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Posted (edited)

You can use for-loop to implement Matrix Multiplication in Java

import java.util.Scanner;
 
public class MatrixMultiplicationExample{  
  public static void main(String args[]){  
 
    int row1, col1, row2, col2;
    Scanner s = new Scanner(System.in);
    System.out.print("Enter number of rows in first matrix:");
    row1 = s.nextInt();
    System.out.print("Enter number of columns in first matrix:");
    col1 = s.nextInt();
    System.out.print("Enter number of rows in second matrix:");
    row2 = s.nextInt();
    System.out.print("Enter number of columns in second matrix:");
    col2 = s.nextInt();
 
    if (col1 != row2) {
        System.out.println("Matrix multiplication is not possible");
    }
    else {
        int a[][] = new int[row1][col1];
        int b[][] = new int[row2][col2];
        int c[][] = new int[row1][col2];
 
        System.out.println("Enter values for matrix A : \n");
        for (int i = 0; i < row1; i++) {
            for (int j = 0; j < col1; j++) 
                a[i][j] = s.nextInt();
        }
        System.out.println("Enter values for matrix B : \n");
        for (int i = 0; i < row2; i++) {
            for (int j = 0; j < col2; j++) 
                b[i][j] = s.nextInt();
        }
 
        System.out.println("Matrix multiplication is : \n");
        for(int i = 0; i < row1; i++) {    
            for(int j = 0; j < col2; j++){    
              c[i][j]=0;      
              for(int k = 0; k < col1; k++){      
                c[i][j] += a[i][k] * b[k][j];      
              }
              System.out.print(c[i][j] + " ");  
            }
            System.out.println();
        }    
    }
  }
}

To know more about the Matrix Multiplication read more on commercial url removed by moderator.

 

Edited by Phi for All
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  • 1 month later...
Posted
// *To perform matrix multiplication, the first matrix must have the same number of columns as the second matrix has rows. 

public class MatrixMultiplicationExample{  
public static void main(String args[]){  
  //matrix 1
int a[][]={{1,1,1},{2,2,2},{3,3,3}}; 
  //matrix 2
int b[][]={{1,1,1},{2,2,2},{3,3,3}};    
    
//creating another matrix to store the multiplication of two matrices    
int c[][]=new int[3][3];  //3 rows and 3 columns  
    
//multiplying and printing multiplication of 2 matrices    
for(int i=0;i<3;i++){    
for(int j=0;j<3;j++){    
c[i][j]=0;      
for(int k=0;k<3;k++)      
{      
c[i][j]+=a[i][k]*b[k][j];      
}//end of k loop  
System.out.print(c[i][j]+" ");  //printing matrix element  
}//end of j loop  
System.out.println();   
}    
}}  

// Hope it will help you

 

  • 7 months later...
Posted

Hello this is Gulshan Negi

Well, matrix multiplication is a mathematical operation used to combine two matrices to produce a third matrix. It involves multiplying the elements of one matrix by the elements of another matrix and adding up the results.

How matrix multiplication works:

Suppose we have two matrices, A and B. Matrix A has dimensions m x n (m rows and n columns), while matrix B has dimensions n x p (n rows and p columns). To multiply these matrices, we need to make sure that the number of columns in matrix A is equal to the number of rows in matrix B.

The resulting matrix, C, will have dimensions m x p (m rows and p columns). Each element of the resulting matrix is computed as the dot product of a row from matrix A and a column from matrix B. To find the element at the ith row and jth column of the resulting matrix, we would multiply the elements in the ith row of matrix A by the elements in the jth column of matrix B and add up the results.

This can be represented mathematically as:

C(i,j) = sum(A(i,k) * B(k,j)) for k=1 to n

Codebase-

def matrix_multiplication(A, B):
    m, n = A.shape
    n, p = B.shape
    C = np.zeros((m, p))
    for i in range(m):
        for j in range(p):
            for k in range(n):
                C[i,j] += A[i,k] * B[k,j]
    return C

where A and B are the input matrices, and np is the NumPy library used for matrix operations.

Hope it will help you.

Thanks

 

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