By Bernhard Beckermann, Edward B. Saff (auth.), Walter Gautschi, Gerhard Opfer, Gene H. Golub (eds.)
The workshop on purposes and Computation of Orthogonal Polynomials came about March 22-28, 1998 on the Oberwolfach Mathematical study Institute. It was once the 1st workshop in this subject ever held at Oberwolfach. there have been forty six members from thirteen international locations, greater than part coming from Germany and the USA, and a considerable quantity from Italy. a complete of 23 plenary lectures have been offered and four brief casual talks. Open difficulties have been mentioned in the course of a night consultation. This quantity includes refereed models of 18 papers offered at, or submitted to, the convention. the idea of orthogonal polynomials, as a department of classical research, is definitely proven. yet orthogonal polynomials play additionally an enormous function in lots of components of medical computing, akin to least squares becoming, numerical integration, and fixing linear algebraic platforms. even though the fundamental tenets have their roots in nineteenth century arithmetic, using sleek pcs has required the advance and research of latest algorithms which are exact and strong. The computational equipment and purposes represented during this quantity, of necessity, are incomplete, but sufficiently assorted to show an effect of present actions during this area.
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Extra resources for Applications and Computation of Orthogonal Polynomials: Conference at the Mathematical Research Institute Oberwolfach, Germany March 22–28, 1998
Example text
For example, to compute the numerator of >'kH with the choice Uk(~) = ~k in Lanczos/Orthomin, we need to compute (y, Akrk ). Since the vector 26 C. Brezinski and M. Redivo-Zaglia Comparison of iterative residuals 1014 1011 \08 \0' 102 \0-1 \0-4 " \0-7 " /\_ ... ''.. - 80 90 100 Comparison of actual residuals \010 \07 \0' \0 1 \0-2 -, \0-' " \0-8 ", 10- 11 0 FIGURE l. \0 20 30 40 50 60 70 - , 100 Iterative and actual residuals for the matrix riemann rk depends on k, the computation of Akrk requires k matrix-vector products and the algorithm becomes costly.
Transpose-Free Look-Ahead Algorithms for Lanczos' Method 33 Incorporating in the code of the BSMRZS the recursive computation of the iterates and of the residuals of Lanczos' method, and also the recurrence for the auxiliary vectors, we get a look-ahead transpose-free algorithm for implementing simultaneously Lanczos' method and the CGS. Its pseudocode is given in the next subsection. 1. TFLA Lanczos/Orthosym and Look-Ahead CGS Algorithm TFLACGS (A,b,xo,y,n,e) 1. Initializations TO t-- b - Axo Zo = TO Xo =Xo fo = Zo = So = To no t-- 0 m-1 t-- 0 O'~O) t-- (y, fo) 2.
T-- (- y, Sk+1 ) end if Execute the tests for breakdown and near-breakdown While breakdown or near-breakdown do Repeat mk t-- mk + 1 c. Brezinski and M. Redivo-Zaglia 34 C2'Tnk-2 +-- y, A 2'Tnk-I-) Zk ~ C2'Tnk- 1 +-- y, A 2'Tnk Zk) compute A'Tnk Zk Ifmk:::; nk + 1 then compute A 2'Tnk-3 rk , A2'Tnk-2 rk , A'Tnk-I rk else compute Ank+'Tn ksk end if If mk :::; nk then d2'Tnk- 2 +-- (y, A 2'Tn k-2 Sk ) d2'Tnk- 1 +-- (Y, A 2'Tn k-I Sk ) else dnk+'Tnk- 1 +-- (y, Ank+'Tnk- 1Sk) end if compute f3i and the coefficients 'Yi of Wk, i = 0, ...