Category - "General Engineering"

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Although powerful and very popular in science and engineering, Mathematica can be difficult to learn because of its large command structure and intricate syntax. This book offers a simple, step-by-step approach to help newcomers to Mathematica build the skills needed to use the software in practice. Aimed at professionals with a good mathematics background, this book teaches by example, pointing out potential pitfalls along the way. In an easy-to-use format not found in other books and downloadable code furnished on the Internet, it covers many of the general areas of mathematics, including entering equations, plotting, computing ordinary and partial differential equations, and linear algebra.

Placing combinatorial and graph-theoretical tools at the forefront of the development of matrix theory, this book uses graphs to explain basic matrix construction, formulas, computations, ideas, and results. It presents material rarely found in other books at this level, including Gersgorin’s theorem and its extensions, the Kronecker product of matrices, sign-nonsingular matrices, and the evaluation of the permanent matrix. The authors provide a combinatorial argument for the classical Cayley–Hamilton theorem and a combinatorial proof of the Jordan canonical form of a matrix. They also describe several applications of matrices in electrical engineering, physics, and chemistry.

Drawing from the history of mathematics and practical applications, A Concrete Introduction to Real Analysis uses problems emerging from calculus to introduce themes of estimation, approximation, and convergence. Avoiding unnecessary abstractions to provide an accessible presentation of material, this book covers discrete calculus, selected area computations, Taylor's theorem, infinite sequences and series, limits, continuity and differentiability of functions, the Riemann integral, and much more. It contains a large collection of examples and exercises, ranging from simple problems that allow students to check their understanding to challenging problems that develop new material.

Categorical data requires a different methodology and techniques typically not encountered in introductory statistics courses. Developed from long experience in teaching categorical analysis to a multidisciplinary mix of graduate and undergraduate students, A Course in Categorical Data Analysis presents the easiest, most straightforward ways of extracting real-life conclusions from contingency tables. The author uses a Fisherian approach to categorical data analysis and incorporates numerous examples and real data sets. S-plus routines are offered on the Internet, but readers do not need full knowledge of a statistical software package.

Emphasizing Markovian structures and the techniques that occur in different models, A Course on Queueing Models discusses recent developments in the field, different methodological tools - some of which are not available elsewhere - and computational techniques. The book covers fundamentals on Markovian and regenerative non-Markovian models as well as computational methods, statistical inference, and simulation. It also presents network queues, discrete time queues, optimization, combinatorial treatments in transient analysis, general queues, duality in queues, and new computational methods. Each self-contained chapter features a discussion section that summarizes material and highlights special features.