M^5v given that M = [3 2 4 2 0 2 4 2 3]

  • Thread starter squenshl
  • Start date
In summary, "M^5v" refers to the result of multiplying the matrix M by the vector v, with the exponent 5 indicating that the multiplication is performed 5 times. The matrix M has a size of 3 rows and 3 columns, and to calculate the value of "M^5v", you would need to multiply M by itself 5 times and then by v. The values in M represent coefficients in a system of linear equations, and M can be multiplied by any vector as long as the dimensions are compatible.
  • #1
squenshl
479
4
Hi,
Just wondering how to calculate M^5v given that
M = [3 2 4
2 0 2
4 2 3].
and v = (1,0,-1). v being a column vector.
 
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  • #2


v is an eigenvector of M. Find the eigenvalue that it corresponds to.
 
  • #3


If [itex]Mv= \lambda v[/itex], then [itex]M^2v= M(Mv)= M(\lambda v)= \lambda Mv= \lambda^2 v[/itex]. Get the point?
 
  • #4


Also, remember that M^5 is just M acting on v 5 consecutive times. Eigenvectors make this quite simple :)
 

1. What does "M^5v" mean in this context?

In this context, "M^5v" refers to the result of multiplying the matrix M by the vector v, with the exponent 5 indicating that the multiplication is performed 5 times.

2. What is the size of the matrix M?

The matrix M has a size of 3 rows and 3 columns, as indicated by the dimensions [3 3] in its description.

3. How do you calculate the value of "M^5v"?

To calculate the value of "M^5v", you would need to first multiply the matrix M by itself 5 times, and then multiply the resulting matrix by the vector v. This can be done using matrix multiplication rules.

4. What is the significance of the values in the matrix M?

The values in the matrix M represent the coefficients of a system of linear equations. They can be used to solve for the values of the variables in the equations.

5. Can the matrix M be multiplied by any vector?

Yes, the matrix M can be multiplied by any vector as long as the number of columns in M is equal to the number of rows in the vector. This ensures that the dimensions of the resulting matrix are compatible for multiplication.

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