## Abstract In this paper, two new matrixβform iterative methods are presented to solve the leastβsquares problem: and matrix nearness problem: where matrices $A\in R^{p\times n\_1},B\in R^{n\_2\times q},C\in R^{p\times m\_1},D\in R^{m\_2\times q},E\in R^{p\times q},\widetilde{X}\in R^{n\_1\time
Solution of a complex least squares problem with constrained phase
β Scribed by Mark Bydder
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 105 KB
- Volume
- 433
- Category
- Article
- ISSN
- 0024-3795
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β¦ Synopsis
The least squares solution of a complex linear equation is in general a complex vector with independent real and imaginary parts. In certain applications in magnetic resonance imaging, a solution is desired such that each element has the same phase. A direct method for obtaining the least squares solution to the phase constrained problem is described.
π SIMILAR VOLUMES
By means of complex representation of a quaternion matrix, we study the relationship between the solutions of the quaternion equality constrained least squares problem and that of complex equality constrained least squares problem, and obtain a new technique of finding a solution of the quaternion e
The linear least squares problem, min x Ax-b 2 , is solved by applying a multisplitting(MS) strategy in which the system matrix is decomposed by columns into p blocks. The b and x vectors are partitioned consistently with the matrix decomposition. The global least squares problem is then replaced by