MIMO Detection

Related lectures (30)

Page 3 of 3

Explores LU decomposition for solving linear systems and the associativity of operations.

Covers the LU decomposition method applied to linear systems, presenting the system in two steps.

Explores spectral and singular value decompositions of matrices.

Explains the QR factorization theorem and demonstrates the Gram-Schmidt procedure with an example.

Explains the method of least squares in linear regression to find the best-fitting line to a set of data points.

Covers the decomposition of matrices into triangular blocks and spectral decomposition.

Explores LU decomposition of a matrix into lower and upper triangular matrices.

Covers the decomposition of a matrix into Jordan blocks and the process of finding the Jordan form.

Explores Gram-Schmidt process, orthogonal projection, QR factorization, and least squares solutions for linear systems.

Explores matrix decompositions for solving linear systems and simulating dynamics.