Lecture
QR Factorization
Description
This lecture covers the QR factorization theorem, stating that for a matrix A with linearly independent columns, there exists a factorization A = QR where Q has orthonormal columns forming a basis of the column space of A and R is an upper triangular matrix with strictly positive diagonal coefficients. The Gram-Schmidt procedure is used to transform the columns of A into an orthonormal basis. The lecture demonstrates the algorithm with an example, finding the QR factorization of a given matrix.
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