By Jane K. Cullum, Ralph A. Willoughby (auth.)
Read or Download Lanczos Algorithms for Large Symmetric Eigenvalue Computations Vol. II Programs PDF
Best algorithms books
Algorithms For Interviews (AFI) goals to assist engineers interviewing for software program improvement positions in addition to their interviewers. AFI comprises 174 solved set of rules layout difficulties. It covers center fabric, akin to looking and sorting; basic layout ideas, similar to graph modeling and dynamic programming; complex issues, reminiscent of strings, parallelism and intractability.
This ebook focuses like a laser beam on one of many most well-liked subject matters in evolutionary computation over the past decade or so: estimation of distribution algorithms (EDAs). EDAs are an incredible present strategy that's resulting in breakthroughs in genetic and evolutionary computation and in optimization extra typically.
This self-contained monograph is an built-in examine of typical structures outlined through iterated relatives utilizing the 2 paradigms of abstraction and composition. This comprises the complexity of a few state-transition structures and improves realizing of advanced or chaotic phenomena rising in a few dynamical platforms.
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: a brand new instrument for Evolutionary Computation is dedicated to a brand new paradigm for evolutionary computation, named estimation of distribution algorithms (EDAs). This new classification of algorithms generalizes genetic algorithms through exchanging the crossover and mutation operators with studying and sampling from the chance distribution of the easiest participants of the inhabitants at every one generation of the set of rules.
- Automate This: How Algorithms Came to Rule Our World
- Computational geometry: An introduction through randomized algorithms
- WALCOM: Algorithms and Computation: 5th International Workshop, WALCOM 2011, New Delhi, India, February 18-20, 2011. Proceedings
- Computability theory
- Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI
Additional info for Lanczos Algorithms for Large Symmetric Eigenvalue Computations Vol. II Programs
Sample text
C LEV12260 C LEV12270 (0,1) MEANS ERCONT C LEV12280 C LEV12290 ( 0) PROCEDURE WILL NOT COMPUTE A RITZ VECTOR FOR C LEV12300 ANY EIGENVALUE FOR WHICH NO T-EIGENVECTOR WHICH C LEV12310 SATISFIES THE ERROR ESTIMATE TEST (ERTOL) HAS C LEV12320 BEEN IDENTIFIED. C LEV12330 C LEV12340 (1 ) A RITZ VECTOR WILL BE COMPUTED FOR EVERY C LEV12350 EIGENVALUE FOR WHICH A T-EIGENVECTOR HAS BEEN C LEV12360 COMPUTED REGARDLESS OF WHETHER OR NOT THAT C LEV12370 T-EIGENVECTOR SATISFIED THE ERROR ESTIMATE TEST. C LEV12380 C LEV12390 C C-----INPUT/OUTPUT FILES FOR THE EIGENVECTOR COMPUTATIONS---------------LEVI2400 LEV12410 C LEV12420 C LEV12430 ANY INPUT DATA OTHER THAN THE T-MATRIX HISTORY FILE AND THE C LEV12440 PREVIOUSLY COMPUTED EIGENVALUES AND CORRESPONDING ERROR C LEV12450 ESTIMATES SHOULD BE STORED ON FILE 5 IN FREE FORMAT.
BTOL) GO TO 210 LEV03100 IBMEV = -IBMEV LEV03110 GO TO 600 LEV03120 C LEV03130 210 CONTINUE LEV03140 IC = MXSTUR-ICT LEV03150 C LEV03160 C-----------------------------------------------------------------------LEV03170 C BISEC LOOP. THE SUBROUTINE BISEC INCORPORATES DiRECTLY THE LEV03180 C T-MULTIPLICITY AND SPURIOUS TESTS. T-EIGENVALUES WILL BE LEV03190 C CALCULATED BY BISEC SEQUENTIALLY ON INTERVALS LEV03200 C (LB(J),UB(J)), J = 1,NINT). LEV03210 C LEV03220 C ON RETURN FROM BI SEC LEV03230 C NO IS = NUMBER OF 0 IST I NCT EIGENVALUES OF T( 1 ,MEV) ON UN ION LEV03240 C OF THE (LB,UB) INTERVALS LEV03250 C VS = DISTINCT T-EIGENVALUES IN ALGEBRAICALLY INCREASING ORDER LEV03260 C MP = MULTIPLICITIES OF THE T-EIGENVALUES IN VS LEV03270 C MP(I) = (O,l,MI), MI>l, l=l,NDIS MEANS: LEV03280 C (0) VS( I) IS SPURIOUS LEV03290 C (1) VS( I) IS T-S IMPLE AND GOOD LEV03300 C (MI) VS( I) is MULTIPLE AND IS THEREFORE NOT ONLY GOOD BUT LEV03310 C ALSO A CONVERGED GOOD T-EIGENVALUE.
LEVII180 C LEVII190 C THIS IMPLEMENTATION FIRST COMPUTES ALL OF THE RELEVANT LEVI1200 C EIGENVECTORS OF THE SYMMETRIC TRIDIAGONAL MATRICES LEVI1210 LEVl1220 IN THE VECTOR. TVEC. C LEVI1230 C LEV 11240 THEN. AS ~ACH OF THE LANCZOS VECTORS IS REGENERATED. ALL C LEVI1250 OF THE RITZ VECTORS CORRESPONDING TO THESE C LEVI1260 T-EIGENVECTORS ARE UPDATED USING THE CURRENTLY-GENERATED C LEVI1270 LANCZOS VECTOR. LANCZOS VECTORS ARE GENERATED (NOTE C LEVI1280 THAT THEY ARE NOT BEING KEPT). UNTIL ENOUGH HAVE C LEVI1290 BEEN GENERATED TO MAP THE LONGEST T-EIGENVECTOR INTO ITS C LEVI1300 CORRESPONDING RITZ VECTOR.