Springer, 2002, 324 p. This is an introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. Based on measure theory, which is introduced as smoothly as possible, it provides practical skills in the use of MAPLE in the context of probability and its applications. It offers to graduates and advanced undergraduates an overview and intuitive background for more advanced studies.
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Springer, 2011, 233 p. Thirty years ago mathematical, as opposed to applied numerical, computation was difficult to perform and so relatively little used. Three threads changed that: the emergence of the personal computer; the discovery of fiber-optics and the consequent development of the modern internet; and the building of the Three M’s Maple, Mathematica and MatLAB. We...
John Wiley & Sons, Inc., 2009, 219 p., 3 ed. The purpose of this guide is to give a quick introduction on how to use Maple. It primarily covers Maple 12, although most of the guide will work with earlier versions of Maple. Also, throughout this guide, we will be suggesting tips and diagnosing common problems that users are likely to encounter. This should make the learning process...
Springer, 2011. - 370 pages. ISBN: 3709105161 The emphasis of the book is given in how to construct different types of solutions (exact, approximate analytical, numerical, graphical) of numerous nonlinear PDEs correctly, easily, and quickly. The reader can learn a wide variety of techniques and solve numerous nonlinear PDEs included and many other differential equations,...
Second Edition. — Springer, 2009. — 483 p. The first book to compare the main two computer algebra systems (CAS), Maple and Mathematica used by students, mathematicians, scientists, and engineers. Both systems are presented in parallel so that Mathematica users can learn Maple quickly by finding the Maple equivalent to Mathematica functions, and vice versa. This student...
Springer, 2013. — 287 p. 54 illus. — ISBN: 1461440564, 9781461440574 The book presents an introduction to Stochastic Processes including Markov Chains, Birth and Death processes, Brownian motion and Autoregressive models. The emphasis is on simplifying both the underlying mathematics and the conceptual understanding of random processes. In particular, non-trivial computations...
