Scientific Computing

Book Description

Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems.

Customer Reviews:

very nice conceptual overview.......2006-07-22

Wow, people seem to be really split on this book. I had Mike Heath for numerical analysis/scientific computing and he was an excellent instructor, one of the best lecturers I've ever had. (As a consequence, I have a hard time separating the book and the class, so judge accordingly.) The book is based on his lecture notes, though he added some material and didn't cover every topic in the book. Just reading the book is useful to give you an overview of the point behind different methods. The goal of the class for which this book was written is actually quite conceptual. It was to give scientists (that's me: a stats researcher who makes heavy use of numerical computation) and CS people in areas other than scientific computing a leg up. It was only a first class for people in scientific computing, the rough equivalent of intro Physics or intro Probability/Stats for people in those respective majors. However, you *won't* be prepared to "roll your own" from this book. In fact, at the beginning of the semester Heath was very careful to note that if you have the opportunity to use a library function for most numerical programming, you are nuts to roll your own. Why? Numerical algorithms are usually extremely complicated and the authors of the code often spend years developing careful expertise on them. Frequently the formulas used to elucidate a given method are NOT the ones used to implement it. You need error traps, tricks to handle ill-scaling and other special cases, etc. These are things that someone who has a one-semester, superficial understanding of a topic simply won't have. So consider the book on the goals it set: it is an overview of a field. If you want to learn more about any one topic, you have to dig deeper and consult references and other works, but this is a good place to start. For this, the book serves admirably.

Not for the practitioner.......2005-11-17

If you are interested in Scientific computing from the viewpoint of the end user that is the guy who uses the method to solve practical engineering problems then this book is lacking.

Not enough methods in this book to constitute an introductory survey of the field. Every chapter gets heavy dose mathematical treatment, apparently Heath loves his math but for the rest of us it doesnt translate into know-how. Know how to solve equations using computational techniques. Very few derivations to back his mathematical swagger, very few examples (if any) and fewer numerical schemes to solve problems. Many of the chapters receive cursory treatment such as PDE's get about 70 pages of print. Far too little to do anyone any good.

He does talk about interesting issues such as conditioning and error analysis and computer precision and memory issues but it is done from such a superficial viewpoint that one cannot use anything to improve ones code. Not recommended if you want to learn numerical methods even if you have an excellent professor to learn from. His chapter on FFT's was even more abstruse and there was hardly any methods with which to solve PDE's.

I had this for a graduate course in Numerical Methods but ended up using Hoffman's excellent book on Numerical Methods.

Trash.......2005-10-14

If you want to have a solid understanding of numerical computation, this book is definitely the last choice. Many theorems are given without any proof or even intuitions behind them in this book. Even when a proof is provided, it's often far from rigorous. The organization of chapters is the worst I have ever seen, revelant materials are scattered over several different locations rather than put together. Take the SVD for example, it is mentioned in the end of chapter 3, but reappears in chapter 4, which is very confusing. If you are new to this area, please don't read this book. It gives you many many facts without explanations, which I think is not a good way to learn new things. David S. Watkins' Fundamentals of Matrix Computations is a lot better and easier to understand. It also emcompasses many detailed treatments of various theorems. If you have bought Heath's book, don't be sad, at least it can serve as a coaster.

Excellent Introduction, Sparse on Details.......2004-11-20

While sparse on the details of many of the algorithms and theorems mentioned, as an introduction it covers a broad range of material-enough for two semesters of study. The writing is lucid, and when a proof of a theorem is given, it is easy to follow and explained in english afterward. Rationale is given for everything, which is a great benefit to a student not familiar with the nuances of sophisticated linear algebra.

A Good Introductory Survey.......2002-11-05

This book excels at presenting a reader with little to no knowledge in computer science and a mild mathematical background (knowledge of differential equations as a prerequisite) with the fundamental concepts regarding scientific computing. The presentation of pseudo-code algorithms helps smooth the transition from analytical (pencil and paper) thinking to numerical thinking. The algorithms are presented in a manner such tha anyone with access to dozens of possible environments can apply them, though they are by no means complete, thus requiring some thought into the processes. The material covered is 110% of what an engineer will want to know, 90% of what an applied mathematician will want to know, and 45% of what a numerical analyist will want to know. In all, a great book to begin a foray into numerical computing.

Applied Optimization with MATLAB Programming

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worst ever!!!
How to learn and use MATLAB quickly!
Great self teaching tool

Applied Optimization with MATLAB Programming
P. Venkataraman
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

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ASIN: 0471349585

Book Description

A new approach to learning classical optimization methods-numerical techniques modeled and illustrated via MATLAB

This unique and timely volume combines a formal presentation of classical methods of design optimization with detailed instruction in the application of these methods using MATLAB. It introduces readers to the symbolic, numerical, and graphic features of MATLAB and integrates this powerful combination in the translation of many algorithms into applied optimization techniques with animation.

Applied Optimization with MATLAB® Programming develops all necessary mathematical concepts, illustrates abstract mathematical ideas of optimization using MATLAB's rich graphics features, and introduces new programming skills incrementally as optimization concepts are presented. This valuable learning tool:

Focuses on real-world optimization techniques
Covers all areas of optimization, including linear, nonlinear, discrete, and global
Includes creative examples from many disciplines
Presents a number of practical, open-ended design problems
Features an accompanying Web site with MATLAB code for all the numerical techniques and examples in the book

This one-of-a-kind resource enables senior-undergraduate and graduate students in engineering and other design disciplines to develop practical programming skills as they master the concepts of optimization. It is also an excellent self-teaching guide for design engineers in all fields of endeavor.

Customer Reviews:

worst ever!!!.......2004-01-29

I've had Dr. Venkat as a professor for 3 classes at RIT and he is by far the worst I have ever had. DO NOT BUY HIS BOOK! It will only make you dumber! That is how I feel after coming out of his class. I believe the reviewer that says the website is a main resource, he points us to the class site all the time with no helpful information, and because he can't answer the questions himself on the spot. Are you buying a book or a website? I think that's all the helpful information I have for now.

How to learn and use MATLAB quickly!.......2002-11-03

Excellent source for all people who don't have time to study MATLAB in-depth. A lot of useful examples help anyone to create his/her own code in no time!

Great self teaching tool.......2002-01-03

In this text the author chooses MATLAB as the tool in running computer-based optimization problems. This approach clearly covers all levels of optimization, and the book further supports this coverage through many helpful examples that balance theory with the application. The open-ended problems that are provided are a helpful mechanism for reinforcing the lessons of the text. The website that is a companion to the book, helped me access the reference links to the MATLAB software and the author's own personal site. This web site is a true lifeline to the book.

Nonlinear Programming: Theory and Algorithms

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Great Book for NLP (for the mathematically inclined only!)

Nonlinear Programming: Theory and Algorithms
Mokhtar S. Bazaraa , Hanif D. Sherali , and C. M. Shetty
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

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ASIN: 0471486000

Book Description

COMPREHENSIVE COVERAGE OF NONLINEAR PROGRAMMING THEORY AND ALGORITHMS, THOROUGHLY REVISED AND EXPANDED

Nonlinear Programming: Theory and Algorithms-now in an extensively updated Third Edition- addresses the problem of optimizing an objective function in the presence of equality and inequality constraints. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction.

Concentration on the three major parts of nonlinear programming is provided:
* Convex analysis with discussion of topological properties of convex sets, separation and support of convex sets, polyhedral sets, extreme points and extreme directions of polyhedral sets, and linear programming
* Optimality conditions and duality with coverage of the nature, interpretation, and value of the classical Fritz John (FJ) and the Karush-Kuhn-Tucker (KKT) optimality conditions; the interrelationships between various proposed constraint qualifications; and Lagrangian duality and saddle point optimality conditions
* Algorithms and their convergence, with a presentation of algorithms for solving both unconstrained and constrained nonlinear programming problems

Important features of the Third Edition include:
* New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more
* Updated discussion and new applications in each chapter
* Detailed numerical examples and graphical illustrations
* Essential coverage of modeling and formulating nonlinear programs
* Simple numerical problems
* Advanced theoretical exercises

The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques. The logical and self-contained format uniquely covers nonlinear programming techniques with a great depth of information and an abundance of valuable examples and illustrations that showcase the most current advances in nonlinear problems.

Customer Reviews:

Great Book for NLP (for the mathematically inclined only!).......1999-12-30

I am referring to the Bazaraa, Sherali and Shetty book "Nonlinear Programming, Theory and Applications", second edition (it seems that Amazon missed the third author).

This is a great book for anyone who is interested in nonlinear optimization. The book presents the topic in a clear and concise manner, provides learning aides in form of examples and generally has a very well structured layout. I have other books on NLP, but I consider this the best one (Luenberger is great, too - but very condensed). The book consists of three parts: the first part presents convex analysis, the second part looks at optimality conditions and the third part presents algorithms. If you went through some OR textbooks and felt that they didn't give you enough on NLP, this is the place to get your fix!

Book Description

The study of nonlinear dynamical systems has advanced tremendously in the last 15 years, making a big impact on science and technology. This book provides all the techniques and methods used in nonlinear dynamics. The concepts and underlying mathematics are discussed in detail.

The numerical and symbolic methods are implemented in C++, SymbolicC++ and Java. Object-oriented techniques are also applied. The book contains more than 100 ready-to-run programs.

The text has also been designed for a one-year course at both the junior and senior levels in nonlinear dynamics. The topics discussed in the book are part of e-learning and distance learning courses conducted by the International School for Scientific Computing.

Customer Reviews:

Good overview of nonlinear dynamics.......2005-11-15

This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools. The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented. If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs. Overall, I would highly recommend it as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible.

Helpful in some sections.......2001-09-01

The topics covered in this book are all important from the standpoint of applications in physics, engineering, computer science, financial engineering, and computational biology. It is written for the person just getting started in these topics, and the author does a fairly good job of discussing them. Readers should not expect, and they will not get, in-depth discussions on these topics, as this would swell the book to 10 times the size. They will however get preparation for moving on to more advanced and complete treatments.

Nonlinear and chaotic maps are considered in chapter 1, with elementary definitions given and six different examples of maps discussed. In discussing the calculation of numerical trajectories of maps, the author deals with the problem of large initial values for the maps and how to implement these in SymbolicC++ and Java. He also shows how to write/read data to a file using C, C++, and JAVA. The exception handling capability of JAVA comes out nicely, but no performance comparison between the three languages for simulating the maps is given by the author. The language REDUCE is used to discuss the stability of the fixed points of the logistic equation, but the code would be useless to the reader who did not have REDUCE since some of the function calls are hidden from the reader. Useful programs are given for calculating the Lyapunov and autocorrelation functions. In addition, C++ programs are given for evaluating the correlation integral for the Henon map. The programs he develops in this chapter can serve as a quick benchmark for one's own programs that calculate the same quantities.

In chapter 2, the author discusses methods for studying time series, including the Lyapunov and Hurst exponents. These two quantities are of enormous importance in the study of dynamical systems, financial data, and network performance. The C++ program that the author gives for calculating the Hurst exponent will not work for arbitrary time intervals. This is followed in the next chapter by a consideration of autonomous systems of ordinary differential equations. The classification of fixed points is considered, and the important concept of a homoclinic orbit. The author gives a nice JAVA program that finds the homoclinic orbit of an anharmonic differential equation using the Lie series technique. The phase portrait of the Van der Pol oscillator is calculated using the Runge-Kutta technique in a C++ program, along with the Lotka-Volterra system from mathematical biology.

Hamiltonian mechanics is discussed in chapter 4, with the important Henon-Heiles model from astrophysics is discussed and JAVA programs given for studying its behavior using the Poincare section technique. Newcomers to this technique will appreciate seeing it done here explicitly. Integrability of Hamiltonian systems using the Lax representation and Floquet theory are also treated, but only at a very rudimentary level. Dissipation is included in the next chapter, and the author discusses the classification of fixed points according to their stability. Lyapunov exponents are again brought into the picture, and the phenomenon of hyperchaos is discussed. Some bifurcation theory is introduced with an example of the Hopf bifurcation. Chapter 6 studies nonlinear driven systems, with the Duffing oscillator treated, and the author gives a useful program for calculating the autocorrelation function of this system. The controlling of chaos with feedback and non-feedback controls is the subject of the next chapter, mostly in the context of difference maps. Fractals finally get introduced in chapter 8, with iterated function systems defined but proofs of their properties omitted. The author gives programs for calculating various popular fractals, such as the dragon, Sierpinski gasket, Koch curve, the Mandelbrot set, and the Julia set. The main disappointment in this chapter is that the author does not give programs for calculating the Hausdorff dimension or capacity, quantities that are notoriously difficult to get a meaningful computational handle on.

The author switches gears in the next chapter and discusses cellular automata, which have recently made a comeback, especially in research on quantum computation. The discussion is too brief however, and does not allow the reader to gain an appreciation of the properties of these important objects. Chapter 10 gives a brief overview of some techniques for solving differential equations, such as the Euler method and the Lie series technique. The latter is not commonly treated in beginning books so its inclusion here is helpful. Symplectic integration is also discussed briefly, but the author does not discuss how to check the integrators using backward integration, which is commonly used in conservative systems modeled by symplectic maps.

Chapter 11, covering neural networks, is the most well-written in the book, and the newcomer to the field will get a fairly decent introduction to the subject. The supplied programs serve to illustrate some of the important concepts in neural networks, such as the Hopfield model, the Kohonen network, the perceptron learning algorithm, and the back-propagation algorithm.

Chapter 12 is an introduction to genetic algorithms, and I find this one particularly nice also, as it does give a rudimentary introduction to what evolutionary algorithms are all about, and gives some elementary genetic programs that find the maximum of one- and two-dimensional maps. He also discusses simulated annealing, and gives a useful program that allows the reader to see clearly how this technique works.

The last chapter covers fuzzy sets and fuzzy logic, which has also taken on importance in recent years, especially in data mining and financial engineering. The programs given to illustrate the concepts are particularly interesting from the standpoint of coding in C++, as the author uses friend functions and operating overloading in some of them. The reader gets a good overview of fuzzy reasoning and fuzzy rule-based systems.

Useful information, poor presentation.......2000-07-19

The information was useful & approprate to the topic. I'd rank it as an average quality refence but a very poor text book.

The text is poorly written. The code is simple and easy to understand, but not very object oriented. There is not enough explanation of the code. The code is not electronically available.

Book Description

The study of nonlinear dynamical systems has advanced tremendously in the last 20 years, making a big impact on science and technology. This book provides all the techniques and methods used in nonlinear dynamics. The concepts and underlying mathematics are discussed in detail.

The numerical and symbolic methods are implemented in C++, SymbolicC++ and Java. Object-oriented techniques are also applied. The book contains more than 150 ready-to-run programs.

Customer Reviews:

Exact same content as the cheaper and sturdy paperback version.......2007-07-20

Overall, this is a good book on the various subjects it covers, but I have to wonder - why would you buy this expensive hardcover version when the paperback version costs a little more than half what this hardcover costs? The contents are the same, the publication date is the same, and having had my softcover copy for two years and made heavy use of it, it seems to be standing up to the wear and tear just fine.

This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools.

The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented. If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs.

Overall, I would highly recommend this as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible.

explains many key ideas.......2005-12-08

Here is a text of advanced nonlinear dynamics. Geared towards the intensive use of computers to perform the necessary grungework. Steeb hits on many important ideas that have emerged in recent decades. He shows the interrelation between chaotic phenomena and fractals, and how fractals can be used to describe the onset to chaos.

The Hidden Markov Models have proved to be the key idea in current Automatic Speech Recognisers. A tribute to the practical nature of this idea.

Steeb's discussion of neural networks and genetic algorithms is enough to get you started in this field. Ideas like forward and back propagation for feedback are clearly explained.

The sample code should be welcomed. It lets you see for yourself on your own computer, and to tinker with the various parameters. Though I am unsure about the choice of code in Symbolic C++. Unlike C++ or Java, this is a rarely used language.

Nonlinear Assignment Problems: Algorithms and Applications (Combinatorial Optimization)

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Nonlinear Assignment Problems: Algorithms and Applications (Combinatorial Optimization)

Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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ASIN: 0792366468

Book Description

Nonlinear Assignment Problems (NAPs) are natural extensions of the classic Linear Assignment Problem, and despite the efforts of many researchers over the past three decades, they still remain some of the hardest combinatorial optimization problems to solve exactly. The purpose of this book is to provide in a single volume, major algorithmic aspects and applications of NAPs as contributed by leading international experts. The chapters included in this book are concerned with major applications and the latest algorithmic solution approaches for NAPs. Approximation algorithms, polyhedral methods, semidefinite programming approaches and heuristic procedures for NAPs are included, while applications of this problem class in the areas of multiple-target tracking in the context of military surveillance systems, of experimental high energy physics, and of parallel processing are presented. Audience: Researchers and graduate students in the areas of combinatorial optimization, mathematical programming, operations research, physics, and computer science.

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications (Nonconvex Optimization and Its Applications)

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Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming: Theory, Algorithms, Software, and Applications (Nonconvex Optimization and Its Applications)
M. Tawarmalani , and Nikolaos V. Sahinidis
Manufacturer: Springer
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Binding: Hardcover

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ASIN: 1402010311

Book Description

This book provides an insightful and comprehensive treatment of convexification and global optimization of continuous and mixed-integer nonlinear programs. Developed for students, researchers, and practitioners, the book covers theory, algorithms, software, and applications. This thought-provoking book:

-develops a powerful and widely-applicable framework for constructing closed-form expressions of convex envelopes of nonlinear functions;
-presents a systematic treatment of branch-and-bound, while providing acceleration mechanisms and enhancements;
-unifies ideas at the interface between operations research and computer science, devising efficient algorithmic implementation for global optimization; offers students, modelers, and algorithm developers a rich collection of models, applications, and numerical examples;
-elucidates through geometric interpretations the concepts discussed throughout the book; -shows how optimization theory can lead to breakthroughs in diverse application areas, including molecular design, process and product design, facility location, and supply chain design and operation;
-demonstrates that the BARON software developed by the authors can solve global optimization problems heretofore considered intractable, in an entirely automated manner on a personal computer.

Audience: This book will be of interest to researchers in operations research, management science, applied mathematics, computer science, computational chemistry, and all branches of engineering. In addition, the book can be used in graduate level courses in nonlinear optimization, integer programming, global optimization, convex analysis, applied mathematics, and engineering design.

Adaptive Multilevel Solution on Nonlinear arabolic PDE Systems

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Adaptive Multilevel Solution on Nonlinear arabolic PDE Systems
Jens Lang
Manufacturer: Springer
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Binding: Paperback

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ASIN: 3540679006
Release Date: 2007-05-25

Book Description

This book deals with the adaptive numerical solution of parabolic partial differential equations (PDEs) arising in many branches of applications. It illustrates the interlocking of numerical analysis, the design of an algorithm and the solution of practical problems. In particular, a combination of Rosenbrock-type one-step methods and multilevel finite elements is analysed. Implementation and efficiency issues are discussed. Special emphasis is put on the solution of real-life applications that arise in today's chemical industry, semiconductor-device fabrication and health care. The book is intended for graduate students and researchers who are either interested in the theoretical understanding of instationary PDE solvers or who want to develop computer codes for solving complex PDEs.

A Collection of Test Problems for Constrained Global Optimization Algorithms (Lecture Notes in Computer Science)

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A Collection of Test Problems for Constrained Global Optimization Algorithms (Lecture Notes in Computer Science)
Christodoulos A. Floudas , and Panos M. Pardalos
Manufacturer: Springer
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Constrained Global Optimization: Algorithms and Applications (Lecture Notes in Computer Science)

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Constrained Global Optimization: Algorithms and Applications (Lecture Notes in Computer Science)
Panos M. Pardalos , and J. B. Rosen
Manufacturer: Springer-Verlag
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ASIN: 0387180958

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