Linear and Nonlinear Programming with Maple, Fishback, Paul E.

Автор: Erik W. Grafarend , Silvelyn Zwanzig , Joseph L. Awange
Название: Applications of Linear and Nonlinear Models
ISBN: 3030945979 ISBN-13(EAN): 9783030945978
Издательство: Springer
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Цена: 186330.00 T
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Описание: This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view and a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss–Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters, we concentrate on underdetermined and overdetermined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE, and total least squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimation by the so-called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann–Plucker coordinates, criterion matrices of type Taylor–Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overjet. This second edition adds three new chapters: (1) Chapter on integer least squares that covers (i) model for positioning as a mixed integer linear model which includes integer parameters. (ii) The general integer least squares problem is formulated, and the optimality of the least squares solution is shown. (iii) The relation to the closest vector problem is considered, and the notion of reduced lattice basis is introduced. (iv) The famous LLL algorithm for generating a Lovasz reduced basis is explained. (2) Bayes methods that covers (i) general principle of Bayesian modeling. Explain the notion of prior distribution and posterior distribution. Choose the pragmatic approach for exploring the advantages of iterative Bayesian calculations and hierarchical modeling. (ii) Present the Bayes methods for linear models with normal distributed errors, including noninformative priors, conjugate priors, normal gamma distributions and (iii) short outview to modern application of Bayesian modeling. Useful in case of nonlinear models or linear models with no normal distribution: Monte Carlo (MC), Markov chain Monte Carlo (MCMC), approximative Bayesian computation (ABC) methods. (3) Error-in-variables models, which cover: (i) Introduce the error-in-variables (EIV) model, discuss the difference to least squares estimators (LSE), (ii) calculate the total least squares (TLS) estimator. Summarize the properties of TLS, (iii) explain the idea of simulation extrapolation (SIMEX) estimators, (iv) introduce the symmetrized SIMEX (SYMEX) estimator and its relation to TLS, and (v) short outview to nonlinear EIV models. The chapter on algebraic solution of nonlinear system of equations has also been updated in line with the new emerging field of hybrid numeric-symbolic solutions to systems of nonlinear equations, ermined system of nonlinear equations on curved manifolds. The von Mises–Fisher distribution is characteristic for circular or (hyper) spherical data. Our last chapter is devoted to probabilistic regression, the special Gauss–Markov model with random effects leading to estimators of type BLIP and VIP including Bayesian estimation. A great part of the work is presented in four appendices. Appendix A is a treatment, of tensor algebra, namely linear algebra, matrix algebra, and multilinear algebra. Appendix B is devoted to sampling distributions and their use in terms of confidence intervals and confidence regions. Appendix C reviews the elementary notions of statistics, namely random events and stochastic processes. Appendix D introduces the basics of Groebner basis algebra, its careful definition, the Buchberger algorithm, especially the C. F. Gauss combinatorial algorithm.

Автор: Luis V?zquez; Salvador Jimenez
Название: Newtonian Nonlinear Dynamics for Complex Linear and Optimization Problems
ISBN: 1461459117 ISBN-13(EAN): 9781461459118
Издательство: Springer
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Цена: 121890.00 T
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Описание: This book takes in some of the latest mathematical applications derived from Newtonian law. It explains the mechanical method for determining matrix singularity or non-independence of dimension and complexity, and includes new approaches to standard problems.

Автор: Kythe, Prem K.
Название: Green`s Functions and Linear Differential Equations
ISBN: 1439840083 ISBN-13(EAN): 9781439840085
Издательство: Taylor&Francis
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Цена: 148010.00 T
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Автор: Dingyu Xue
Название: Differential Equation Solutions with MATLAB
ISBN: 3110675242 ISBN-13(EAN): 9783110675245
Издательство: Walter de Gruyter
Цена: 74320.00 T
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Описание:

This book focuses the solutions of differential equations with MATLAB. Analytical solutions of differential equations are explored first, followed by the numerical solutions of different types of ordinary differential equations (ODEs), as well as the universal block diagram based schemes for ODEs. Boundary value ODEs, fractional-order ODEs and partial differential equations are also discussed.

Автор: Marc Schniederjans
Название: Goal Programming: Methodology and Applications
ISBN: 1461359376 ISBN-13(EAN): 9781461359371
Издательство: Springer
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Цена: 139750.00 T
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Автор: Ernic Kamerich
Название: A Guide to Maple
ISBN: 1461264367 ISBN-13(EAN): 9781461264361
Издательство: Springer
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Цена: 46570.00 T
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Описание: This "hands-on" book is for people who are interested in immediately putting Maple to work. The book is sufficient for standard use of Maple and will provide techniques for extending Maple for more specialized work. The book allows a reader to become a user almost immediately and helps him/her to grow gradually to a broader and more proficient use.

Автор: Jos? Luis G?mez Pardo
Название: Introduction to Cryptography with Maple
ISBN: 3642446213 ISBN-13(EAN): 9783642446214
Издательство: Springer
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Цена: 55890.00 T
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Описание: This introduction to cryptography uses a programming-oriented approach to study important current cryptographic schemes and the main cryptanalytic attacks against them. The Maple implementations include many examples with parameters of realistic size.

Автор: Bruce F. Torrence, Eve A. Torrence
Название: The Student`s Introduction to Mathematica and the Wolfram Language
ISBN: 110840636X ISBN-13(EAN): 9781108406369
Издательство: Cambridge Academ
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Цена: 51750.00 T
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Описание: This book introduces Mathematica (R) and the Wolfram Language (TM) in the context of the standard university mathematics curriculum. It equips current and former students to harness these tools to explore ideas from pre-calculus, calculus, and linear algebra. Additional chapters on programming and 3D printing provide outlets for further exploration.

Автор: Klima, Richard
Название: Applied Abstract Algebra with MapleTM and MATLAB®
ISBN: 1482248239 ISBN-13(EAN): 9781482248234
Издательство: Taylor&Francis
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Цена: 107190.00 T
Наличие на складе: Нет в наличии.

Автор: Claire Montemar
Название: Linear Algebra: Theorems and Applications
ISBN: 1773612123 ISBN-13(EAN): 9781773612126
Издательство: Mare Nostrum (Eurospan)
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Цена: 155230.00 T
Наличие на складе: Невозможна поставка.
Описание: Welcome to the beginning of this book - an algebra book that shows and explains further topics than those that are covered in a primary course on linear algebra. Such course usually leaves the student with the question “Why in the world do I have to go through linear algebra?” which is absolutely understandable. Algebra, and other sciences in general, are not entities that one just needs to pass as a course. Sciences are masters that stay with you and are always there whenever you need them, that in some occasions we do not understand that those masters are something else.Before talking about the importance of algebra, let us first clear some details about this text. This book does not only contain a set of complicated equations with heavy definitions about abstract entities and problems that arise in several fields of mathematics, which in many other texts, makes you feel like you’re reading Mandarin. This book also contains clear and deductive explanations from different perspectives about those set of complicated equations, with the hope of making them accessible and easy to assimilate for the reader.Algebra is the science of representing life through equations while keeping it simple. The reason for writing this book was, at first, the decision to spread knowledge of such a great science that is usually feared by many young students and ignored by others, when in reality Algebra is a body of knowledge so beautiful within itself, as well as necessary dealing with or approaching many mathematical situations. As this book is being developed, another reason to continue to write it arose – there is a lack of easy-to-understand texts, which are supposed to be the high end books that today’s generation are obligated to read, in order to understand the subjects they should know to continue their formation in their respective careers.This book is dedicated to those who really want to learn linear algebra. But be warned, the journey is not promised to be easy as it will require dedication, honesty and time from the reader; but the journey will also be nurturing and revealing in the sense that at the end of each chapter, the reader will be able to say “I’ve got it!” in much the same way when Archimedes said “Eureka!” which means “I’ve found it!” In addition, this book also contains techniques and algorithms, along with their derivations and examples, which are used in the real world, thus helping the reader become a well prepared professional.Many texts, articles and lessons were used as resources for this book, however, the most used resource in the development of this text was common sense. You see, mathematics is a free science, a body of knowledge that anyone can derive on its own. This book is just a compendium of the works of many mathematicians through the centuries, making it possible for humankind to get to where it is today. And as life goes on, it is probable that further developments, researches and advances will continue. That was one of the main ideas in the background while writing this text - to make the reader able to fully understand as much knowledge in linear algebra as possible, especially those concerning methods and algorithms that arose in the twentieth century.Just as a brief comment, the first chapter of this book is dedicated to making certain topics clear to avoid confusion, and answering questions that usually arise during the first course in linear algebra. The rest of the chapters are more advanced and developed.

Автор: George B. Dantzig; Mukund N. Thapa
Название: Linear Programming 1
ISBN: 1475781121 ISBN-13(EAN): 9781475781120
Издательство: Springer
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Цена: 111790.00 T
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Описание: Encompassing all the major topics students will encounter in courses on the subject, the authors teach both the underlying mathematical foundations and how these ideas are implemented in practice.

Автор: Hu T. C., Kahng Andrew B.
Название: Linear and Integer Programming Made Easy
ISBN: 3319795686 ISBN-13(EAN): 9783319795683
Издательство: Springer
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Цена: 55890.00 T
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Описание: This textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc., are becoming fundamental toolkits for data and information science and technology.