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C Examples on Matrix OperationsA matrix is a rectangular array of numbers or symbols arranged in rows and columns. The following section contains a list of C programs which perform the operations of Addition, Subtraction and Multiplication on the 2 matrices. The section also deals with evaluating the transpose of a given matrix. The transpose of a matrix is the interchange of rows and columns.The section also has programs on finding the trace of 2 matrices, calculating the sum and difference of two matrices. It also has a C program which is used to perform multiplication of a matrix using recursion.C Program to Calculate the Addition or Subtraction & Trace of 2 MatricesC Program to Find the Transpose of a given MatrixC Program to Compute the Product of Two MatricesC Program to Calculate the Sum & Difference of the MatricesC Program to Perform Matrix Multiplication using Recursion
The check sum8 of hex string 0221323DA3B4 is E9.
Here is the C program to check whether the inputted matrix is scalar matrix or not. ( its not my creation, its get from other website,am not check) #include<stdio.h> #include<conio.h> int main() { int a[10][10],i,j,m,n,f=0; printf("Enter the order of the matrix\n"); scanf("%d%d",&m,&n); printf("Enter the matrix\n"); for(i=0;i<m;i++) { for(j=0;j<n;j++) { scanf("%d",&a[i][j]); } } if(m!=n) { printf("The matrix is not identity"); } else { for(i=0;i<m;i++) { for(j=0;j<n;j++) { if((i==j&&a[i][j]!=a[0][0])(i!=j&&a[i][j]!=0)) { printf("The matrix is not scalar\n"); f=1; break; } } if(f==1) { break; } } if(f==0) { printf("The matrix is scalar\n"); } } getch(); return 0; }
To determine if an array is symmetric, the array must be square. If so, check each element against its transpose. If all elements are equal, the array is symmetric.For a two-dimensional array (a matrix) of order n, the following code will determine if it is symmetric or not:templatebool symmetric(const std::array& matrix){for (size_t r=0 ; r
variance - covariance - how to calculate and its uses
write a programe to build a sparse matrix as an array. write function to check if the sparse matrix is a square, diagonal,lower triangular, upper triangular or tridiagonal matrix
look in a maths dictionary
In our simulations, we use this (in Matlab/Octave): function l=linearityindex(matrix) m=(matrix>matrix')+.5*(matrix==matrix'); rowsums=sum(m,2)-.5; n=length(rowsums); l=12/(n^3-n)*sum((rowsums-(n-1)/2).^2); You may want to check out Landau's 1951 paper, "On dominance relations and the structure of animal societies: I. Effect of inherent characteristics". From http://www.springerlink.com/content/366920782vwr0648/
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actually MATRICES is the plural of matrix which means the array of numbers in groups and columns in a rectangular table... and determinant is used to calculate the magnitude of a matrix....
check the manual.
This is the matrix im talking about [A B][C D]For a 2x2 matrix if the f***ing AD-BC does not = 0 thennnn theres an inverse!!!!Sooo........Use this equation!!!1/(AD-BC) multiplied by the matrix [D -B]
The Cayley-Hamilton (not Caley hamilton) theorem allows powers of the matrix to be calculated more simply by using the characteristic function of the matrix. It can also provide a simple way to calculate the inverse matrix.
to check a matrix as transitive multiplay matrix with its self and take the row from m1 multiplay it with col from m2 if result equel one or more than one then matrix is transitive else not transitivesee this matrixm1[1010;0101;0101]m2[1010;0101;0101]result m1*m2=[2020;0202;2020;0202]if a(i,j)>2thena(i,j)=1endbest regardss13eed@yahoo.com
There are two main methods: both depend on a reasonable understanding of matrices and determinants.One way is to append an identity matrix to the right of the original matrix. So, given an n x n matrix A, create an n x 2n matrix A|I.Using only row operations, convert A into an identity matrix. Then the right hand side of A|I will be A-1Alternatively, calculate the determinant |A|Also calculate the determinants of all n-1 x n-1 sub-matrices where sijdenotes the determinant of the submatrix created when row i and column j are deleted.Let bij= sij*(-1)i+j/|A|.Then the matrix B = {bij} = A-1.
To efficiently calculate and visualize the plot covariance matrix in Python, you can use the NumPy library to calculate the covariance matrix and the Seaborn library to visualize it. First, import the necessary libraries: import numpy as np import seaborn as sns Next, calculate the covariance matrix using NumPy: data = np.random.rand(10, 2) # Example data cov_matrix = np.cov(data.T) Finally, visualize the covariance matrix using Seaborn: sns.heatmap(cov_matrix, annot=True, cmap='coolwarm', xticklabels=['Feature 1', 'Feature 2'], yticklabels=['Feature 1', 'Feature 2']) This will create a heatmap visualization of the covariance matrix with annotations showing the values.