GIVENS正交三角化的列超前并行消去算法

在分析已有的Ｇｉｖｅｎｓ正交三角化并行算法的基础上，进一步分析了在ＭＩＭＤ并行系统上行反射交替存储的逐次Ｇｉｖｅｎｓ正交三角化并行过程，提出了列超前并行消去算法，还介绍了这个算法在ＭＩＭＤ并行系统上实现的主要技巧，证明了列超前并行消去算法的并行加速倍数Ｓｐ与处理机台数Ｐ十分接近．     

求解场问题的一种新算法

基于文（１）（２），本文给出了一种计算场问题的新算法－拓扑有限元Ｇｉｖｅｎｓ算法，该方法利用了拓扑有限元的特性及快速Ｇｉｖｅｎｓ变换。算例结果与实验吻合很好。     

A Class of Incomplete Orthogonal Factorization Methods. II: Implementation and Results

We present, implement and test several incomplete QR factorization methods based on Givens rotations for sparse square and rectangular matrices. For square systems, the approximate QR factors are used as right-preconditioners for GMRES, and their performance is compared to standard ILU techniques. For rectangular matrices corresponding to linear least-squares problems, the approximate R factor is used as a right-preconditioner for CGLS. A comprehensive discussion is given about the uses, advantages and shortcomings of the preconditioners. AMS subject classification (2000) 65F10, 65F25, 65F50.Received May 2002. Revised October 2004. Communicated by Åke Björck.     

一种基于矩阵三对角化分解的DOA估计算法

针对DOA（Direction of Arrival）估计在低信噪比的情况下估计性能下降的问题, 根据阵列协方差矩阵共轭对称的特点,采用基于Givens变换的三对角化分解方法对协方 差矩阵进行三对角化,同时利用盖氏(Gerschgorin)圆递推方法准确估计信号子空间的秩, 然后再对三对角 矩阵进行对角化,估计出噪声子空间,利用噪声子空间与导向矢量正交实现波达方向估计, 改善了低信噪比背景下估计的误差性能和稳健性。计算机仿真证明了算法的有效性 。     

Two efficient and stable MMSE detection algorithms for the V‐BLAST system

For practical consideration, efficient and stable implementation of the promising vertical Bell Labs Layered Space–Time system is highly desirable. The original square‐root algorithm (SRA), proposed by Hassibi, for the minimum mean square error detection, is composed of three stages, that is, initialization, ordering, and nulling. Unlike the original SRA whose initialization stage is not completely based on unitary transformations, the three stages of our proposed algorithm #1 are all based on unitary transformations. The average number of multiplications required by our proposed algorithm #1 is about (29∕10)M³, where both the numbers of transmit and receive antennas are equal to M. In the meantime, the average number of multiplications required by the original SRA is (17∕3)M³. In addition to the stable initialization, ordering, and nulling considered by the proposed algorithm #1, our proposed algorithm #2 considers stable detection. Our proposed algorithm #2 is completely based on Givens rotations, which is to be implemented by COordinate Rotation DIgital Computer‐based hardwares. Copyright © 2011 John Wiley & Sons, Ltd.     

A note on hyperbolic transformations

We shall discuss the so‐called hyperbolic Householder and Givens transformations applied to complex matrices, including the case of zero hyperbolic energy of a transformed vector. For each case a numerically stable algorithm is available. Copyright © 2001 John Wiley & Sons, Ltd.     

Relaxed Annihilation-Reordering Look-Ahead QRD-RLS Adaptive Filters

The optimum architecture design and mapping of QRD-RLS adaptive filters can be achieved through filter architecture selections, look-ahead transformations, and hierarchical pipelining/folding transformations. In this paper, a relaxed annihilation-reordering look-ahead (RARL) architecture is proposed, and shown to be more power and area efficient than pipelined processing architecture which was considered the most area efficient. The filters with this architecture are based on relaxed weight-update through filtering approximation, where a filter tap weight is updated upon arrival of every block of input data, and are speeded up with annihilation-reordering look-ahead transformation. As a result of the computational complexity reduction, this architecture does not change the iteration bound and filter clock frequency, and leads to speed up with linear increase in power consumption, while the pipelined processing architectures result in speedup with quadratic increase in power consumption. Upon hardware mapping, this architecture is also more advantageous to achieve low area designs. Two design examples are presented to illustrate mapping optimization using above transformations. These results are important for mapping designs onto ASICs, FPGAs or parallel computing machines. The results show significant improvements in throughput, power consumption and hardware requirement. It is also interesting to show through mathematics and simulations that the RARL QRD-RLS filters have no performance degradation in terms of convergence rate.     

A note on the recursive calculation of dominant singular subspaces

A recursive procedure for computing an approximation of the left and right dominant singular subspaces of a given matrix is proposed in [1]. The method is particularly suited for matrices with many more rows than columns. The procedure consists of a few steps. In one of these steps a Householder transformation is multiplied to an upper triangular matrix. The following step consists in recomputing an upper triangular matrix from the latter product. In [1] it is said that the latter step is accomplished in O(k³) operations, where k is the order of the triangular matrix. In this short note we show that this step can be accomplished in O(k²) operations. This research was partially supported by MIUR, grant number 2002014121 (first author) and by the Research Council K.U.Leuven, project OT/00/16 (SLAP: Structured Linear Algebra Package), by the Fund for Scientific Research–Flanders (Belgium), projects G.0078.01 (SMA: Structured Matrices and their Applications), G.0176.02 (ANCILA: Asymptotic aNalysis of the Convergence behavior of Iterative methods in numerical Linear Algebra), G.0184.02 (CORFU: Constructive study of Orthogonal Functions) and G.0455.0 (RHPH: Riemann–Hilbert problems, random matrices and Padé–Hermite approximation), and by the Belgian Programme on Interuniversity Poles of Attraction, initiated by the Belgian State, Prime Ministers Office for Science, Technology and Culture, project IUAP V-22 (Dynamical Systems and Control: Computation, Identification & Modelling) (second and third author). The scientific responsibility rests with the authors.AMS subject classification 15A15, 15A09, 15A23     

基于复Givens矩阵与蝙蝠优化的卷积盲分离算法

针对传统卷积混合盲分离待求参数多、分离效果易受分离矩阵初值影响的局限性,提出了基于复Givens矩阵与蝙蝠优化的频域求解算法。算法采用复Givens矩阵表示分离矩阵,减少了待求参数,降低了求解难度和计算量。利用蝙蝠算法代替梯度算法优化求解旋转角度完成各频点线性瞬时混合复信号的盲分离,全局收敛性更强。此外,由于对源信号的先验知识要求较少,可以分离服从多种分布的信号。仿真实验表明,该算法可有效地实现卷积混合盲分离。     

Preconditioned GMRES methods with incomplete Givens orthogonalization method for large sparse least-squares problems

We propose to precondition the GMRES method by using the incomplete Givens orthogonalization (IGO) method for the solution of large sparse linear least-squares problems. Theoretical analysis shows that the preconditioner satisfies the sufficient condition that can guarantee that the preconditioned GMRES method will never break down and always give the least-squares solution of the original problem. Numerical experiments further confirm that the new preconditioner is efficient. We also find that the IGO preconditioned BA-GMRES method is superior to the corresponding CGLS method for ill-conditioned and singular least-squares problems.