MATLAB: Models based on singular value decomposion

MATLABsingular value decompositionssvd

Im new in matlab and im trying to write a code that can creat models based on svd with 100 * 10 matrix of dataset to estimate values that user wants.

So is it possible in matlab and how should i start?

Dataset is in excel file, how can i use that data in matlab?

thanks

Best Answer

load your dataset from your excel file using this command: "A = csvread(filename)".

then you can do anything and ofcourse matlab has a svd function. "[U,S,V] = svd(A)".

matlab is a powerful tool of matrix and array manipulation, data optimization, and equation solvers.

if you are a beginner in matlab programming, start by matrix and array indexing and manipulating, "if statements", "for and while loops". the rest you get used to it.

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MATLAB: Singular matrix and MATLAB inversion

DON'T use det to determine if a matrix is singular!

A non-zero multiple of the identity matrix isn't singular, right?

A = 0.1*eye(400);
det(A)

The determinant of A underflowed to 0.

Can multiplying a singular (or nearly singular) matrix by a non-zero scalar make it no longer singular?

B = [1 1; 1 1+eps];
C = 1e8*B;
det(B)
det(C)

A number with a determinant on the order of 1 can't be singular, can it?

Use the cond or rcond functions instead. Matrices with condition numbers closer to 1 are better behaved.

cond(A)
cond(B)
cond(C)

If you're calling inv to try to solve a system of linear equations, DON'T. Use the backslash operator (\) instead. Even if your textbook told you to multiply by the inverse matrix, well, in theory there is no difference between theory and practice ...

MATLAB: Is pca() faster than svd()

Read the help for SVD, particularly the economy SVD.

Best Answer

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MATLAB: Singular matrix and MATLAB inversion

MATLAB: Is pca() faster than svd()

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