[A] is a square matrix which is neither symmetric nor skew-symmetric a...
[A] is a square matrix which is neither symmetric nor skew-symmetric a...
Differences between [A] and [A]T
- [A] is the given square matrix which is neither symmetric nor skew-symmetric.
- [A]T is the transpose of [A], which means the rows of [A] become the columns of [A]T and vice versa.
Sum and Difference of Matrices
- [S] is defined as the product of [A] and [A]T, meaning each element of [S] is the dot product of the corresponding row of [A] and column of [A]T.
- [D] is defined as the difference between [A] and [A]T, meaning each element of [D] is the difference between the corresponding elements of [A] and [A]T.
Properties of [S] and [D]
- To determine the properties of [S] and [D], we need to analyze their symmetry.
- A square matrix is symmetric if it is equal to its transpose, i.e., [M] = [M]T.
- A square matrix is skew-symmetric if the transpose of the matrix is equal to the negation of the original matrix, i.e., [M] = -[M]T.
Analysis of [S]
- [S] = [A] [A]T, which means [S] is the product of [A] and its transpose.
- Since [A] is neither symmetric nor skew-symmetric, it cannot be equal to its transpose, which means [S] is not equal to [S]T.
- Therefore, [S] is not symmetric.
Analysis of [D]
- [D] = [A] - [A]T, which means [D] is the difference between [A] and its transpose.
- Since [A] is neither symmetric nor skew-symmetric, it cannot be equal to its transpose, which means [D] is not equal to -[D]T.
- Therefore, [D] is not skew-symmetric.
Conclusion
- Based on the analysis, both [S] and [D] do not possess the properties of symmetry or skew-symmetry.
- The correct answer is option D: [S] is symmetric and [D] is skew-symmetric.