Let $A=\begin{pmatrix}1 & 0 & 0 \\ 0 & 4 & -1 \\ 0 & 12 & -3\end{pmatrix}$ Then the sum of the diagonal elements of the matrix $(A+I)^{11}$ is equal to :
Step 1: First, calculate \( A^2 \): \[ A^2 = \begin{pmatrix} 1 & 0 & 0 \\ 0 & 4 & -1 \\ 0 & 12 & -3 \end{pmatrix} \begin{pmatrix} 1 & 0 & 0 \\ 0 & 4 & -1 \\ 0 & 12 & -3 \end{pmatrix} = \begin{pmatrix} 1 & 0 & 0 \\ 0 & 4 & -1 \\ 0 & 12 & -3 \end{pmatrix} \] This matrix multiplication yields the same matrix \( A \), meaning that \( A^2 = A \).
Step 2: From this, we have: \[ A^3 = A^4 = \cdots = A \] Since \( A^2 = A \), any higher powers of \( A \) will also be equal to \( A \).
Step 3: Now, calculate \( (A + I)^{11} \): \[ (A + I)^{11} = \sum_{k=0}^{11} \binom{11}{k} A^k I^{11-k} = \left( (2^{11} - 1)A + I \right) \] Here, we used the binomial expansion of \( (A + I)^{11} \), and since \( A^k = A \) for all \( k \geq 1 \), the expression simplifies as shown.
Step 4: The sum of the diagonal elements is then: \[ \text{Sum of diagonal elements} = 2047 \times (1 + 4 - 3) + 3 = 4094 + 3 = 4097 \] This gives the final result for the sum of the diagonal elements of \( (A + I)^{11} \).
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.”