Eigenvalues and Eigenvectors: Polynomials and Matrices

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Covers eigenvalues, eigenvectors, and the Fibonacci sequence, exploring their mathematical properties and practical applications.

Eigenvalues and Diagonalization

Explores eigenvalues, eigenvectors, and matrix diagonalization with examples and proofs.

Eigenvalues and Eigenvectors in 3D

Explores eigenvalues and eigenvectors in 3D linear algebra, covering characteristic polynomials, stability under transformations, and real roots.

Eigenvalues and Eigenvectors: Understanding Matrix Transformations

Explores eigenvalues and eigenvectors in matrix transformations, essential for understanding mathematical and real-world systems.

Diagonalization of Matrices: Eigenvectors and Eigenvalues

Covers the concept of diagonalization of matrices through the study of eigenvectors and eigenvalues.

Eigenvalues and Minimal Polynomial

Explores eigenvalues and minimal polynomial, emphasizing their importance in linear algebra.

Matrix Similarity and Diagonalization

Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.

Diagonalizability Criterion

Covers the criterion for diagonalizability of matrices, focusing on comparing examples and understanding the relationship between algebraic and geometric multiplicities of eigenvalues.

Non-Diagonalizable Case: Two Eigenvalues (Example)

Showcases a non-diagonalizable matrix example and explores eigenvalues and eigenvectors.