[Linear Algebra] Closed formula for recursive sequence

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The discussion revolves around finding a closed formula for a recursive sequence using a matrix representation. Participants are trying to derive the correct matrix A that maps a vector of initial values to a vector of subsequent values. The equations for the matrix elements are established, with some initial values proposed, but there are questions about their correctness. It is clarified that while multiple matrices might seem possible, only one matrix A will satisfy the recursion for all values. Ultimately, the focus is on ensuring that the derived matrix correctly reflects the relationships defined by the recursive sequence.
reminiscent
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Homework Statement


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Homework Equations


a) the one given
b) det(A-λI) = 0
find λ values using A
c)use λ values to find eigenvectors

The Attempt at a Solution


This wasn't explained well enough so I can understand it in class. So far, I made the matrix being multiplied to A have the following elements from top to bottom: x0 = 1, x1 = 1, x2 = 2. The one on the right has the following elements: x1 = 1, x2= 2, x3=7. Is this correct thinking? Do I just find a matrix A that maps the vector on the left to the vector on the right?
I know how to do b) and c), I just don't know how to get A correctly.
 
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reminiscent said:
So far, I made the matrix being multiplied to A have the following elements from top to bottom: x0 = 1, x1 = 1, x2 = 2

The usual way to describe an element of a matrix is to give it two indices, such as A[1][1] , A[1][2] or ## A_{1,1}, A_{1,2} ## etc. Which elements are you trying to describe with the phrase "from top to bottom" ?

You need a matrix A such that:

eq. 1: A_{1,1} x_k + A_{1,2} x_{k+1} + A_{1,3} x_{k+2} = x_{k+1}
eq 2: A_{2,1} x_k + A_{2,2} x_{k+1} + A_{2,3} x_{k+2} = x_{k+2}
eq 3: A_{3,1} x_k + A_{3,2} x_{k+1} + A_{3,3} x_{k+2} = x_{k+3}

An solution to eq. 1 is A_{1,1} = 0, A_{1,2} = 1, A_{1,3} = 0.
 
Stephen Tashi said:
The usual way to describe an element of a matrix is to give it two indices, such as A[1][1] , A[1][2] or ## A_{1,1}, A_{1,2} ## etc. Which elements are you trying to describe with the phrase "from top to bottom" ?

You need a matrix A such that:

eq. 1: A_{1,1} x_k + A_{1,2} x_{k+1} + A_{1,3} x_{k+2} = x_{k+1}
eq 2: A_{2,1} x_k + A_{2,2} x_{k+1} + A_{2,3} x_{k+2} = x_{k+2}
eq 3: A_{3,1} x_k + A_{3,2} x_{k+1} + A_{3,3} x_{k+2} = x_{k+3}

An solution to eq. 1 is A_{1,1} = 0, A_{1,2} = 1, A_{1,3} = 0.
Sorry, I completely forgot that A was a 3x3 matrix.
Anyways, I see how you are getting the solutions.
For equation 2, I found these solutions:
A21 = 0 A22 =0 A23= 1
For equation 3, I found:
A31 = 0 A32 = 1 A33 =3

Are those correct? Does what they give for xk+3 have anything to do with the last equation?
 
Stephen Tashi said:
The usual way to describe an element of a matrix is to give it two indices, such as A[1][1] , A[1][2] or ## A_{1,1}, A_{1,2} ## etc. Which elements are you trying to describe with the phrase "from top to bottom" ?

You need a matrix A such that:

eq. 1: A_{1,1} x_k + A_{1,2} x_{k+1} + A_{1,3} x_{k+2} = x_{k+1}
eq 2: A_{2,1} x_k + A_{2,2} x_{k+1} + A_{2,3} x_{k+2} = x_{k+2}
eq 3: A_{3,1} x_k + A_{3,2} x_{k+1} + A_{3,3} x_{k+2} = x_{k+3}

An solution to eq. 1 is A_{1,1} = 0, A_{1,2} = 1, A_{1,3} = 0.
So A can be more than 1 matrix?
 
reminiscent said:
Sorry, I completely forgot that A was a 3x3 matrix.
Anyways, I see how you are getting the solutions.
For equation 2, I found these solutions:
A21 = 0 A22 =0 A23= 1
For equation 3, I found:
A31 = 0 A32 = 1 A33 =3

Are those correct? Does what they give for xk+3 have anything to do with the last equation?

You can (and should) check that for yourself. When you substitute in your values for ##A_{31}, A_{32}## and ##A_{33}## do you get the correct recursion?

And, for your next question in post #4, why do you think there is more than one matrix? The matrix ##A## has 9 elements called ##A_{11}, A_{12} \ldots, A_{33}##.
 
Ray Vickson said:
You can (and should) check that for yourself. When you substitute in your values for ##A_{31}, A_{32}## and ##A_{33}## do you get the correct recursion?

And, for your next question in post #4, why do you think there is more than one matrix? The matrix ##A## has 9 elements called ##A_{11}, A_{12} \ldots, A_{33}##.
Yes, I do. I just changed the bottom row of A to be the constants of the recursive formula given, but I kept the first 2 rows I stated the same. I verified and got the eigenvalues in b.
I thought there was more than one matrix because in the equations, there are a combination of values for each element in A that can produce the desired elements. But it seems like there will be only one because the eigenvalues have to be verified, correct?
 
reminiscent said:
Yes, I do. I just changed the bottom row of A to be the constants of the recursive formula given, but I kept the first 2 rows I stated the same. I verified and got the eigenvalues in b.
I thought there was more than one matrix because in the equations, there are a combination of values for each element in A that can produce the desired elements. But it seems like there will be only one because the eigenvalues have to be verified, correct?

I have no idea what you are saying.

While it is the case that IF you apply the matrix to some smal number of initial values like ##x_0=1,x_1=, x_2 =2## (and a few more obtained from the recursion) you will get numbers on the left and numbers on the right, so will have equations like
$$ A_{31}\: \text{number one} + A_{32}\: \text{number two} + A_{33} \:\text{number three} = \text{number four} $$
with actual numbers. Of course you can have many possible values of ##A_{31}, A_{32}, A_{33}## that "work". However, that is irrelevant: you are supposed to find a matrix that works for all values of ##x_k, x_{k+1}, x_{k+2}, x_{k+3}## that you will ever encounter in the calculations (say for ##x_{27}, x_{28}, x_{29}, x_{30}## or for ##x_{1000}, x_{1001}, x_{1002}, x_{1003}##, etc.) and when you use that fact there can be only one possible choice for the three numbers ##A_{31}, A_{32}, A_{33}##. There is only one matrix ##A##.
 
Last edited:
reminiscent said:
Are those correct?

You solution for eq. 3 doesn't work. Your solution gives x_{k+2} = x_{k+3}.

Does what they give for xk+3 have anything to do with the last equation?
Yes !
 
Stephen Tashi said:
You solution for eq. 3 doesn't work. Your solution gives x_{k+2} = x_{k+3}.Yes ! (I see by post #6 that you figured it out.)
 

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