Apr 4, 2013 · * is matrix multiplication while .* is elementwise multiplication. In order to use the first operator, the operands should obey matrix multiplication rules in terms of size.

May 19, 2011 · Matrix multiplication (together with Matrix-vector, vector-vector multiplication and many of the matrix decompositions) is (are) the most important problems in linear algebra.

Sep 9, 2015 · I have two 3-dimensional arrays, the first two dimensions of which represent matrices and the last one counts through a parameterspace, as a simple example take A = …

Nov 16, 2009 · Suppose I have an AxBxC matrix X and a BxD matrix Y. Is there a non-loop method by which I can multiply each of the C AxB matrices with Y?

Feb 19, 2024 · Given a matrix A, I need to multiply with another constant vector B, N times (N > 1 million). The size of A is 9000x1 and B is 9000x1000. The code is currently evaluated in the …

Nov 12, 2014 · After this, you can do element-by-element multiplication. You can do this stacking by using repmat which repeats a vector or matrices a given number of times in any dimension …

Apr 20, 2013 · In MATLAB you obviously do not need programming explicit loops in most cases because you can use operator *. There exists a technique how to speed up matrix …

Jul 22, 2015 · I am translating some MATLAB code and am having some problems understanding the syntaxical difference between MATLAB and numpy for Python. In MATLAB I have a 6 by 6 …

Jan 6, 2013 · A(isnan(A)) = 0; before running the multiplication. I would advise against re-writing matrix multiplication, since you won't get similar performance to built-in matrix algebra out of …

Nov 16, 2013 · Matrix multiplication is a series of multiply-and-add operations. If the inputs are all ones and zeros, the result of such an operation will be "zero or greater than zero".