How do you initialize an N*M matrix?
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Harry
il 26 Giu 2013
Risposto: HARSHAVARTHINI
il 26 Nov 2024 alle 6:21
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
il 26 Giu 2013
Modificato: MathWorks Support Team
il 27 Nov 2018
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”.
3 Commenti
Abhishek Inamdar
il 6 Lug 2021
Use "X = ones(n)" and add the values based on the row and column. Use for loop to work on value addition
israt fatema
il 25 Ago 2021
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
Più risposte (5)
Lokesh Ravindranathan
il 26 Giu 2013
Modificato: Lokesh Ravindranathan
il 26 Giu 2013
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.
2 Commenti
per isakson
il 26 Giu 2013
Modificato: per isakson
il 26 Giu 2013
matrix is a function in the symbolic toolbox.
Lokesh Ravindranathan
il 26 Giu 2013
Oh. Thanks Isakson. I will update my answer. My MATLAB did not have symbolic Math toolbox.
Pau
il 17 Ott 2018
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
il 26 Nov 2024 alle 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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