Problem 28
Question
Find \(A B\), if possible. $$ A=\left[\begin{array}{rrr} 1 & 0 & 0 \\ 0 & 4 & 0 \\ 0 & 0 & -2 \end{array}\right], B=\left[\begin{array}{rrr} 3 & 0 & 0 \\ 0 & -1 & 0 \\ 0 & 0 & 5 \end{array}\right] $$
Step-by-Step Solution
Verified Answer
So, the result of the matrix multiplication AB is \( \left[\begin{array}{ccc} 3 & 0 & 0 \ 0 & -4 & 0 \ 0 & 0 & -10 \end{array}\right]\).
1Step 1: Define Matrices A and B
Let's define Matrix \(A\) and Matrix \(B\) as: \(A = \left[\begin{array}{ccc} 1 & 0 & 0 \ 0 & 4 & 0 \ 0 & 0 & -2 \end{array}\right]\) \(B = \left[\begin{array}{ccc} 3 & 0 & 0 \ 0 & -1 & 0 \ 0 & 0 & 5 \end{array}\right]\)
2Step 2: Perform Matrix Multiplication
Now, multiplying each element in the row of the first matrix with the corresponding element in the column of the second matrix, and summing them up to get the element at the respective position in the resultant matrix. \(AB = \left[\begin{array}{ccc} 1*3 & 0*(-1) & 0*5 \ 0*3 & 4*(-1) & 0*5 \ 0*3 & 0*(-1) & -2*5 \end{array}\right]\). Which results in: \(AB = \left[\begin{array}{ccc} 3 & 0 & 0 \ 0 & -4 & 0 \ 0 & 0 & -10 \end{array}\right]\).
Key Concepts
Diagonal MatrixMatrix OperationsMatrix Arithmetic
Diagonal Matrix
A diagonal matrix is a special type of square matrix. In a diagonal matrix, all entries outside the main diagonal are zero. The main diagonal runs from the top left to the bottom right corner.
This design simplifies many matrix operations, including multiplication.
Diagonal matrices are crucial in various mathematical areas. They make it easy to understand the properties of matrices.
For instance, eigenvalues of diagonal matrices are simply the diagonal elements themselves.
Their simplicity allows for straightforward computation in matrix arithmetic as well.
This design simplifies many matrix operations, including multiplication.
- Example: For a 3x3 diagonal matrix like \(A\), elements \( a_{12}, a_{13}, a_{21}, a_{23}, a_{31}, \) and \( a_{32} \) are all zero.
- Only \( a_{11}, a_{22}, \) and \( a_{33} \) (the diagonal elements) have non-zero values.
Diagonal matrices are crucial in various mathematical areas. They make it easy to understand the properties of matrices.
For instance, eigenvalues of diagonal matrices are simply the diagonal elements themselves.
Their simplicity allows for straightforward computation in matrix arithmetic as well.
Matrix Operations
Matrix operations involve addition, subtraction, and multiplication. Multiplying matrices is a bit more complex than the other operations.
When multiplying two matrices, you take the dot product of rows and columns.
This method ensures proper alignment and multiplication for each matrix element. With diagonal matrices like \(A\) and \(B\) from our exercise, matrix multiplication becomes easier since zeros keep computations minimal outside the main diagonal.
For instance, multiplying two diagonal matrices results in another diagonal matrix.
When multiplying two matrices, you take the dot product of rows and columns.
- The number of columns in the first matrix must equal the number of rows in the second.
- The element in the \(i^{th}\) row and \(j^{th}\) column of the resulting matrix is computed by multiplying corresponding elements from the row of the first matrix and column of the second matrix, then summing up these products.
This method ensures proper alignment and multiplication for each matrix element. With diagonal matrices like \(A\) and \(B\) from our exercise, matrix multiplication becomes easier since zeros keep computations minimal outside the main diagonal.
For instance, multiplying two diagonal matrices results in another diagonal matrix.
Matrix Arithmetic
Matrix arithmetic includes operations like addition, subtraction, and multiplication. While addition and subtraction are straightforward, following element-by-element operations, multiplication requires additional rules:
In our solved example, both matrices are 3x3, which makes them compatible for multiplication. With diagonal matrices like \(A\) and \(B\), computations are direct.
Non-diagonal elements multiply to zero, leaving only the diagonal elements to be multiplied directly.
This simplification is one of the key advantages of working with diagonal matrices in matrix arithmetic. It also speeds up computation significantly, which is beneficial for larger matrices.
- For two matrices to be multiplied, they must be compatible (i.e., the number of columns in the first matrix must equal the number of rows in the second).
- The resulting matrix's size is determined by the number of rows of the first and columns of the second matrix.
In our solved example, both matrices are 3x3, which makes them compatible for multiplication. With diagonal matrices like \(A\) and \(B\), computations are direct.
Non-diagonal elements multiply to zero, leaving only the diagonal elements to be multiplied directly.
This simplification is one of the key advantages of working with diagonal matrices in matrix arithmetic. It also speeds up computation significantly, which is beneficial for larger matrices.
Other exercises in this chapter
Problem 28
Find all (a) minors and (b) cofactors of the matrix. $$ \left[\begin{array}{rrr} -2 & 9 & 4 \\ 7 & -6 & 0 \\ 6 & 7 & -6 \end{array}\right] $$
View solution Problem 28
Find the inverse of the matrix (if it exists). $$ \left[\begin{array}{lll} 1 & 0 & 0 \\ 3 & 0 & 0 \\ 2 & 5 & 5 \end{array}\right] $$
View solution Problem 28
Write the matrix in row-echelon form. (Note: Row-echelon forms are not unique.) $$ \left[\begin{array}{rrrr} 1 & -3 & 0 & -7 \\ -3 & 10 & 1 & 23 \\ 1 & 0 & 1 &
View solution Problem 29
Use a determinant to find an equation of the line passing through the points. $$ (-1,2),(5,3) $$
View solution