Intro to Scientific Computing
The QR Algorithm is a numerical method used for computing the eigenvalues and eigenvectors of a matrix. It works by decomposing a matrix into a product of an orthogonal matrix (Q) and an upper triangular matrix (R), facilitating iterative approximations that converge to the eigenvalues. This technique is particularly useful in solving eigenvalue problems and is closely linked to the singular value decomposition, allowing for efficient calculations in various applications, including linear algebra and statistics.
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