New Hardcover 2nd Edition (as shown PLEASE READ!!!! THIS IS HARDCOVER COPY)

An Introduction to Numerical Computations (2nd Edition)

Computers & Technology

Szidarovszky, Ferenc

Yakowitz, Sidney

Computer Science

Pearson

It is an incontestable fact that numerical analysis techniques are used rou tinely (although not always effectively) in virtually every quantitative field of scientific endeavor. In this book, which is directed toward upper-division and graduate level students in engineering and mathematics, we have selected for discussion subjects that are traditionally found in numerical analysis texts. But our choice of methodology rejects the traditional where analysis and experience clearly warrant such a departure, and one of our primary aspirations in this work is to equip the reader with the wherewithal to apply numerical analysis thinking to nontraditional subjects. For there is a plethora of computer-oriented sciences such as optimization, statistics, and system analysis and identification that are sorely in need of methods comparable to those related here for classical numerical analysis problems. Toward uncovering for the reader the structure of numerical methods we have, for example, devoted a chapter to a metric space theory for iter ative application of operators. In this chapter, we have collected those definitions and concepts of real and functional analysis that are requisite to a modern intermediate-level exposition of the principles of numerical anal ysis. Further, we derive the abstract theory (most notably, the contraction mapping theorem) for iteration processes.

Principles and Procedures of Numerical Analysis (Mathematical Concepts and Methods in Science and Engineering, 14)

Science & Math

Yakowitz, Sidney J.

Mathematics

Springer

In almost every engineering, business or personal decision there are several conflicting objectives or criteria to be considered. The choice of objectives unavoidably involves subjective judgements, yet it is possible to embed many aspects of subjective judgements into a rigorous mathematical framework. Although there is a wide-ranging literature on the subject, there are relatively few books which attempt to present multi-objective decision making techniques in a comprehensive, unified and rigorous manner as this book does. It contains a wide spectrum of multiobjective decision making techniques based on quantitative, as well as qualitative, criteria. In addition to the description of the algorithms, their mathematical properties and practical applications are discussed. Of particular interest is the discussion of the relationship between the traditionally used concept of the efficient (non-dominated) solution and the equilibrium point used in game theoretical models. Other valuable features of the book are that it presents, for the first time, a rigorous mathematical framework for the multiobjective models and that it also includes the recently emphasized area of model choice, including a prescriptive algorithm. A complete set of clear examples illustrates each of the models and detailed case studies show the practical application of the models. Researchers and practitioners in decision making will find this a very useful book. It is an ideal learning and teaching aid for courses on multiple criteria decision making in the management of large scale systems. In comparing projects, plans or alternatives on the basis of a set of quantitative and/or qualitative criteria, the principles and techniques discussed will be useful, if not indispensable, tools.

Techniques for Multi-Objective Decision Making in Systems Management (Advances in Industrial Engineering)

Business & Money

Gershon, Mark E.

Duckstein, L.

Management & Leadership

Elsevier Science Ltd.

Techniques for multiobjective decision making in systems management (Advances in industrial engineering)

Distributors for the U.S. and Canada, Elsevier Science Pub. Co

Game theory, defined in the broadest sense, is a collection of mathematical models designed for the analysis of strategic aspects of situations of conflict and cooperation in a broad spectrum of fields including economics, politics, biology, engineering, and operations research. This book, besides covering the classical results of game theory, places special emphasis on methods of determining `solutions' of various game models. Generalizations reaching beyond the `convexity paradigm' and leading to nonconvex optimization problems are enhanced and discussed in more detail than in standard texts on this subject. The development is theoretical-mathematical interspersed with elucidating interpretations and examples. Audience: The material in the book is accessible to PhD and graduate students and will also be of interest to researchers. Solid knowledge of standard undergraduate mathematics is required to read the book.

Introduction to the Theory of Games: Concepts, Methods, Applications (Nonconvex Optimization and Its Applications, 32)

Forgó, Ferenc

Szép, Jeno

Economics

This second edition comprehensively presents important tools of linear systems theory, including differential and difference equations, Laplace and Z transforms, and more. Linear Systems Theory discusses: 
<li>Nonlinear and linear systems in the state space form and through the transfer function method 
</li>
<li>Stability, including marginal stability, asymptotical stability, global asymptotical stability, uniform stability, uniform exponential stability, and BIBO stability 
</li>
<li>Controllability 
</li>
<li>Observability 
</li>
<li>Canonical forms 
</li>
<li>System realizations and minimal realizations, including state space approach and transfer function realizations 
</li>
<li>System design 
</li>
<li>Kalman filters 
</li>
<li>Nonnegative systems 
</li>
<li>Adaptive control 
</li>
<li>Neural networks The book focuses mainly on applications in electrical engineering, but it provides examples for most branches of engineering, economics, and social sciences. What's New in the Second Edition? 
</li>
<li>Case studies drawn mainly from electrical and mechanical engineering applications, replacing many of the longer case studies 
</li>
<li>Expanded explanations of both linear and nonlinear systems as well as new problem sets at the end of each chapter 
</li>
<li>Illustrative examples in all the chapters 
</li>
<li>An introduction and analysis of new stability concepts 
</li>
<li>An expanded chapter on neural networks, analyzing advances that have occurred in that field since the first edition Although more mainstream than its predecessor, this revision maintains the rigorous mathematical approach of the first edition, providing fast, efficient development of the material. Linear Systems Theory enables its reader to develop his or her capabilities for modeling dynamic phenomena, examining their properties, and applying them to real-life situations.</li>

Linear Systems Theory (Systems Engineering)

Politics & Social Sciences

Social Sciences

Routledge

Linear Systems Theory is a comprehensive text that presents a mathematically rigorous development of important tools of linear systems theory. These tools include differential and difference equations, Laplace and Z transforms, state space and transfer function representations, stability, controllability and observability, duality, canonical forms, realizability, minimal realizations, observers, feedback compensators, nonnegative systems, Kalman filters, and adaptive control and neural networks.

Bahill, A. Terry

Physics

CRC-Press

The Theory and Applications of Iteration Methods focuses on an abstract iteration scheme that consists of the recursive application of a point-to-set mapping. Each chapter presents new theoretical results and important applications in engineering, dynamic economic systems, and input-output systems. At the end of each chapter, case studies and numerical examples are presented from different fields of engineering and economics. Following an outline of general iteration schemes, the authors extend the discrete time-scale Liapunov theory to time-dependent, higher order, nonlinear difference equations. The monotone convergence to the solution is examined in and comparison theorems are proven . Results generalize well-known classical theorems, such as the contraction mapping principle, the lemma of Kantorovich, the famous Gronwall lemma, and the stability theorem of Uzawa. The book explores conditions for the convergence of special single- and two-step methods such as Newton's method, modified Newton's method, and Newton-like methods generated by point-to-point mappings in a Banach space setting. Conditions are examined for monotone convergence of Newton's methods and their variants. Students and professionals in engineering, the physical sciences, mathematics, and economics will benefit from the book's detailed examples, step-by-step explanations, and effective organization.

The Theory and Applications of Iteration Methods (Systems Engineering)

Argyros, Ioannis K.

A comprehensive guide to the application and processing of condition-based data to produce prognostic estimates of functional health and life. Prognostics and Health Management provides an authoritative guide for an understanding of the rationale and methodologies of a practical approach for improving system reliability using conditioned-based data (CBD) to the monitoring and management of health of systems. This proven approach uses electronic signatures extracted from conditioned-based electrical signals, including those representing physical components, and employs processing methods that include data fusion and transformation, domain transformation, and normalization, canonicalization and signal-level translation to support the determination of predictive diagnostics and prognostics. Written by noted experts in the field, Prognostics and Health Management clearly describes how to extract signatures from conditioned-based data using conditioning methods such as data fusion and transformation, domain transformation, data type transformation and indirect and differential comparison. This important resource: <ul>
<li>Integrates data collecting, mathematical modelling and reliability prediction in one volume</li> <li>Contains numerical examples and problems with solutions that help with an understanding of the algorithmic elements and processes</li> <li>Presents information from a panel of experts on the topic</li> <li>Follows prognostics based on statistical modelling, reliability modelling and usage modelling methods</li> </ul>
Written for system engineers working in critical process industries and automotive and aerospace designers, Prognostics and Health Management offers a guide to the application of condition-based data to produce signatures for input to predictive algorithms to produce prognostic estimates of functional health and life.

Prognostics and Health Management: A Practical Approach to Improving System Reliability Using Condition-Based Data (Quality and Reliability Engineering Series)

Goodman, Douglas

Hofmeister, James P.

Networking & Cloud Computing

wiley

Game theory, defined in the broadest sense, is a collection of mathematical models designed for the analysis of strategic aspects of situations of conflict and cooperation in a broad spectrum of fields including economics, politics, biology, engineering, and operations research. This book, besides covering the classical results of game theory, places special emphasis on methods of determining `solutions' of various game models. Generalizations reaching beyond the `convexity paradigm' and leading to nonconvex optimization problems are enhanced and discussed in more detail than in standard texts on this subject. The development is theoretical-mathematical interspersed with elucidating interpretations and examples.  Audience: The material in the book is accessible to PhD and graduate students and will also be of interest to researchers. Solid knowledge of standard undergraduate mathematics is required to read the book.

Introduction to the Theory of Games: Concepts, Methods, Applications (Nonconvex Optimization and Its Applications)

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