How do you initialize an N*M matrix?
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Harry
el 26 de Jun. de 2013
Respondida: HARSHAVARTHINI
el 26 de Nov. de 2024 a las 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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Respuesta aceptada
Leah
el 26 de Jun. de 2013
Editada: MathWorks Support Team
el 27 de Nov. de 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 comentarios
Abhishek Inamdar
el 6 de Jul. de 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
el 25 de Ag. de 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
Más respuestas (5)
Lokesh Ravindranathan
el 26 de Jun. de 2013
Editada: Lokesh Ravindranathan
el 26 de Jun. de 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 comentarios
per isakson
el 26 de Jun. de 2013
Editada: per isakson
el 26 de Jun. de 2013
matrix is a function in the symbolic toolbox.
Lokesh Ravindranathan
el 26 de Jun. de 2013
Oh. Thanks Isakson. I will update my answer. My MATLAB did not have symbolic Math toolbox.
Pau
el 17 de Oct. de 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
el 26 de Nov. de 2024 a las 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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