QR分解-householder reflection

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QR分解-householder reflection

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QR decomposition is a fundamental method in linear algebra, which can be computed using Householder reflections. This method is used to decompose a matrix into a product of an orthogonal matrix Q and an upper triangular matrix R. QR decomposition can be used in numerical algorithms, such as least squares and eigenvalue computation. Householder reflections is a technique used to transform a vector into a multiple of a coordinate axis, which can be used in various applications such as image processing and data compression. By combining QR decomposition and Householder reflections, we can solve complex mathematical problems and better understand the underlying structure of a matrix.