摘要: Random matrix theory is now a big subject with applications in many disciplines of science, engineering and finance. This article survey specifically oriented towards the needs interests numerical analyst. includes some original material not found anywhere else. We include important mathematics which very modern development, as well computational software that transforming into useful practice.
daum.net 参考文章(95)
Kurt Johansson, Random Growth and Random Matrices Birkhäuser, Basel. pp. 445- 456 ,(2001) , 10.1007/978-3-0348-8268-2_25
Arno B.J. Kuijlaars, Riemann-Hilbert Analysis for Orthogonal Polynomials Lecture Notes in Mathematics. ,vol. 1817, pp. 167- 210 ,(2003) , 10.1007/3-540-44945-0_5
Lloyd N. Trefethen, Mark Embree, Spectra and Pseudospectra Princeton University Press. ,(2005) , 10.1515/9780691213101
Percy Deift, Integrable systems and combinatorial theory Notices of the American Mathematical Society. ,vol. 47, pp. 631- 640 ,(2000)
B.J.C. Baxter, A. Iserles, On the Foundations of Computational Mathematics Handbook of Numerical Analysis. ,vol. 11, pp. 3- 34 ,(2003) , 10.1016/S1570-8659(02)11001-5
Iain M. Johnstone, On the distribution of the largest eigenvalue in principal components analysis Annals of Statistics. ,vol. 29, pp. 295- 327 ,(2001) , 10.1214/AOS/1009210544
Harold Widom, Craig A. Tracy, Introduction to Random Matrices Springer Lecture Notes in Physics 424 (1993) 103-130. ,vol. 424, pp. 103- 130 ,(1993) , 10.1007/BFB0021444
Gideon Schechtman, Vitali D Milman, Asymptotic theory of finite dimensional normed spaces ,(1986)
Ioana Dumitriu, Eigenvalue statistics for beta-ensembles Massachusetts Institute of Technology. ,(2003)
Arvind Sankar, Smoothed analysis of Gaussian elimination Massachusetts Institute of Technology. ,(2004)