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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3rd Edition, Elsevier Inc, 2005. – 550 p. Maple by Example bridges the gap that exists between the very elementary handbooks available on Maple and those reference books written for the advanced Maple users. Maple by Example is an appropriate reference for all users of Maple and, in particular, for beginning users like students, instructors, engineers, business people, and...
Springer, 2014. — 905 p. 133 illus., 53 illus. in color. — (Texts in Computational Science and Engineering, Vol. 11). — ISBN: 9783319043258 Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic...
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...
Artech House Publishers, 2009. - 406 p. MAPLE is easy-to-use software that performs numerical and symbolic analysis to solve complex mathematical problems. A reference for engineers, scientists, and application developers, it shows you how to tap the full power of MAPLE in solving real-world engineering problems in circuit theory, control theory, curve fitting, mechanics and...
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...
