You can observe that bsxfun is slightly faster. Solution using bsxfun provided by : 0.683331 seconds.Matrix indexing can achieve the same behavior as repmat and be faster. There is an alternative to repmat that I would like you to know. Edit: Just to add to the computational aspect. ![]() Solution using indexing technique explained above : 0.734435 seconds Then we can do element-wise multiplication (.) to 'multiply every column of a M × N matrix by corresponding element of a vector of size N'.So, if A is an m × n matrix, then the product A x is. Let us define the multiplication between a matrix A and a vector x in which the number of columns in A equals the number of rows in x. Solution using repmat : 0.824518 seconds To multiply a row vector by a column vector, the row vector must have as many columns as the column vector has rows. ![]() I ran three solutions 100000 times, namely, The output is a K1 x K2 size matrix while the ck vector is a K2 x 1 matrix. The idea is that a vector c, matches with each column B - t and we want to multiply each column of B - t by the entries in the vector x. If at least one input is scalar, then AB is. That is, AB is typically not equal to BA. Matrix multiplication is not universally commutative for nonscalar inputs. C (i,j) A (i,:)B (:,j) For nonscalar A and B, the number of columns of A must equal the number of rows of B. Thereby achieving the same behavior as repmat and be faster. no its not, because its not element-wise multiplication. You can write this definition using the MATLAB ® colon operator as. If you see closely, the expression boils down to vec1('*),:) which is again: vec1(),:) Observe that you can write the following statement repmat(vec1,) Īs vec1('*ones(1,size(mat1,1)),:) ![]() v By this way, this is very basic MATLAB syntax. As such, you can simply take your vector (let's call it v, where v 1 2 3 ) and multiply this with the third column of your matrix (let's call the matrix A) by: out A (:,3). There is an alternative to repmat that I would like you to know. I'm assuming you want to do point-by-point multiplication. The result is a 4-by-4 matrix, also called the outer product of the vectors. Alternatively, you can calculate the dot product A B with the syntax dot (A,B). Now I want to do a vector multiplication with a column vector v over one of the dimensions (as I would do in 2 dimensions, where I get a vector returned - for instance for d1 2, d3 4 and size(v) d2), so that (Ad)i sum(aijvj). Then we can do element-wise multiplication (.*) to "multiply every column of a M × N matrix by corresponding element of a vector of size N".Įdit: Just to add to the computational aspect. The result is a 1-by-1 scalar, also called the dot product or inner product of the vectors A and B. I have a 3d (or in general n-dimensional) matrix A with dimensions. Rempat will replicate vec1 along the rows of mat1. I think this is what you want: mat1=randi(10,)
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |