Titlebook: Linear Algebra for Large Scale and Real-Time Applications; Marc S. Moonen,Gene H. Golub,Bart L. R. Moor Book 1993 Springer Science+Busines

GUST

書目名稱Linear Algebra for Large Scale and Real-Time Applications影響因子(影響力)




書目名稱Linear Algebra for Large Scale and Real-Time Applications影響因子(影響力)學科排名




書目名稱Linear Algebra for Large Scale and Real-Time Applications網(wǎng)絡公開度




書目名稱Linear Algebra for Large Scale and Real-Time Applications網(wǎng)絡公開度學科排名




書目名稱Linear Algebra for Large Scale and Real-Time Applications被引頻次




書目名稱Linear Algebra for Large Scale and Real-Time Applications被引頻次學科排名




書目名稱Linear Algebra for Large Scale and Real-Time Applications年度引用




書目名稱Linear Algebra for Large Scale and Real-Time Applications年度引用學科排名




書目名稱Linear Algebra for Large Scale and Real-Time Applications讀者反饋




書目名稱Linear Algebra for Large Scale and Real-Time Applications讀者反饋學科排名

放氣

Adaptive Signal Processing with Emphasis on QRD-Least Squares Lattice. The algorithm makes it possible for the filter to perform satisfactorily in an environment when complete knowledge of the relevant signal characteristics is not available [1], Adaptive filters find applications in such diverse fields as communications, radar, sonar, control, and biomedical engineering.

jaundiced

Computing the Singular Value Decomposition on a Fat-Tree Architecturen necessary to calculate the SVD in real time. We present here a new technique for computing the SVD on a parallel architecture whose processors are connected via a fat-tree. We tested our idea on the Connection Machine CM-5, and achieved efficiency up to 40% even for moderately sized matrices.

排出

Determining Rank in the Presence of Errorsition and make a decision about the rank by examining the small elements of the decomposition. In this paper we look at three commonly use decompositions: the singular value decomposition, the pivoted QR decomposition, and the URV decomposition.

Myocyte

因無茶而冷淡

Trading off Parallelism and Numerical StabilityThe fastest parallel algorithm for a problem may be significantly less stable numerically than the fastest serial algorithm. We illustrate this phenomenon by a series of examples drawn from numerical linear algebra. We also show how some of these instabilities may be mitigated by better floating point arithmetic.

袋鼠

Case Studies of Real-Time Processing in RoboticsExamples are used to illustrate how robotics is computationally demanding, particularly with respect to time constraints within which the computation must complete. The examples are picked both from control algorithms for robots and from sensor data interpretation for robotics. The linear algebra problems involved are indicated.

停止償付

A New Matrix Decomposition for Signal ProcessingWe extend the generalized singular value decomposition to a new decomposition that can be updated at a low cost. In addition, we show how a forgetting factor can be incorporated in our decomposition.

束縛

NATO Science Series E:http://image.papertrans.cn/l/image/586278.jpg

格言

978-90-481-4246-0Springer Science+Business Media Dordrecht 1993