Optimizing Halley's Iteration for Computing the Matrix Polar Decomposition
نویسندگان
چکیده
We introduce a dynamically weighted Halley (DWH) iteration for computing the polar decomposition of a matrix, and prove that the new method is globally and asymptotically cubically convergent. For matrices with condition number no greater than 1016, the DWH method needs at most 6 iterations for convergence with the tolerance 10−16. The Halley iteration can be implemented via QR decompositions without explicit matrix inversions. Therefore, it is an inverse free communication friendly algorithm for the emerging multicore and hybrid high performance computing systems.
منابع مشابه
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ورودعنوان ژورنال:
- SIAM J. Matrix Analysis Applications
دوره 31 شماره
صفحات -
تاریخ انتشار 2010