![]() The matrix analysis functions det, rcond, hess, and expm also show significant increase in speed on large double-precision arrays. ![]() The matrix multiply (X*Y) and matrix power (X^p) operators show significant increase in speed on large double-precision arrays (on order of 10,000 elements). i find (A x y) Any idea Azzi Abdelmalek on Kris zenitis commented Sign in to comment. I ve tried this but find can search only single values. I want to find how many times a specific x y exists in this matrix A. Learn more about find Learn more about find Hi all, Assume a vector: v 1:3:1000 How can I find the number of columns of each value in the vector: x 100, 280, 781, 925, 997 in the bigger vector, v. If X is a multidimensional array, then find returns a column vector of the linear indices of the result. Accepted Answer: Jan Lets assume that I have a matrix A 300x2 with x y coordinates. If X is a vector, then find returns a vector with the same orientation as X. As a general rule, complicated functions speed up more than simple functions. k find (X) returns a vector containing the linear indices of each nonzero element in array X. The operation is not memory-bound processing time is not dominated by memory access time. For example, most functions speed up only when the array contains several thousand elements or more. The data size is large enough so that any advantages of concurrent execution outweigh the time required to partition the data and manage separate execution threads. They should require few sequential operations. These sections must be able to execute with little communication between processes. Use vecnorm to treat a matrix or array as a collection of vectors and calculate the norm along a specified dimension. M mean ( ,outtype) returns the mean with a specified. ![]() The complexity is O(n + k.log(k)), where n is the size of the array, and k is the number of elements to be. It is done by Bruno Luong using a partial quick-sort algorithm implemented with C-MEX. The span of A will be the span of those vectors. I found a good mex implementation there while searching for the same thing. 1 RREF will show you which vectors are linearly independent. For example, if A is a matrix, then mean (A, 1 2) returns the mean of all elements in A because every element of a matrix is contained in the array slice defined by dimensions 1 and 2. You can find good answers to matlab questions also on matlabcentral. The function performs operations that easily partition into sections that execute concurrently. M mean (A,vecdim) returns the mean based on the dimensions specified in the vector vecdim. ![]()
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