Step 1: Analyze the Given Information
We are given that \(AA^T = I\). Taking the determinant of both sides:
\(|AA^T| = |I|\)
\(|A| \cdot |A^T| = 1\)
Since \(|A^T| = |A|\), we have:
\(|A|^2 = 1\)
\(|A| = \pm 1\)
We are also given that \(|A| = 1\).
Step 2: Analyze B
To continue, we must know something that holds true for Matrix B. Let's add information into the equation such as |A|= 1 the |B|=-1 and say that Then the new equation of A+B=0
Step 3: Analyze A + B, if |A|= 1 the |B|=-1 and |A+B|=0
Add these equation together for the total value, then |A+B|=0 Then A+B is Singular, and can hold true
Conclusion:
Given |A|= 1 the |B|=-1 and |A+B|=0 : A+B is singular.
Step 1: Orthogonal Matrix Property
Since A and B are orthogonal matrices, we have:
\(AA^T = I\) and \(BB^T = I\)
Taking determinants, we get:
\(|AA^T| = |I| = 1\) and \(|BB^T| = |I| = 1\)
\(|A||A^T| = 1\) and \(|B||B^T| = 1\)
Since \(|A^T| = |A|\) and \(|B^T| = |B|\),
\(|A|^2 = 1\) and \(|B|^2 = 1\)
Thus, \(|A| = \pm 1\) and \(|B| = \pm 1\)
Step 2: Using the Given Condition |A| = -|B|
We are given that \(|A| = -|B|\). This means if \(|A| = 1\) then \(|B| = -1\) and if \(|A| = -1\) then \(|B| = 1\). In any case
\(|A||B| = -1\)
Step 3: Analyzing |A+B|
Consider \(|A + B|\). Multiply by the Identity Matrix in a clever way to insert the Orthogonal matrix properties.
\(|A + B| = |A \cdot I + B \cdot I| = |A BB^T + A^T A B|\)
\(=|ABB^T + A^TB||\)
Factoring gives:
\( |A + B| = |A (B^T + A^T)B|\)
Taking Determinants:
\(|A+B| = |A| |B^T+A^T | |B| =|A||B||B^T+A^T |\)
Rearranging and rewritting gives us:
\(=|A||B| (|(A+B)^T|) \)
Since \(|A||B|=-1\) So the solution is given as \(|A+B| = -|(A+B)^T|\) \(|A+B|=-|A+B|\) \(2|A+B|=0\) Then \(|A+B|=0\)
Step 4: Concluding Singularity
Since the determinant of \(A + B\) is 0, \(A + B\) is a singular matrix.
A, B, C, D are square matrices such that A + B is symmetric, A - B is skew-symmetric, and D is the transpose of C.
If
\[ A = \begin{bmatrix} -1 & 2 & 3 \\ 4 & 3 & -2 \\ 3 & -4 & 5 \end{bmatrix} \]
and
\[ C = \begin{bmatrix} 0 & 1 & -2 \\ 2 & -1 & 0 \\ 0 & 2 & 1 \end{bmatrix} \]
then the matrix \( B + D \) is:
Given matrices \( A \) and \( B \) where:
and the condition:
If matrix \( C \) is defined as:
then the trace of \( C \) is:
Matrix Inverse Sum Calculation
Given the matrix:
A = | 1 2 2 | | 3 2 3 | | 1 1 2 |
The inverse matrix is represented as:
A-1 = | a11 a12 a13 | | a21 a22 a23 | | a31 a32 a33 |
The sum of all elements in A-1 is:
The numbers or functions that are kept in a matrix are termed the elements or the entries of the matrix.
The matrix acquired by interchanging the rows and columns of the parent matrix is termed the Transpose matrix. The definition of a transpose matrix goes as follows - “A Matrix which is devised by turning all the rows of a given matrix into columns and vice-versa.”