Circulant linear systems and the Discrete Fourier Transform

In summary, the conversation discusses finding a solution for a circulant n x n matrix C multiplied by a vector x equal to another vector b. One approach is to use the DFT, where the Circular Convolution Theorem states that F_k(c) F_k(x) = F_k(b) if c is the first column of C. However, if F_k(c) = 0 for some k, it is unclear what value to choose for F_k(x). The conversation also mentions the definitions of circulant matrix and DFT for reference.
  • #1
burritoloco
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Homework Statement


Hi, this is not a homework question per se, but something I'm wondering. Let C be a circulant n x n matrix, let x, b, be vectors such that

C x = b.

We would like to find a solution x. One way is to use the DFT: According to section 5, In Linear Equations, in the wikipedia article available at

http://en.wikipedia.org/wiki/Circulant_matrix#In_linear_equations

if we let c be the 1st column of C, we have a convolution c * x = b from which the Circular Convolution Theorem gives

F_k(c) F_k(x) = F_k(b),

where F_k(x) denotes the k-th component of the Fourier transformation of the vector x. My question is, as I'm fairly new to all this, what is F_k(x) if F_k(c) = 0 for some k? Do we choose F_k(x) arbitrarily in this case? Thank you.
 
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  • #3
It's probably a yes I'm thinking implying more than one solution for x.
 

What is a circulant linear system?

A circulant linear system is a type of linear system where the matrix representing the system is a circulant matrix. This means that the matrix is symmetric and each row is a cyclic permutation of the row above it. Circulant linear systems are commonly used in signal processing and image processing applications.

What is the Discrete Fourier Transform (DFT)?

The Discrete Fourier Transform is a mathematical operation that converts a discrete sequence of numbers, such as a signal or image, into its frequency components. It is used to analyze and manipulate signals in various applications, such as audio processing and data compression.

How are circulant linear systems and the DFT related?

Circulant linear systems and the DFT are closely related because the matrix representation of the DFT is a circulant matrix. This means that the DFT can be thought of as a special case of a circulant linear system, and many of the properties and algorithms for circulant linear systems can be applied to the DFT.

What are some applications of circulant linear systems and the DFT?

Some common applications of circulant linear systems and the DFT include signal and image processing, audio and video compression, and solving differential equations. They are also used in fields such as cryptography, data analysis, and communication systems.

What are some efficient methods for computing the DFT of a circulant linear system?

There are several efficient algorithms for computing the DFT of a circulant linear system, such as the Fast Fourier Transform (FFT) and the Butterfly Algorithm. These algorithms take advantage of the symmetry and structure of circulant matrices to reduce the computational complexity of the DFT from O(n^2) to O(nlogn), making it more efficient for large data sets.

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