Linear Algebra Rank of a Matrix Problem

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SUMMARY

The discussion focuses on proving that the array a(k) = rank(A^(k + 1)) - rank(A^k) is monotonically increasing for an n x n matrix A with complex elements. The proof leverages the property that rank(AB) ≤ min(rank(A), rank(B)). The solution was ultimately derived using the Frobenius Inequality, confirming that the rank difference does not decrease as k increases.

PREREQUISITES
  • Understanding of matrix rank and properties of matrix multiplication
  • Familiarity with the Frobenius Inequality in linear algebra
  • Knowledge of complex matrices and their characteristics
  • Basic concepts of mathematical induction and sequences
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  • Study the properties of matrix rank in detail, focusing on rank inequalities
  • Explore the Frobenius Inequality and its applications in linear algebra
  • Learn about the implications of matrix rank in the context of linear transformations
  • Investigate the behavior of powers of matrices and their ranks
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Mathematicians, students of linear algebra, and researchers interested in matrix theory and its applications in complex systems.

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Let A be a n x n matrix with complex elements. Prove that the a(k) array, with k ∈ ℕ, where a(k) = rank(A^(k + 1)) - rank(A^k), is monotonically increasing.

Thank you! :)
 
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This follows from $\operatorname {rank} (AB)\leq \min(\operatorname {rank} (A),\operatorname {rank} (B))$, if by "increasing" you mean "not decreasing".
 
Finally solved it using the Frobenius Inequality for the rank of a matrix. Thank you anyway!
 

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