square matrix
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A square matrix is a matrix with the same number of rows and columns. It can be classified as singular or nonsingular. Special types of square matrices include symmetric matrices where the matrix is equal to its transpose and skew-symmetric matrices where the matrix is equal to the negative of its transpose. Any square matrix can be uniquely expressed as the sum of a symmetric matrix and a skew-symmetric matrix using the formula C = (1/2)(C + C^T) + (1/2)(C - C^T).
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Here are the key steps to find the eigenvalues of the given matrix:
1) Write the characteristic equation: det(A - λI) = 0
2) Expand the determinant: (1-λ)(-2-λ) - 4 = 0
3) Simplify and factor: λ(λ + 1)(λ + 2) = 0
4) Find the roots: λ1 = 0, λ2 = -1, λ3 = -2
Therefore, the eigenvalues of the given matrix are -1 and -2.
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Tools for system analysis
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Virtual Memory
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Network topologies
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Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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square matrix
- 2. HELLO! I am Sanjana Jahan 163-15-8443
- 3. WHAT IS SQUARE MATRIX?
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- 10. TRUE FACTS : M+ MT is symmetric matrix M-MT is skew-symmetric matrix. M CAN be uniquely expressed as the sum of a symmetric matrix and a skew-symmetric matrix.
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