Making approximate 2D Continuous Fourier Transform (CFT) efficient
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Hi there!
I have a matrix that represents a certain 2D function in a frequency domain
calculated on a regular grid, and I want to find it on a certain pre-defined 2D grid in time domain, that is to find the values of
.
calculated on a regular grid, and I want to find it on a certain pre-defined 2D grid in time domain, that is to find the values of Right now I do it using the "trapz()" function to approximate the continuous integral, and it works. However, if the input matrix size (
) is large or the mesh in time is too fine, it takes a very long time to find it. For example, for input in frequency domain of size [500x100] and time domain grid of size [300x300] it takes something on the order of tens of minutes!
) is large or the mesh in time is too fine, it takes a very long time to find it. For example, for input in frequency domain of size [500x100] and time domain grid of size [300x300] it takes something on the order of tens of minutes! Is there any other way to do it efficiently?
1 Kommentar
Paul
am 14 Mär. 2023
Hi Stranger,
You might get more traction if you post code with some example data for F_w and the area of integration for the doulbe integral.
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