Diagonalising Matrices / Recurrence Relations

In summary, the conversation is about solving a question involving eigenvalues and eigenvectors of a matrix, as well as using diagonalization to find a solution to a recurrence relation. The conversation also discusses how to compare coefficients and how they relate to the recurrence relation. Finally, it concludes with a detailed explanation of how to use diagonalization to find a solution to the recurrence relation and how to find the specific values for the coefficients.
  • #1
Ted123
446
0

Homework Statement



[PLAIN]http://img530.imageshack.us/img530/6672/linn.jpg

The Attempt at a Solution



For parts (a) and (b) I've found the eigenvalues to be [itex]-\frac{1}{3}[/itex] and [itex]-1[/itex] with corresponding eigenvectors [itex]\begin{bmatrix} -1 \\ 3 \end{bmatrix}[/itex] and [itex]\begin{bmatrix} -1 \\ 1 \end{bmatrix}[/itex] respectively.

Now for part (c) I know there is a way of solving this by diagonalising matrices but I can't remember the method.

The recurrence relation can be written as [itex]\begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = \begin{bmatrix} -\frac{4}{3} & -\frac{1}{3} \\ 1 & 0 \end{bmatrix} \begin{bmatrix} a_{n-1} \\ a_{n-2} \end{bmatrix}[/itex]

We can diagonalise [itex]A = \begin{bmatrix} -\frac{4}{3} & -\frac{1}{3} \\ 1 & 0 \end{bmatrix}[/itex] by:

letting [itex]D = \begin{bmatrix} -\frac{1}{3} & 0 \\ 0 & -1 \end{bmatrix}[/itex] and [itex]P = \begin{bmatrix} -1 & -1 \\ 3 & 1 \end{bmatrix}[/itex] so that we have [itex]A= PDP^{-1}[/itex]

Now how do I find [itex]a_n[/itex] from here?
 
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  • #2
I'll give a hint:

[tex]\left( \begin{array}{c} a_n\\ a_{n-1} \end{array}\right)=\left( \begin{array}{cc} -\frac{4}{3} & -\frac{1}{3}\\ 1 & 0 \end{array}\right)\left( \begin{array}{c} a_{n-1}\\ a_{n-2} \end{array}\right)=\left( \begin{array}{cc} -\frac{4}{3} & -\frac{1}{3}\\ 1 & 0 \end{array}\right)^2\left( \begin{array}{c} a_{n-2}\\ a_{n-3} \end{array}\right)=??\left( \begin{array}{c} a_1\\ a_0 \end{array}\right)[/tex]
 
  • #3
micromass said:
I'll give a hint:

[tex]\left( \begin{array}{c} a_n\\ a_{n-1} \end{array}\right)=\left( \begin{array}{cc} -\frac{4}{3} & -\frac{1}{3}\\ 1 & 0 \end{array}\right)\left( \begin{array}{c} a_{n-1}\\ a_{n-2} \end{array}\right)=\left( \begin{array}{cc} -\frac{4}{3} & -\frac{1}{3}\\ 1 & 0 \end{array}\right)^2\left( \begin{array}{c} a_{n-2}\\ a_{n-3} \end{array}\right)=??\left( \begin{array}{c} a_1\\ a_0 \end{array}\right)[/tex]

[itex]\begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = A^{n-1} \begin{bmatrix} a_1 \\ a_0 \end{bmatrix}[/itex]

so how do I use the diagonalisation? EDIT: I see...
 
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  • #4
You use the diagonalization to calculate [tex]A^{n-1}[/tex]. For example

[tex]A^3=(PDP^{-1})(PDP^{-1})(PDP^{-1})=PD^3P^{-1}[/tex]
 
  • #5
micromass said:
You use the diagonalization to calculate [tex]A^{n-1}[/tex]. For example

[tex]A^3=(PDP^{-1})(PDP^{-1})(PDP^{-1})=PD^3P^{-1}[/tex]

I get [itex]\begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = \begin{bmatrix} -\frac{1}{3}\left( -\frac{1}{3} \right) ^{n-1} + (-1)^{n-1} \\ \left( -\frac{1}{3} \right) ^{n-1} - (-1)^{n-1} \end{bmatrix}[/itex]

Reading off the top component, is this the same as the printed formula?
 
  • #6
Well, it requires some reworking. But it's the same thing. So it looks like you've solved it!
 
  • #7
micromass said:
Well, it requires some reworking. But it's the same thing. So it looks like you've solved it!

There's actually a further part to the question:

[PLAIN]http://img703.imageshack.us/img703/273/lin0.jpg

After multiplying through how do I 'compare coefficients'?
 
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  • #8
What happens if you multiply

[tex](x^2+4x+3)(a_0+a_1x+a_2x^2+a_3x^3+...)[/tex]

Multiply these things out. What you get, should be equal to x.
 
  • #9
micromass said:
What happens if you multiply

[tex](x^2+4x+3)(a_0+a_1x+a_2x^2+a_3x^3+...)[/tex]

Multiply these things out. What you get, should be equal to x.

This gives:

[itex]2x = 3a_0 + (4a_0 + 3a_1)x + (a_0 + 4a_1 + 3a_2)x^2 + (a_1 +4a_2 +3a_3)x^3 + (a_2 +4a_3)x^4 + a_3x^5 + \cdots[/itex]

If we equate coefficients we see that

[itex]3a_0 = 0 \Rightarrow a_0 = 0[/itex]

[itex]4a_0 + 3a_1 = 2 \Rightarrow 3a_1 = 2 \Rightarrow a_1 = \frac{2}{3}[/itex]

I could keep going forever but how do I show that the coefficients satisfy the recurrence relation?
 
  • #10
In general, what will the coefficient of xn be? You'll see your recurrence relation popping up...
 
  • #11
micromass said:
In general, what will the coefficient of xn be? You'll see your recurrence relation popping up...

In general the coefficient of [itex]x^n[/itex] is [itex]3a_n + 4a_{n-1} + a_{n-2}[/itex]

How does the link with the recurrence relation?
 
  • #12
Yes. So what does an equal?
 
  • #13
micromass said:
Yes. So what does an equal?

Well for [itex]n\in \mathbb{N} \backslash \{1\}[/itex] ,

[itex]3a_n + 4a_{n-1} + a_{n-2} = 0[/itex]

so [itex]a_n = -\frac{4}{3} a_{n-1} - \frac{1}{3} a_{n-2}[/itex]

which is precisely the recurrence relation!
 
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  • #14
Ted123 said:
Well for [itex]n\in \mathbb{N} \backslash \{1\}[/itex] ,

[itex]3a_n + 4a_{n-1} + a_{n-2} = 0[/itex]

so [itex]a_n = -\frac{4}{3} a_{n-1} - \frac{1}{3} a_{n-2}[/itex]

which is precisely the recurrence relation!

The characteristic polynomial is given by

[itex]c_A (\lambda ) = \begin{vmatrix} \displaystyle -\frac{4}{3} - \lambda & \displaystyle -\frac{1}{3} \\ 1 & -\lambda \end{vmatrix} =0[/itex]

[itex]\Rightarrow (-\frac{4}{3} - \lambda ) \left(-\lambda \right) - ( -\frac{1}{3} ) ( 1) = 0[/itex]

[itex]\displaystyle \Rightarrow \frac{4}{3} \lambda + \lambda ^2 + \frac{1}{3} = 0[/itex]

[itex]\displaystyle \Rightarrow 3\lambda ^2 + 4\lambda + 1=0[/itex]

[itex]\displaystyle \Rightarrow (3\lambda +1)(\lambda +1)=0[/itex]

[itex]\displaystyle \Rightarrow \lambda = -\frac{1}{3}[/itex] or [itex]\lambda = -1[/itex]

[itex]\displaystyle \therefore -\frac{1}{3}[/itex] and [itex]-1[/itex] are eigenvalues of [itex]A[/itex]

The eigenvectors

[itex]\begin{bmatrix} x \\ y \end{bmatrix}[/itex] of A with eigenvalue -1/3 satisfy the vector equation

[itex]\begin{bmatrix} -1 & -\frac{1}{3} \\ 1 & \frac{1}{3} \end{bmatrix} \begin{bmatrix} x \\ y \end{bmatrix} = \begin{bmatrix} 0 \\ 0 \end{bmatrix}[/itex]

which is equivalent to the single linear equation [itex]x = -\frac{y}{3}[/itex]

Hence the eigenvectors of A with eigenvalue -1/3 are [itex]\begin{bmatrix} -\frac{y}{3} \\ y \end{bmatrix}[/itex] where [itex]y \neq 0[/itex]
 
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  • #15
Ted123 said:
The characteristic polynomial is given by

[itex]c_A (\lambda ) = \begin{vmatrix} \displaystyle -\frac{4}{3} - \lambda & \displaystyle -\frac{1}{3} \\ 1 & -\lambda \end{vmatrix} =0[/itex]

[itex]\Rightarrow (-\frac{4}{3} - \lambda ) \left(-\lambda \right) - ( -\frac{1}{3} ) ( 1) = 0[/itex]

[itex]\displaystyle \Rightarrow \frac{4}{3} \lambda + \lambda ^2 + \frac{1}{3} = 0[/itex]

[itex]\displaystyle \Rightarrow 3\lambda ^2 + 4\lambda + 1=0[/itex]

[itex]\displaystyle \Rightarrow (3\lambda +1)(\lambda +1)=0[/itex]

[itex]\displaystyle \Rightarrow \lambda = -\frac{1}{3}[/itex] or [itex]\lambda = -1[/itex]

[itex]\displaystyle \therefore -\frac{1}{3}[/itex] and [itex]-1[/itex] are eigenvalues of [itex]A[/itex]

The eigenvectors

[itex]\begin{bmatrix} x \\ y \end{bmatrix}[/itex] of A with eigenvalue -1/3 satisfy the vector equation

[itex]\begin{bmatrix} -1 & -\frac{1}{3} \\ 1 & \frac{1}{3} \end{bmatrix} \begin{bmatrix} x \\ y \end{bmatrix} = \begin{bmatrix} 0 \\ 0 \end{bmatrix}[/itex]

which is equivalent to the single linear equation [itex]x = -\frac{y}{3}[/itex]

Hence the eigenvectors of A with eigenvalue -1/3 are [itex]\begin{bmatrix} -\frac{y}{3} \\ y \end{bmatrix}[/itex] where [itex]y \neq 0[/itex]

Then

[itex]AP = \begin{bmatrix} -\frac{4}{3} & -\frac{1}{3} \\ 1 & 0 \end{bmatrix} \begin{bmatrix} -1 & -1 \\ 3 & 1 \end{bmatrix}= \begin{bmatrix} \frac{1}{3} & 1 \\ -1 & -1 \end{bmatrix}[/itex]

and

[itex]PD = \begin{bmatrix} -1 & -1 \\ 3 & 1 \end{bmatrix} \begin{bmatrix} -\frac{1}{3} & 0 \\ 0 & -1 \end{bmatrix} = \begin{bmatrix} \frac{1}{3} & 1 \\ -1 & -1 \end{bmatrix}[/itex]

and [itex]P[/itex] is invertible since [itex]\text{det}(P) = (-1)(1) - (-1)(3) - -1+3=2 \neq 0[/itex]

Now [itex]\begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = \begin{bmatrix} -1 & -1 \\ 3 & 1 \end{bmatrix} \begin{bmatrix} -\frac{1}{3} & 0 \\ 0 & -1 \end{bmatrix} ^{n-1} \begin{bmatrix} \frac{1}{2} & \frac{1}{2} \\ -\frac{3}{2} & -\frac{1}{2} \end{bmatrix} \begin{bmatrix} a_1 \\ a_0 \end{bmatrix}[/itex]

[itex]= \begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = \begin{bmatrix} -1 & -1 \\ 3 & 1 \end{bmatrix} \begin{bmatrix} (-\frac{1}{3})^{n-1} & 0 \\ 0 & (-1)^{n-1} \end{bmatrix} \begin{bmatrix} \frac{1}{2} & \frac{1}{2} \\ -\frac{3}{2} & -\frac{1}{2} \end{bmatrix} \begin{bmatrix} \frac{2}{3} \\ 0 \end{bmatrix}[/itex]

[itex]= \begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = \begin{bmatrix} -(-\frac{1}{3})^{n-1} & -(-1)^{n-1} \\ 3(-\frac{1}{3})^{n-1} & (-1)^{n-1} \end{bmatrix} \begin{bmatrix} \frac{1}{3} \\ -1 \end{bmatrix}[/itex]

[itex]\begin{bmatrix} a_n \\ a_{n-1} \end{bmatrix} = \begin{bmatrix} -\frac{1}{3} ( -\frac{1}{3} ) ^{n-1} + (-1)^{n-1} \\ ( -\frac{1}{3} ) ^{n-1} - (-1)^{n-1} \end{bmatrix}[/itex]

Reading off the top component we see that [itex]a_n = -\frac{1}{3} ( -\frac{1}{3} ) ^{n-1} + (-1)^{n-1}[/itex]

[itex]a_n = -\frac{1}{3} ( -\frac{1}{3} ) ^n ( -\frac{1}{3} ) ^{-1} + (-1)^n (-1)^{-1}[/itex]

[itex]a_n = ( -\frac{1}{3} ) ^n - (-1)^n[/itex]

[itex]a_n = \frac{(-1)^n}{3^n} - (-1)^n[/itex]

[itex]a_n = (-1)^n \left( \frac{1}{3^n} - 1 \right)[/itex]
 
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  • #16
[itex]{\bf p}(t) = (f(t)\cos\,t,f(t)\sin\,t)[/itex]

[itex]{\bf p}'(t) = (f'(t)\cos\,t - f(t)\sin\,t , f'(t)\sin\,t + f(t) \cos\,t)[/itex]

[itex]\displaystyle \oint_C -\frac{y}{x^2+y^2} \; dx + \frac{x}{x^2+y^2} \; dy[/itex]

[itex]\displaystyle = \int^{\pi}_{-\pi} \left( -\frac{y}{x^2+y^2} \frac{dx}{dt} + \frac{x}{x^2+y^2} \frac{dy}{dt} \right) \; dt[/itex]

[itex]\displaystyle = \int^{\pi}_{-\pi} \bigg \{ \left( -\frac{f(t)\sin\,t}{f^2(t)\cos^2 \, t} + f^2(t) \sin^2 \, t \right) \left( f'(t) \cos \, t - f(t)\sin \, t \right)[/itex]

[itex] + \left( \frac{f(t)\cos \, t}{f^2(t)\cos^2 \, t} + f^2(t) \sin^2 \, t \right) \left( f'(t)\sin \, t + f(t)\cos \, t \right) \bigg \} \; dt[/itex]

[itex]\displaystyle = \int^{\pi}_{-\pi} \left( -\frac{f(t)f'(t) \sin\,t\cos\,t}{f^2(t)} + \frac{f^2(t)\sin^2 t}{f^2(t)} + \frac{f(t)f'(t) \sin\,t\cos\,t}{f^2(t)} + \frac{f^2(t)\cos^2 t}{f^2(t)} \right) \;dt[/itex]

[itex]\displaystyle = \int^{\pi}_{-\pi} \left( \sin^2 t + \cos^2 t \right) \;dt[/itex]

[itex]\displaystyle = \int^{\pi}_{-\pi} \;dt = \left[ t \right]^{\pi}_{-\pi} = 2\pi[/itex]

----------------------------------------------------------------------------------------------------------------------

2(a) Call the 3 sections of the curve C in the order described in the question [itex]C_1, C_2 ,C_3[/itex] respectively.

Then [itex]\displaystyle \int_C = \int_{C_1+C_2+C_3} = \int_{C_1} + \int_{C_2} + \int_{C_3}[/itex]

So parametrising [itex]C_1 , C_2 , C_3[/itex] as follows,

[itex]C_1[/itex] : For [itex]0 \leq t \leq 1\;,\;p(t) = (1-t)(0,0) + t(R,0) = (tR,0)[/itex]

[itex]p'(t) = (R,0)[/itex]

[itex]C_2[/itex] : For [itex]0 \leq t \leq \frac{\pi}{2}\;,\;p(t) = (R\cos\,t , R\sin\,t)[/itex]

[itex]p'(t) = (-R\sin\,t , R\cos\,t)[/itex]

[itex]C_3[/itex] : For [itex]0 \leq t \leq 1\;,\;p(t) = (1-t)(0,R) + t(0,0) = (0,R-Rt)[/itex]

[itex]p'(t) = (0,-R)[/itex]

Hence [itex]\displaystyle \int_{C_1} = \int_{C_1} \left( -xy^2 \frac{dx}{dt} + x^2y \frac{dy}{dt} \right)\;dt[/itex]

[itex]\displaystyle = \int^1_0 \bigg \{ (-tR)(0)(R) + (R^2)(0)(0) \bigg \}\;dt = 0[/itex]

[itex]\displaystyle \int_{C_2} = \int^{\frac{\pi}{2}}_0 \bigg \{ (-R\cos\,t)(R^2\sin\,t)(-R\sin\,t) + (R^2\cos^2t)(R\sin\,t)(R\cos\,t) \bigg \} \;dt[/itex]

[itex]\displaystyle = R^4 \int^{\frac{\pi}{2}}_0 \left( \cos\,t\,\sin^3t + \sin\,t\,\cos^3\,t \right) \;dt[/itex]

[itex]\displaystyle = R^4 \left( \frac{1}{4} + \frac{1}{4} \right) = \frac{R^4}{2}[/itex]

[itex]\displaystyle \int_{C_3} = \int^1_0 \bigg \{ (0)\left( (R-Rt)^2 \right)(0) + (0)(R-Rt)(-R) \bigg \} \;dt =0[/itex]

Hence [itex]\displaystyle \int_C = 0 + \frac{R^4}{2} + 0 = \frac{R^4}{2}[/itex]

[itex]\sin^3\,t[/itex] and [itex]\cos^3\,t[/itex]

2(b) Let [itex]P = -xy^2[/itex] and [itex]Q = x^2y[/itex]

Then Green's theorem says that [itex]\displaystyle \oint_C P\;dx + Q\;dy = \iint_S \left( \frac{\partial Q}{\partial x} - \frac{\partial P}{\partial y} \right) \;dxdy[/itex]

So (calling the integral I) [itex]\displaystyle I = \iint_S (2xy + 2xy) \;dxdy = \iint_S 4xy\;dxdy[/itex]
 
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1. What is a diagonal matrix?

A diagonal matrix is a square matrix in which all the elements outside of the main diagonal (from top left to bottom right) are equal to zero. This means that all the non-zero elements are present only on the main diagonal.

2. How do you diagonalise a matrix?

To diagonalise a matrix, we need to find a matrix that is similar to the given matrix. This can be done by finding the eigenvectors and eigenvalues of the matrix and using them to create a diagonal matrix through a similarity transformation.

3. What are the benefits of diagonalising a matrix?

Diagonalising a matrix can simplify calculations, as the diagonal elements can be easily raised to a power or multiplied. It also helps in solving systems of linear equations and finding the inverse of a matrix.

4. What are recurrence relations?

Recurrence relations are mathematical equations that describe a sequence of values by relating each term to one or more of the previous terms. They are often used in mathematical modeling and in solving problems involving iterative processes.

5. How do you solve a recurrence relation?

There are various methods for solving recurrence relations, including substitution, iteration, and generating functions. The choice of method depends on the type of recurrence relation and its initial conditions. In some cases, it may also involve using properties of generating functions or using a computer program to find a solution.

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