Posted by **insetes** at Nov. 6, 2015

2003 | 348 Pages | ISBN: 0198506260 | PDF | 6 MB

Posted by **tanas.olesya** at July 24, 2015

English | Oct. 12, 2000 | ISBN: 3540571000 | 393 Pages | PDF | 12 MB

An up-to-date, self-contained review of a wide range of recursive methods for stabilization, identification and control of complex stochastic models (guiding a rocket or a plane, organizing multi-access broadcast channels, self-learning of neural networks …). Suitable for mathematicians (researchers and also students) and engineers.

Posted by **roxul** at March 2, 2015

English | ISBN: 0198506260 | 2003 | 348 pages | PDF | 6 MB

Posted by **arundhati** at Nov. 14, 2014

2015 | ISBN-10: 3319100637 | 492 pages | PDF | 14 MB

Posted by **Specialselection** at Feb. 3, 2014

English | 2006-10-23 | ISBN: 0521866561 | 222 pages | PDF | 1.3 mb

Posted by **arundhati** at Jan. 5, 2014

2013 | ISBN-10: 1461463157 | 181 pages | PDF | 5 MB

Posted by **arundhati** at Dec. 5, 2013

2007 | ISBN-10: 1860947867 | 260 pages | PDF | 3,6 MB

Posted by **Veslefrikk** at Nov. 18, 2013

Cambridge University Press | 2001-02-15 | ISBN: 0521802091 | 496 pages | Djvu | 2,8 MB

Posted by **Alexpal** at Sept. 3, 2006

Cambridge University Press | ISBN 0521802091 | 2001 Year | DjVu | 2,52 Mb | 496 Pages

Posted by **hill0** at Jan. 17, 2017

English | 20 Jan. 2017 | ISBN: 9811033153 | 152 Pages | PDF | 1.83 MB

This is a first book to show that the theory of the Gaussian random matrix is essential to understand the universal correlations with random fluctuations and to demonstrate that it is useful to evaluate topological universal quantities. We consider Gaussian random matrix models in the presence of a deterministic matrix source.