Compact closed category

Related lectures (23)

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Covers the Gram-Schmidt algorithm for orthonormal bases in vector spaces.

Covers the concept of diagonalizability of matrices and explores eigenvalues and eigenvectors.

Explores normal equations, pseudo-solutions, unique solutions, and symmetric matrices in linear algebra.

Covers error correction in quantum computing using Hamming codes and syndrome decoding.

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

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

Explores properties of linear applications, including symmetric matrices and linearity in analysis.

Explores free generating families in linear algebra, discussing subspaces, stability, and linear dependency relations.

Explores the Rank Theorem in linear algebra, covering matrix properties and determinants.