} \right]=0 \hspace{0.3cm} \Rightarrow\hspace{0.3cm}-\zeta_{11}= 2\zeta_{12}=0\hspace{0.3cm}\Rightarrow\hspace{0.3cm}\zeta_{12}={\zeta_{11}}/{2}
\Rightarrow\hspace{0.3cm}\alpha = \arctan ({\zeta_{12}}/{\zeta_{11}}) = \arctan(0.5) \hspace{0.15cm}\underline{= 26.56^\circ}.

The accompanying sketch shows the joint PDF of the random variable  \mathbf{z}:

  • Because of  \rho = 1  all values lie on the correlation line with coordinates  z_1  and  z_2 = z_1/2.
  • By rotating by the angle   \alpha = \arctan(0.5) = 26.56^\circ   a new coordinate system is formed.
  • The variance along the axis   \mathbf{\zeta_1}   is  \lambda_1 = 5  (standard deviation  \sigma_1 = \sqrt{5} = 2.236),
  • while in the direction orthogonal to it,  the random variable  \mathbf{\zeta_2}  is not extended  (\lambda_2 = \sigma_2 = 0).