Introduction to Numerical Methods and MATLAB: Implementations and Applications

Book Description

From the Back Cover: The outstanding pedagogical features of this book are: o use of numerical experiments as a means of learning

why numerical methods work and how they fail; o a separate chapter reviewing the basics of applied

linear algebra, and how computations involving

matrices and vectors are naturally expressed in MATLAB; o use of a range of examples from those that provide a

succinct illustration of a basic algorithm, to those

that develop solutions to substantial problems in

engineering; o consistent use of well-documented and structured code

written in the MATLAB idiom; o a library of general purpose routines—-the NMM

Toolbox-—that are readily applied to new problems; o a progressive approach to algorithm development

leading the reader to an understanding of the more

sophisticated routines in the built-in MATLAB toolbox.

Customer Reviews:

Okay for a text.......2006-03-18

This book is okay for a text book, however there arent many examples, and the examples that are there are very simple. There are solutions for some problems online, though most of them are very basic and don't help very much.

Useful Book.......2004-08-28

This is a nice book for scientists and engineers. There are MATLAB programs already written that you can download from the webpage very easily, and modify for your specific use. I am no programmer, so having programs I can easily modify is a plus. This is meant to only be a review of linear algebra, so if you are trying to learn that subject, you will probably need to supplement this text with another book. This is not terribly in-depth on the MATLAB either. But it is a very useful handbook of plotting and interpolation methods, and how to choose the best methods for your particular set of data.

An Introduction to Genetic Algorithms (Complex Adaptive Systems)

Average customer rating:

Good Theoretical GA Textbook
Not for beginners
An introduction and much more
A Great Introduction to Genetic Algorithms
Good introduction for such a short book

An Introduction to Genetic Algorithms (Complex Adaptive Systems)
Melanie Mitchell
Manufacturer: The MIT Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0262631857

Book Description

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics--particularly in machine learning, scientific modeling, and artificial life--and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics.

Customer Reviews:

Good Theoretical GA Textbook.......2005-05-06

This book primarily deals with the theoretical side of genetic algorithms. If you are looking for practical knowledge of how to implement a GA you should look elsewhere. For all intents and purposes this is a textbook. It's heavy on theory and proofs, but doesn't always explain everything in depth (that's what class time is for). There are problems at the end of each chapter that can be assigned to students.

There are case studies of many academic projects that seem to drone on forever and aren't really that useful in helping you learn how to write your own GA. Chapter 1 gives an overview and provides all of the appropriate terminology. Chapter 5 gives an high-level overview of how to implement a GA. Those are the 2 must-read chapters, all of the others can be used as torture for CS students.

To recap, if you're teaching a class in artificial intelligence this book is good. If you're trying to figure out how to implement a GA to solve a practical problem not so good. That evens out to 3 stars for my rating. I recommend searching the web, there are a few good sites on GA programming.

Not for beginners.......2004-02-04

I have an engineering degree, and I found this to be a little tough to follow for two reasons:

1. Not enough step by step prodecure especially at the beginning. Mitchell is too quick to start with the math formulas. It turns out that Genetic Algorithms are fairly straight forward and easy to follow, but you have to read this book twice before you "get it" because Mitchell clouds the discussion with proofs and mathematical representations of systems. It is tough to follow.

2. Mitchell does a poor job of selecting meaningful examples to illustrate the points. A nice simple set of examples where the average person easily picture the system would have been delightful. Instead this author chooses to illustrate the Genetic Algorithms through uncommon neural networks amoung other exotic applications. I found myself struggling to understand both the example (I didn't know a thing about neural networks!) and the genetic algorithm.

When buying an Introduction type book, I expected it to be more 'down to earth'. this book is for advanced minds!

An introduction and much more.......2004-01-26

First it must be said that the book is not an introduction that the non-scientist will easily understand. Some knowledge of computer programming is assumed. It acknowledges this in the last paragraph of the preface. Many of the notations in the book are unfamiliar to business or financial readers. There is no mathematics beyond algebra so the aforementioned prerequisites are the main hills to climb.

Mitchell's book is an overview of genetic algorithm analysis techniques as of 1996. The author gives a history of pre-computer evolutionary strategies and a summary of John Holland's pioneering work. A description of the basic terminology is presented and examples of problems solved using a GA (such as the prisoner's dilemma). The second chapter discusses evolving programs in Lisp and cellular automata. Also included in this chapter is a discussion of predicting dynamical systems. This was the section that has the most interest for me. Also interesting was the summary in this chapter about putting GAs into a neural network so that the ANNs could evolve.

The fifth chapter discusses when to employ a GA for maximum success. I appreciate the clearly thought out discussion of when to choose a GA for a problem. Sometimes authors of these types of books mimic the man with a hammer that thinks everything looks like a nail.

A Great Introduction to Genetic Algorithms.......2002-12-07

This is a great place to start to learn about genetic algorithms. The writing is clear and not bogged down by jargon. The book is not overly technical; it is written for the layman and has a casual conversational style that is a pleasure to read.

About half of the book is devoted to presenting examples of studies that have used genetic algorithms. These examples are interesting in themselves and also serve to illustrate the variety of genetic approaches that are available. The book also presents conflicting points of view of experts about which algorithms work best and why. This is helpful in combatting the impression that a beginner sometimes gets that everything is simple and all the answers are known.

Good introduction for such a short book.......2002-04-07

Although short, this book gives a good introduction to genetic algorithms for those who are first entering the field and are looking for insight into the underlying mechanisms behind them. It was first published in 1995, and considerable work has been done in genetic algorithms since then, but it could still serve as an adequate introduction. Emphasizing the scientific and machine learning applications of genetic algorithms instead of applications to optimization and engineering, the book could serve well in an actual course on adaptive algorithms. The author includes excellent problem sets at the end of each chapter, these being divided up into "thought exercises" and "computer exercises", and in the latter she includes some challenge problems for the ambitious reader.

Chapter 1 is an overview of the main properties of genetic algorithms, along with a brief discussion of their history. The role of fitness landscapes and fitness functions is clearly outlined, and the author defines genetic algorithms as methods for searching fitness landscapes for highly fit strings. An elementary example of a genetic algorithm is given, and the author compares genetic algorithms with more traditional search methods. The author emphasizes the unique features of genetic algorithms that distinguish them from other search algorithms, namely the roles of parallel population-based search with stochastic selection of individuals, and crossover and mutation. A list of applications is given, and two explicit examples of applications are given that deal with the Prisoner's Dilemna and sorting networks. The author also gives a brief discussion as to how genetic algorithms work from a more mathematical standpoint, emphasizing the role of Holland schemas. The reader more prepared in mathematics can consult the references for more in-depth discussion.

The next chapter stresses the role of genetic algorithms in problem solving, beginning with a discussion of genetic programming. Automatic programming has long been a goal of computer scientists, and the author discusses the role of genetic programming in this area, particularly the work of John Koza on evolving LISP programs. In addition, she discusses the current work on evolving cellular automata and its role in automatic programming. The latter discussion is more detailed, this resulting from the author's personal involvement in artificial life research. Those interested in time series prediction tools will appreciate the discussion on the use of genetic algorithms to predict the behavior of dynamical systems, with an example given on predicting the behavior of the (chaotic) Mackey-Glass dynamical system. The author also gives applications of genetic algorithms in predicting protein structure, an area of application that has exploded in recent years, due to the importance of the proteome projects. The area of neural networks has also been influenced by genetic algorithms, and the author discusses how they have replaced the familiar back-propagation algorithm as a method to find the optimal weights.

Chapter 3 is more in line with what the author intended in the book, namely a discussion of the relevance of genetic algorithms to study the mechanisms behind natural selection. She discusses the "Baldwin effect", which gives a connection between what an organism has learned (a small time-scale process) to the evolutionary history of the Earth (a long time-scale process). A simple model of the Baldwin effect is given using a genetic algorithm, along with a discussion of the Ackley-Littman evolutionary reinforcement learning model, which involves the use of neural networks, and which is another computational demonstration of the Baldwin effect. In addition, the author discusses models for sexual selection and ecosystems based on genetic algorithms. These are the "artificial life" models that the author has been involved in, and she gives a very understandable overview of their properties.

Chapter 4 should suit the curiosity of the mathematician or computer scientist who wants to understand the theoretical justification behind the use of genetic algorithms. Again employing the Holland notion of schemas and adaptation as a "tension between exploration and exploitation", the author formulates a mathematical model, called the Two-Armed Bandit Problem, of how genetic algorithms are used to study the tradeoffs in this tension. The level of mathematics used here is very elementary with the emphasis placed on the intuition behind this model, with only a sketch of the model's solution given. To address the role of crossover in genetic algorithms, the author discusses in detail a class of fitness landscapes, called "Royal Road functions" that she and others have developed. The performance of the genetic algorithm employed is then compared against the three different hill-climbing methods. Formal mathematical models of genetic algorithms are also discussed, one of which involves dynamical systems, another using Markov chains, and one using the tools of statistical mechanics. The latter is very interesting from a physics standpoint but is only briefly sketched. The interested physicist reader can consult the references given by the author for further details.

Practical use of genetic algorithms demands an understanding of how to implement them, and the author does so in the last chapter of the book. She outlines some ideas on just when genetic algorithms should be used, and this is useful since a newcomer to the field may be tempted to view a genetic algorithm as merely a fancy Monte Carlo simulation. The most difficult part of using a genetic algorithm is how to encode the population, and the author discusses various ways to do this. She also details various "exotic" approaches to improving the performance of genetic algorithms, such as the "messy" genetic algorithms. One must also choose a selection method when employing genetic algorithms, and the author shows how to do this using various techniques, such as roulette wheel and stochastic universal sampling. In addition, genetic operators must also be chosen in implementing genetic algorithms, and the author emphasizes crossover and mutation for this purpose. Lastly, the values of the parameters of the genetic algorithm, such as population size, crossover rate, and mutation rate must be chosen. The author discusses various approaches to this. Although brief, she does give a large set of references for further reading.

Average customer rating:
Introduction to Computational Science: Modeling and Simulation for the Sciences
Angela B. Shiflet
Manufacturer: Princeton University Press
ProductGroup: Book
Binding: Hardcover

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A First Course in Scientific Computing: Symbolic, Graphic, and Numeric Modeling Using Maple, Java, Mathematica, and Fortran90

Chance in Biology: Using Probability to Explore Nature

Essential Mathematical Biology

Dynamic Models in Biology

The Structure and Dynamics of Networks: (Princeton Studies in Complexity)

ASIN: 0691125651

Book Description

Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum.

The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text.

Generic software approach in the text
Web site with tutorials and files in a variety of software packages
Engaging examples, exercises, and projects that explore science
Additional, substantial projects for students to develop individually or in teams
Consistent application of the modeling process
Quick review questions and answers
Projects for students to develop individually or in teams
Reference sections for most modules, as well as a glossary
Online instructor's manual with a test bank and solutions

Introduction to Probability Models, Eighth Edition

Average customer rating:

one of the best introduction to probability and stochastic processes
Why are there so many examples?
One of the most accessible and engaging text books I've read
very good
Good development of intuition, but not as good for other purposes...

Introduction to Probability Models, Eighth Edition
Sheldon M. Ross
Manufacturer: Academic Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0125980558

Book Description

Introduction to Probability Models, 8th Edition, continues to introduce and inspire readers to the art of applying probability theory to phenomena in fields such as engineering, computer science, management and actuarial science, the physical and social sciences, and operations research. Now revised and updated, this best-selling book retains its hallmark intuitive, lively writing style, captivating introduction to applications from diverse disciplines, and plentiful exercises and worked-out examples.

The 8th Edition includes five new sections and numerous new examples and exercises, many of which focus on strategies applicable in risk industries such as insurance or actuarial work.

The five new sections include:
* Section 3.6.4 presents an elementary approach, using only conditional expectation, for computing the expected time until a sequence of independent and identically distributed random variables produce a specified pattern.
* Section 3.6.5 derives an identity involving compound Poisson random variables and then uses it to obtain an elegant recursive formula for the probabilities of compound Poisson random variables whose incremental increases are nonnegative and integer valued
* Section 5.4.3 is concerned with a conditional Poisson process, a type of process that is widely applicable in the risk industries
* Section 7.10 presents a derivation of and a new characterization for the classical insurance ruin probability.
* Section 11.8 presents a simulation procedure known as coupling from the past; its use enables one to exactly generate the value of a random variable whose distribution is that of the stationary distribution of a given Markov chain, even in cases where the stationary distribution cannot itself be explicitly determined.

Other Academic Press books by Sheldon Ross:
Simulation 3rd Ed., ISBN:0-12-598053-1
Probability Models for Computer Science, ISBN 0-12-598051-5
Introduction to Probability and Statistics for Engineers and Scientists, 2nd Ed., ISBN: 0-12-598472-3

* Classic text by best-selling author
* Continues the tradition of expository excellence
* Contains compulsory material for Exam 3 of the
Society of Actuaries

Customer Reviews:

one of the best introduction to probability and stochastic processes.......2007-08-20

Understanding probability requires various resources to read. I think this book is one of the irreplaceable element in these resources. It is an introduction book as the name implies. Examples are illuminating the subject very well.

Why are there so many examples?.......2007-04-01

Extremely difficult to dig through the excessive examples in order to find the relevant theorems and results. Because of this, the problems at the end of each chapter become exercises in tedium, as more time is spent searching for the necessary theorems in the text than in actually working out the solution.

I do not recommend.

One of the most accessible and engaging text books I've read.......2007-02-16

During my undergraduate career I've had the opportunity to spend several thousand dollars on textbooks--many of which have pertained to mathematics in some way. Most of these books, including those concerned with statistics and probability, have been interested in either delivering pure theory or an unending supply of problem sets (with little or nothing in the way of instructive content). Thankfully Ross's book defies these conventions.

By presenting the material in large sets of well explained and genuinely interesting problems, the book avoids being bogged down by excessive theory or volumes of sterile exercises. As a result, the book is unusually easy to read, and quite useful when it comes to clarifying or augmenting what has been taught in class.

very good.......2006-11-14

I used this book for a graduate-level course in Stochastic Processes taught by Dr. Sheldon Ross himself. I must say that I never liked probability and stochastics until I read this book. Reading it is a pleasure! The topics are presented in a highly methodical manner, with plenty of examples and exercises. The exercises are presented in a gradation. Covers a wide range of topics, and is very helpful for a course in stochastics, especially for a student who doesn't have a strong background in P & SP. This is the book to own, don't miss it!

Good development of intuition, but not as good for other purposes..........2006-09-28

I have many of the same criticisms of this book that I do of Ross's book titled: "Probability: a first course". This book reviews most of the material from that book at a faster pace and then goes into other topics. Ross in the introduction states that his main goal in this text is to develop the reader's intuition for probabilistic reasoning. This book is excellent towards acheiving this goal, but not very good for anything else. It is a very "pure" probability text, completely ignoring the fact that the field of statistics exists and is useful. At the same time, it is somewhat weak on theory. Measure theory isn't mentioned, and the emphasis overall is on computation and problem solving, not proving theorems and understanding theoretical connections between different ideas.

This book has too many examples and not enough discussion. While the examples are usually well-executed, and while I think examples are important in probability, I think it's also important to talk about the abstract development of the subject. In my opinion, more prose and fewer examples would improve the quality of this text.

Another criticism I have of this book is that this book focuses exclusively on probability, refusing to touch statistics even with a ten foot pole. While this in itself is fine, I think this book misses numerous chances to pave the road towards the later study of mathematical statistics. The result is that someone reading this book will not be particularly well prepared for studying statistics, even though the fields of probability and statistics are intimately tied to each other.

Lastly, this book has gone through too many editions--one of the reasons I rated it 3 stars instead of 4 is that I believe that there has been almost no noticeable improvement in the last two editions (I have not read any farther back than that so I can't say more). I think this is a money-making scheme on behalf of the publisher, and I think this reflects poorly on the author and publisher alike.

Chemical Engineering Dynamics: An Introduction to Modelling and Computer Simulation

Average customer rating:

Chemical Engineering Dynamics: An Introduction to Modelling and Computer Simulation
John Ingham , Irving J. Dunn , Elmar Heinzle , Jiri E. Prenosil , and Jonathan B. Snape
Manufacturer: Wiley-VCH
ProductGroup: Book
Binding: Hardcover

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ASIN: 3527316787

Book Description

In Chemical Engineering Dynamics, the modelling of dynamic chemical engineering processes is presented in a highly understandable way using the unique combination of simplified fundamental theory and direct hands-on computer simulation. The mathematics is kept to a minimum, and yet the nearly 100 examples supplied on a CD-ROM illustrate almost every aspect of chemical engineering science. Each example is described in detail, including the model equations. They are written in the modern user-friendly simulation language Berkeley Madonna, which can be run on both Windows PC and Power-Macintosh computers.

Madonna solves models comprising many ordinary differential equations using very simple programming, including arrays. It is so powerful that the model parameters may be defined as "sliders", which allow the effect of their change on the model behavior to be seen almost immediately. Data may be included for curve fitting, and sensitivity or multiple runs may be performed. The results can be seen simultaneously on multiple-graph windows or by using overlays. The resultant learning effect of this is tremendous. The examples can be varied to fit any real situation, and the suggested exercises provide practical guidance.

The extensive experience of the authors, both in university teaching and international courses, is reflected in this well-balanced presentation, which is suitable for the teacher, the student, the chemist or the engineer. This book provides a greater understanding of the formulation and use of mass and energy balances for chemical engineering, in a most stimulating manner.

Book Description

This book describes the Property Specification Language PSL, recently standardized as IEEE Std 1850-2005. PSL was specifically developed to fulfill the following requirements:
- easy to learn, write, and read
- concise syntax
- rigorously well-defined formal semantics
- expressive power, permitting the specification for a large class of real world design properties
- known efficient underlying algorithms in simulation, as well as formal verification

This book is primarily targeted to hardware designers and verification engineers who plan to use PSL. It presents PSL using extensive examples in the form of timing diagrams and associated PSL properties. In addition to language elements, it touches on methodological issues in the use of PSL. While primarily oriented to users of PSL for simulation, formal verification is addressed as well. All the basic features of the language are covered, as well as advanced topics such as the use of PSL in multiply-clocked designs and the issue of embedding asynchronous properties in synchronous ones. One chapter is devoted to errors commonly made by begi nners gathered through the authors' many years of experience in using and teaching the language, and will be helpful to both beginners and more experienced users.

The book is accessible to the typical hardware designer and verification engineer with no interest in the theory behind temporal logic. However, the formal semantics are included as an appendix, so that those with such an interest will be able to refer to them.

From the Foreword:
… "Cindy Eisner and Dana Fisman were the two key people who turned IBM Sugar into PSL. Their deep understanding of PSL’s formal semantics was instrumental in both the Accellera and IEEE PSL standardization efforts. Cindy and Dana have now created the most authoritative source for information about PSL, designed to introduce the language incrementally in an easily understood fashion. A Practical Introduction to PSL provides a solid foundation for getting started with PSL today."

Harry Foster - Erich Marschner

Mentor Graphics Corporation Cadence Design Systems

Customer Reviews:

Required reading for anyone involved in verification!.......2006-11-13

For all design or verification engineers interested in the emerging field of assertion-based verification (ABV), you will want to own Cindy Eisner and Dana Fisman's excellent book: A Practical Introduction to PSL. For those who are new to PSL, you will find that this book incrementally introduces the language in an easy-to-understand fashion. Each chapter is chock-full of practical examples, complete with waveforms to visually aid an understanding of the properties. For the expert, you will find that this book is an excellent reference. For readers from beginner to expert, the chapter on Common Errors clarifies often misunderstood concepts, and it will set you in the right direction for successfully applying PSL.

This book should be part of any serious engineer's personal library.

Harry Foster

Co-author--Assertion-Based Design, Applied Formal Verification, Principles of Verifiable RTL Design

Understanding the Light Microscope: A Computer-Aided Introduction (With CD-ROM)

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Understanding the Light Microscope: A Computer-Aided Introduction (With CD-ROM)
D. J. Goldstein
Manufacturer: Academic Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0122886607

Book Description

Understanding the Light Microscope consists of four original computer programs with an explanatory book. Author Dan Goldstein says using the programs can teach aspects of microscopy and diffraction often missed from formal courses, adding, "... what one non-mathematician has created should not be beyond the understanding of others!" The book aims to provide understanding at a level deeper than customary in existing texts and in a form accessible to microscope users, particularly biologists. It covers simple ray optics, the aberrations of "real" (thick) lenses, polarized light, and the influence of diffraction on imaging. The book can be read alone, but appreciation of its contents is greatly enhanced when used in conjunction with the programs.
D J Goldstein was a Nuffield Dominion Travelling Fellow at Oxford University and a visiting Professor in Pittsburgh. He taught at the Universities of the Witwatersrand (Johannesburg, South Africa) and Sheffield (UK) while publishing research in embryology, histology, immunology, histochemistry and microscopy. Since retiring in 1989 as Reader in Anatomy at Sheffield University, he has been an independent research worker in biomedical science.

Key Features
* Aids insight into microscope operation and imitations
* The approach is non-mathematical, yet in-depth
* Enables lecture time to be replaced by learning assignments
* Includes a help function for all four programs
* The programs have been tried and tested by 2nd and 3rd year biomedical undergraduates

An Introduction to Computer Simulation Methods: Applications to Physical Systems (3rd Edition)

Average customer rating:

Pretty good introductory book
very good introductory computational physics book
Makes Physics a pleasure

An Introduction to Computer Simulation Methods: Applications to Physical Systems (3rd Edition)
Harvey Gould , Jan Tobochnik , and Wolfgang Christian
Manufacturer: Addison Wesley
ProductGroup: Book
Binding: Paperback

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ASIN: 0805377581

Book Description

KEY BENEFIT: Now in its third edition, this book teaches physical concepts using computer simulations. The text incorporates object-oriented programming techniques and encourages readers to develop good programming habits in the context of doing physics. Designed for readers at all levels , An Introduction to Computer Simulation Methods uses Java, currently the most popular programming language. Introduction, Tools for Doing Simulations, Simulating Particle Motion, Oscillatory Systems, Few-Body Problems: The Motion of the Planets, The Chaotic Motion of Dynamical Systems, Random Processes, The Dynamics of Many Particle Systems, Normal Modes and Waves, Electrodynamics, Numerical and Monte Carlo Methods, Percolation, Fractals and Kinetic Growth Models, Complex Systems, Monte Carlo Simulations of Thermal Systems, Quantum Systems, Visualization and Rigid Body Dynamics, Seeing in Special and General Relativity, Epilogue: The Unity of Physics For all readers interested in developing programming habits in the context of doing physics.

Customer Reviews:

Pretty good introductory book.......2005-10-19

Good introductory book on Computational Physics.
Projects proposed cover different difficulties so it can be used for college students at all levels.Concepts are well explainded. Introduces areas including linear and nonlinear systems, normal modes and waves, and electrodynamics. This second edition offers expanded material on chaos, complexity, and quantum mechanics, programs with more use of graphics, and appendices on Fortran and C.

very good introductory computational physics book.......2005-04-28

This was my first comp. physics book and it was easy and
very instructive. I can assure your money is well spent.
If you find this book too easy, then you should move on to
Thijssen's Computational Physics which is intended for the
`graduate' level readers.
Only 4 stars (not 5) because I don't think that the codes
provided in the book are that useful. Everyone has different
coding style. What really matters is the physical concepts and
not the numerical receipes.

Makes Physics a pleasure.......2004-04-19

Excellent, outstanding book for clarity, elegance, writing style and level of detail. This book won't leave you alone on the intricacies of marrying physics and computer programming and will make your programming activity more intereesting if you are more of a programmer and you physical studies more rewarding and less
"pen-and-paperlike" if you are an aspiring physicist. In fact I highly recommend this book to anyone that has an interest in how nature works and in playing with computers. The extreme clarity of this book makes it accessible to junior colege students and even to advanced, motivated high school students or for self study. I would have preferred to see the example code in the book
in C or better C++ but using BASIC has the advantage of making the book more esy to read and is just sligtly annoying for the
C++ or Java programmer. ( Are there any other kind of real programmers? ;) Just make sure you master your language enough to make calculations, use functions, and are able to produce at least some basic graphics (using C++ and openGL or DirectX would rock). Judge by yourself, but I would buy without a thought a book whose first chapter is on the "Coffe Cooling Problem".

Creating Computer Simulation Systems: An Introduction to the High Level Architecture (Book only)

Average customer rating:

Best book on HLA available
Superficial
Ok, but could be better.
Recommended, so far
Will do the job in the absence of alternatives

Creating Computer Simulation Systems: An Introduction to the High Level Architecture (Book only)
Frederick Kuhl , Richard Weatherly , and Judith Dahmann
Manufacturer: Prentice Hall PTR
ProductGroup: Book
Binding: Paperback

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ASIN: 0130225118

Amazon.com

As simulations become increasingly important in nearly all aspects of life, we're finding that combining existing systems is much more efficient than building newer, more complex replacements. Whether your interest is in business, the military, or entertainment or is even more general, Creating Computer Simulation Systems: An Introduction to the High Level Architecture will show you how to use the new standard for building and integrating modular simulation components and systems.

The HLA, adopted by the U.S. Department of Defense, has been years in the making and recently has shot out ahead of its competitors to grab the attention of engineers and designers worldwide. The book contains an overview of the rationale and development of the HLA; an extended, integrated tutorial that demonstrates its power and applicability to real-world problems; advanced topics and exercises; and well-thought-out programming examples.

The book's organization and design are top-notch--the chapters are nearly as modular as the systems they explore, though the meat of the book runs the reader through an extended set of problems focusing on the same model. Designed more as a guide than a reference, it is still well-indexed and a must for managers, technicians, programmers, and anyone else working on building simulations. --Rob Lightner

Customer Reviews:

Best book on HLA available.......2006-05-02

I think most of the negative reviews are actually against HLA and due to a lack of experience with component-based simulation system development ... not the book itself.

With the lack of resources out there, I really appreciate this resource.

I've just begun to read the book and find it very easily read. I'll post another review as I progress.

Superficial.......2006-03-27

To paraphrase Douglas Adams, it is very easy to be blinded to the essential uselessness of the HLA by the sense of achievement you get from getting the RTI to work at all. In other words -- and this is the rock solid principal on which the whole of the DMSO's DoD-wide success is founded -- their fundamental design flaws are hidden by their superficial design flaws. This book covers in detail all of the HLA's superficial design flaws while omitting coverage of the fundamental design flaws. Thus, give it a miss.

Ok, but could be better........2003-02-26

This book covers a lot of the basics of what HLA is but contains holes. After reading this book three times I am still left with questions as to how to implement HLA in an application. I [...] still have unanswered questions as to how to implement the HLA. The examples in the book are implemented in Java [...] however I would have been happier if the examples were implemented in C++ as well. This is a good starting point, in the absence of alternatives, but could be better.

Recommended, so far.......2002-10-08

I am at the mid-point of the book and will likely post another review when I am done. [...] The authors give the history and motivation and design decisions behind HLA. They also give many good examples, [...], allow you to get a really good feel for the important concepts of HLA by running an actual federation. One thing I will be looking for is the impact of the architecture on simulation performance, scalability in practice (as opposed to in theory), and how is HLA likely to evolve over the next couple decades.
I don't know yet whether the book is enough for you to create your first federation. If you really have NO background at all in simulation, you will still get a lot out of the first couple of chapters, plus the many references to articles written on the subject, but don't expect to find the other chapters easy. Using my background in simulation systems, I can say that HLA seems to have been very well thought out, based on real-life simulation systems, and is therefore not trivial. But that's what makes it interesting, and the book so far lives up to that.

Will do the job in the absence of alternatives.......2002-09-25

Agree with the reviewer about "pompous computer speak", and that the real info could be presented in about 10 pages. I have far too many docs that I need to wade through. The published IEEE standards are always available if you're having insomnia. BUT, with some motivation to get through this book, I was able to accomplish my objective: get a feel for the HLA. [...] Next I'll try the Singhal/Zyda book that another reviewer suggested.

Computational Chemistry: Introduction to the Theory and Applications of Molecular and Quantum Mechanics

Average customer rating:

Very good first intro to computational chemistry
Rough reading

Computational Chemistry: Introduction to the Theory and Applications of Molecular and Quantum Mechanics
Errol G. Lewars
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback

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ASIN: 1402074220

Book Description

Computational chemistry has become extremely important in the last decade, being widely used in academic and industrial research. Yet there have been few books designed to teach the subject to nonspecialists.
Computational Chemistry: Introduction to the Theory and Applications of Molecular and Quantum Mechanics is an invaluable tool for teaching and researchers alike. The book provides an overview of the field, explains the basic underlying theory at a meaningful level that is not beyond beginners, and it gives numerous comparisons of different methods with one another and with experiment.
The following concepts are illustrated and their possibilities and limitations are given:

- potential energy surfaces;
- simple and extended Hückel methods;
- ab initio, AM1 and related semiempirical methods;
- density functional theory (DFT).

Topics are placed in a historical context, adding interest to them and removing much of their apparently arbitrary aspect. The large number of references, to all significant topics mentioned, should make this book useful not only to undergraduates but also to graduate students and academic and industrial researchers.

Customer Reviews:

Very good first intro to computational chemistry.......2004-08-28

The only other book I can compare this to is Cramer's, and this one is better suited to a first introduction into computatioal chemistry. I have taken one graduate quantum chemistry course, and this was more than enough background for understanding this book. This is the only text I know of (I asked my comp chem prof if he knew of any others) that walks through a Hartree Fock calculation step by step using an example. There are some mistakes in the formulas, but they are quite minor. All in all, I would recommend this book to anybody interested in beginning to learn about computational chemistry.

Rough reading.......2004-05-12

Maybe there just isn't any way into the basics of modern computational chemistry.

Lewars introduces the easy parts in a clear enough way. Potential energy surfaces make sense. Molecular mechanics has a good, intuitive feel - it's the springs-and-balls model, elaborated to include plane and dihedral angles, representing force fields derived from other sources.

After that (i.e., after p. 80), it's quantum mechanics for a few hundred pages. The premise is that the layout of electrons across a molecule determines its chemistry, and that the wave function tells where the electrons will be. Since the wave equations can't be solved exactly for anything with two or more electrons (!), it's actually approximations to quantum. That leads to two levels of opacity: quantum itself, and all the facts that were scraped off in the approximation process. At this point, the chice is binary: become fluent in quantum, or move on. There are a few nuggets to be had for the non-fluent, including some of the techniques for solving these horrendous integrals. Mostly, though, I moved on.

After the "ab initio" quantum mechanical methods, Lewars presents the semi-empirical models. These deal with simplified models of wave functions. Unlike ab initio methods, which stand on almost purely theoretical models, semi-empirical methods are informed by experimental data. They are based on the electron wave functions, as are the ab initio methods, but use approximations calibrated by experimental results. The book's final section presents density functional theory (DFT), another technique for estimating where the electrons will be.

This book demands a lot of the reader, more than I came in with or had time to develop. I was able to use it to get a working vocabulary of the major kinds of computations, the general categories of approach to modeling, and a rough idea of the techniques and complexities involved. I need a little more information than that, but not the immediate leap into the deep end presented here.

I look forward to a review by someone more knowledgeable. For now, my only real criticism of this book is lack of glossary. Initialisms and acronyms abound. It would have made the going a lot easier if the book had one place where I could refresh my memory on the dozens or hundreds of abbreviations.

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