Reducing an Application

Related lectures (26)

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Covers the reduction of a linear transformation in a 2-dimensional space to find a simpler matrix representation.

Covers the diagonalization of linear transformations in R^3, exploring properties and examples.

Covers the reduction of a linear application and finding corresponding reduced forms and bases.

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

Explores canonical basis, linear mapping, and eigenvalues in linear algebra.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Explores the properties of invertible matrices, including unique solutions and linear independence.

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

Explores properties of 3x3 matrices with real coefficients and determinant calculation methods.