How do you initialize an N*M matrix?
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From the MATLAB help, it says to use:
M = matrix(N, M)
but when I apply this it says that the function 'matrix' is not recognized.
Undefined function 'matrix' for input arguments of type 'double'.
Error in experimental (line 1)
M = matrix(3,3)
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Leah
2013년 6월 26일
편집: MathWorks Support Team
2018년 11월 27일
To initialize an N-by-M matrix, use the “zeros” function. For example, create a 3-by-5 matrix of zeros:
A = zeros(3,5);
You can then later assign specific values to the elements of “A”.
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Abhishek Inamdar
2021년 7월 6일
Use "X = ones(n)" and add the values based on the row and column. Use for loop to work on value addition
israt fatema
2021년 8월 25일
Can you please show me how to assign value to A after initialize the N x M matrix? For example i need to create a vector 5 x 5 and with values x = 20 35 49 64 23
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Lokesh Ravindranathan
2013년 6월 26일
편집: Lokesh Ravindranathan
2013년 6월 26일
I am assuming you are trying to create an empty matrix of zeros of dimensions N*M. You can try the following instead
M = zeros(3,3)
This creates a matrix of zeros of size 3*3.
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Lokesh Ravindranathan
2013년 6월 26일
Oh. Thanks Isakson. I will update my answer. My MATLAB did not have symbolic Math toolbox.
Pau
2018년 10월 17일
This should make the trick
M = double.empty(N,M,0);
https://uk.mathworks.com/help/matlab/ref/empty.html
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HARSHAVARTHINI
2024년 11월 26일 6:21
% Define the matrix A = [4 1 9; 0 1 3; 0 1 2];
% Initialize parameters n = size(A, 1); % Size of the matrix x = rand(n, 1); % Initial guess for the eigenvector tolerance = 1e-6; % Convergence criteria max_iter = 1000; % Maximum number of iterations lambda_old = 0; % Initial eigenvalue
for k = 1:max_iter % Multiply matrix A with vector x y = A * x;
% Normalize the vector x = y / norm(y);
% Compute the Rayleigh quotient (dominant eigenvalue) lambda = x' * A * x;
% Check for convergence if abs(lambda - lambda_old) < tolerance fprintf('Converged in %d iterations.\n', k); break; end
% Update old eigenvalue lambda_old = lambda; end
% Display results fprintf('Dominant Eigenvalue: %.6f\n', lambda); disp('Corresponding Eigenvector:'); disp(x);
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