The following function gives the compressed representation of an image and reconstructs it approximately by multiplying out
Function:
I have attached an image with the code
What is an SVD?
A matrix's Singular Value Decomposition (SVD) is a factorization of the matrix into three matrices. It possesses some intriguing algebraic properties and provides important geometrical and theoretical insights into linear transformations. It has some important applications in data science as well. So the SVD function will help in reconstructing and multiplying out the image, it also helps in factorizing the matrix so what it does is it compresses the matrix into three matix
Hence to conclude the above program gives the singular value decomposition by multiplying out the truncated svd
To know more on svd follow this link:
https://brainly.com/question/27854252
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