matrix = arrayfun(@(k) [C{p(k,:)}], 1:size(p,1), 'un', 0) % concatenate the permutations % matrix{k} now holds the k-th permutation of the three arrays (a, b, and s) 댓글 수: 1 Melike Öztürk 2017년 12월 13일 Thank you Jos. I didn't realize it woul...
how to generate a random matrix (X) which Where every numbers in matrix A and B must be at least zero between its numbers of one likethe solution X = [ 0 1 1 1 0 1 1 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 1 1 0 ] ...
In this case, R is generated by random plane rotations applied to a diagonal matrix with the given singular values. It has a great deal of topological and algebraic structure. Data Types: double Limitations sprand is designed to produce large matrices with small density and will generate ...
1) %取到行数，1指代上面返回值的第一个，即行数 cols = size(A, 2) %取到列数，2指代上...
Generate one random number from the normal distribution with the meanμequal to 1 and the standard deviationσequal to 5. Specify the distribution name'Normal'and the distribution parameters. rng('default')% For reproducibilitymu = 1; sigma = 5; r = random('Normal',mu,sigma) ...
function [ Phi ] =ToeplitzMtx( M,N )%ToeplitzMtx Summary ofthisfunction goes here%Generate Toeplitz matrix% M --RowNumber% N --ColumnNumber% Phi --The Toeplitz matrix%%Generate a random vector% %(1)Gauss% u = randn(1,2*N-1);%(2)Bernoulli ...
Create a random matrix?Thanks for everyone's help. After creating the matrix HM, now I want to create 1 vector whose elements are randomly selected from the HM with probability P, this vector satisfies the above constraints. Thank you!編集済み:Roger Stafford For...
RANDN Normally distributed random numbers. RANDOM Generate random arrays from a specified distribution. R = RANDOM(NAME,A) returns an array of random numbers chosen from the one-parameter probability distribution specified by NAME with parameter ...
MATLAB 是“matrix laboratory”的缩写形式。MATLAB® 主要用于处理整个的矩阵和数组,而其他编程语言大多逐个处理数值。矩阵是指通常用来进行线性代数运算的二维数组。 MATLAB 是美国MathWorks公司出品的商业数学软件,用于算法开发、数据可视化、数据分析以及数值计算的高级技术计算语言和交互式环境,主要包括MATLAB和Simulink两...
% parameters for Random Matrix alpha = 50; tau = 10; T = 10; const_z = 1/4; hat_x_RMM = hat_r0; hat_X_RMM = get_random_matrix_state(hat_p0); Cx_RMM = C_r0; for t = 1:time_steps N = poissrnd(possion_lambda);