MIMO Receivers

Related lectures (29)

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Covers the Jacobi method, Givens rotation, QR decomposition, and diagonalization techniques in computational physics.

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

Explores the Jacobi method and diagonalization techniques, including similarity transformation, power methods, and QR decomposition.

Covers the QR factorization of a matrix A into Q and R.

Covers the LU decomposition algorithm, transforming a matrix into L and U.

Covers the fundamentals of Singular Value Decomposition, including properties, applications, and error measurement.

Introduces QR factorization for matrix decomposition, emphasizing its importance in various applications and the implications of a well-chosen model.

Explains Singular Value Decomposition, focusing on orthogonal vectors and matrix decomposition.

Explains the step-by-step process of finding the singular value decomposition of a matrix.

Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.