Book Description
Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own.
The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction.
Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists.
- A how-to guide for developing new mathematical models in biology
- Provides step-by-step recipes for constructing and analyzing models
- Interesting biological applications
- Explores classical models in ecology and evolution
- Questions at the end of every chapter
- Primers cover important mathematical topics
- Exercises with answers
- Appendixes summarize useful rules
- Labs and advanced material available
Book Description
Risk Analysis A Quantitative Guide Risk and uncertainty are key features of most business and government problems and need to be understood for rational decisions to be made. This book concerns itself with the quantification of risk, the modelling of identified risks and how to make decisions from those models. Following on from the success of the previous edition of this clearly written and highly regarded book, this edition is extensively revised and updated and will provide an invaluable practical guide for beginners and experienced practitioners alike. Quantitative risk analysis (QRA) using Monte Carlo simulation offers a powerful and precise method for dealing with the uncertainty and variability of a problem. By providing the building blocks the author guides the reader through the necessary steps to produce an accurate risk analysis model and offers general and specific techniques to cope with most modelling problems. A wide range of solved problems is used to illustrate these techniques and how they can be used together to solve otherwise complex problems. Reviews of the first edition "It identifies the various facets of risk analysis and provides a valuable reference to the concepts and techniques employed." Project, 1997 "It clearly explains many essential aspects of quantitative risk analysis . provides valuable techniques and sound professional advice." Journal of Behavioral Decision Making, Vol. 12, 1999 "The book offers a powerful method for dealing with risk and uncertainty." Zentralblatt für Mathematik, Band 908, 1999
Customer Reviews:
Risk Analysis.......2006-05-24
A very good book, but a bit too much mathematical detail in deriving formulas for probability distributions; could use better descriptions of when to use each probability distribution.
Best Book for Quantitative Risk Analysis.......2004-04-25
I believe that this book is the best of many Risk Analysis books. The book's structure, starting from fundamental topics and guiding to advanced topics, is excellent. So, I translated this book into Japanese! You will make the best use of the book with Excel add-in Monte Carlo simulation software like @Risk and Crystal ball that you can get its trial version from the vendor's site(free!). But, the value of this book is not decreased with its sophistitated notation even if you don't have such software. You can enjoy the logic of Quantitative Risk Analysis. Now, the author is preparing his original software. I hope it will be as valuable as this book.
1st edition more useful to a practitioner than the 2nd.......2003-10-18
Unlike in the first edition, the author seems to have tried his best to eliminate any reference to any simulation software in the second edition. Result: it now reads like any academic simulation text, only less. The first edition wasn't broke. Why fix it? Bring back the classic Vose!
Rigouros, clear and practical.......2003-04-20
This book gives a deep insight into the state of the art and recent developments of quantitative risk analysis using simulation methods. Describes topics such as second order risk analysis I never heard about before. I used the knowledge drawn from this book to write some technical papers (published on peer-reviewed journals and seminars proceedings). Specialized software, such as @-risk and crystal ball is not strictly needed to carry out the risk-analysis systems suggested by the author (but pretty advanced skills with excel or use of math softwares are required). The specific subject of the book is risk modelling by Monte Carlo Simulation and Bayesan analysis; it does not deal with fuzzy models or other uncertainty-propagation methods. I highly reccomend this book to anyone interested into the specific subject.
Risk Analysis: A Quantitative Guide.......2001-08-25
I purchased this book to learn to write simulation equations in excel but only found it was a manual ( type book ) with good information for a very expensive software I did not have....If you have RISK software, it is a great book to have... I returned my copy w/o scanning the entire book.
Book Description
Over the last several decades, mathematical models have become central to the study of social evolution, both in biology and the social sciences. But students in these disciplines often seriously lack the tools to understand them. A primer on behavioral modeling that includes both mathematics and evolutionary theory, Mathematical Models of Social Evolution aims to make the student and professional researcher in biology and the social sciences fully conversant in the language of the field.
Teaching biological concepts from which models can be developed, Richard McElreath and Robert Boyd introduce readers to many of the typical mathematical tools that are used to analyze evolutionary models and end each chapter with a set of problems that draw upon these techniques. Mathematical Models of Social Evolution equips behaviorists and evolutionary biologists with the mathematical knowledge to truly understand the models on which their research depends. Ultimately, McElreath and Boyd’s goal is to impart the fundamental concepts that underlie modern biological understandings of the evolution of behavior so that readers will be able to more fully appreciate journal articles and scientific literature, and start building models of their own.
Customer Reviews:
Excellent addition to cultural evolution.......2007-09-27
For a mathematically-challenged individual and a novice to cultural evolution, the models explained were tough but the explanations of each were invaluable in providing an understanding of the social world, particularly conflict and cooperation. Strongly recommended to those interested in learning more about social and cultural evolution.
Wonderful Hands-On Guide to the Math of Cultural Evolution!.......2007-05-02
This concise book will allow any mathematically competent but sociobiologically inexperienced reader to dive right into the debates about human evolution. Although the many of the models described in McElreath and Boyd's Guide for the Perplexed come from evolutionary biology and were conceived as genetic models, a great deal of them apply without alteration to related processes in the social world. Take the prisoners dilemma, the battle of the sexes, the Price Equation, or the Phillip Sidney game, honest signaling, and social learning. Everything inside has direct bearing on how we should understand the evolution of social systems, it's just that the *math* has already been worked out by others in the biological sciences.
The social sciences have much to gain from game theory, and this book is a concise, complete and speedy primer.
A fantastic introduction to theoretical sociobiology.......2007-04-10
This book provides a thorough, lucid and near-complete guide to the theories used by sociobiologists like no book has achieved before it. As a working biologist, I strongly recommend it to those interested in why animals and indeed all organisms cooperate, or conflict.
Perplexing indeed.......2007-04-08
The mismatch between title and content is perplexing enough: the book is a summary of biological and game-theoretical modeling that has been done and more competently described by others decades ago. These models have little, if any, connection to what one would consider as "social evolution." The words "society" or "social" do not even appear in the index. The index term closest to the equally absent "culture" is "covariance genetics." Welcome to social evolution!
Even more perplexing: why should a reader perplexed by society be guided away from society and into genetics by, of all people, two anthropologists?
Book Description
Beginning Algorithms
A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks.
Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development.
What you will learn from this book
- The basics of algorithms, such as iteration and recursion
- Elementary data structures such as lists, stacks, and queues
- Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort
- Advanced data structures such as binary trees, ternary trees, and heaps
- Algorithms for string searching, string matching, hashing, and computational geometry
- How to use test-driven development techniques to ensure your code works as intended
- How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization
Who this book is for
This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial.
Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.
Download Description
Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. What you will learn from this book The basics of algorithms, such as iteration and recursion Elementary data structures such as lists, stacks, and queues Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort Advanced data structures such as binary trees, ternary trees, and heaps Algorithms for string searching, string matching, hashing, and computational geometry How to use test-driven development techniques to ensure your code works as intended How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization Who this book is for This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.
Customer Reviews:
An unnecessary blend of topics.......2007-05-09
While the basic data structure and algorithm content is fine, the "marriage" of test driven development/JUnit and DS&A is completely unnecessary and, to my mind, seriously damages this book. There's nothing wrong with test driven development and there's nothing wrong with JUnit. But to suggest that it's necessary to force the two together (ad nauseum!) for every single structure is just false. Really, after the first one or two test cases the JUnit stuff gets really tired and it should be obvious to the reader how to continue on with it. This is much like introductory OOD texts trying to munge software engineering principles throughout. A better title for this text would be "A Test Drive Approach to Beginning Algorithms with Java and JUnit". There are those who agree with the Beck Test Driven Development, there are those who disagree. But a linked list is a linked list. At this level, the important material consists of the basic data structures, the algorithms which manipulate them, recursion and some sense of when to choose which structure/algorithm. This material, in my opinion, should be concentrated on without the unit testing - leave unit testing to a text covering general programming best practices. A much better choice for an intro to DS&A in Java is Robert Lafore's "Data Structures and Algorithms in Java".
WARNING.......2007-01-31
The title of the book is 'Beginning Algorithms' and as such should cover the basics. It would be nice if a book on algorithms actually contained detail explanations regarding the particular structure that is going to be discussed or constructed. This book does not do that and hence does an injustice to the beginner or someone wishing to move from some text describing the how-to of programming in a given language to a detailed understanding of fundamental programming paradigms. Moreover, the title should read loosely defined algorithms JUnit tested beyond belief. It is pedagogically unsound to write a beginning book on algorithms whose emphasis is on testing the structures being built and not on accurately defining and motivating the assumed subject matter. For example, a link list or any of it's other incarnations is a structure that every soo-to-be programmer or computer scientist should know of and be able to effortlessly construct. The authors of this book give you a whopping one page description of a doubly linked list with a neat diagram and then go off on their rather annoying tangent of building the JUnit testing for the class or classes they are trying to build. Only after they give you the doce for testing-wasting several pages and minutes of your time-do they begin to construct the linked list. What's even worse than the needless discussion revolving testing (that should come after the object is defined and constructed) is the fact that they do absolutely no justice to the linked list or any other structure for that matter. It's just code with little if any text to motivate of define what hasa been built, why it has been built, where it may apply, how it might be applied or how it relates to, say, some of the fundamental types written as part of the Java core. Hopefully if this book is allowed to be reprinted the author's will do the computer science community and, in particular, its readership justice by never mentioning testing and instead fill those pages with thought provoking ideas that actually pertain to algorithm design. For those of you just starting out in programming and who are looking to move on into data structures and algorithm design and analysis please be warned that this text is not a wise choice and, in fact, this text is not a wise choice for any person above the novel reader interested in applying JUnit testing to fundamental data structures. Just be warned, buy something different and happy programming.
Excellent on the basics and coding style, superficial on advanced or unusual subjects.......2007-01-24
If you are a self-taught programmer who has never taken a class in data structures and algorithms, or has done so but not really got it, this book could be a good read. It presents in a gentle, very tutorial-like, example-driven fashion the basics of this field, Lists, Sets, Maps, Trees, Hashing, Sorting & Searching and a little material on more unusual topics like String searching and matching and computational geometry. This last part however does not maintain the very good standards of the first part of the book. The treatment is too superficial and vague and little mistakes and confusion starts to creep in. The main body of the book anyways is really well written and clear. As an bonus, the authors use a test driven approach to developing their Java code giving you a chance to appreciate this very useful practice of extreme programmming and agile methodologies. The code itself is crystal clear and shows the principles of good coding and refactoring (other pillars of extreme programming): short reusable functions, few local variables and meaningful names.
The end result is so good that the "how it works" sections who are meant to explain the code are almost always unnecessary.
So this book can also be useful in teaching you how to write in a clear and elegant style. Final words, if you are looking for something that will introduce you to mathematical analysis of algorithms and their efficiency look elsewhere as this title contains none of that.
Important to have around for a couple of reasons..........2005-12-10
It's pretty easy these days to use a programming language and the high level of abstraction it can offer to avoid understanding certain programming fundamentals like lists, queues, and stacks. It's for sure that I've gotten away with it. But if you're just starting out in programming (or if you're trying to fill in some gaps), you might be interested in Beginning Algorithms by Simon Harris and James Ross. They do a nice job of making a complex subject approachable...
Contents: Getting Started; Iteration and Recursion; Lists; Queues; Stacks; Basic Sorting; Advanced Sorting; Priority Queues; Binary Searching and Insertion; Binary Search Trees; Hashing; Sets; Maps; Ternary Search Trees; B-Trees; String Searching; String Matching; Computational Geometry; Pragmatic Optimization; Further Reading; Resources; Bibliography; Answers to Exercises; Index
Harris and Ross take you through the basic programming algorithms using Java as the base language. Rather than just tell you "use this Java class to do a Hash", they explain the underlying concept and then have you build an implementation of that concept in code. After you've taken the time to write the methods and classes by hand, you'll end up with a pretty complete understanding of that algorithm in a way that just using provided classes can't offer. Another commendable point in this book is that they start off each algorithm coding exercise by building unit tests first. That way, you can be assured that the code you write does everything it's supposed to do, and further tweaks to improve the logic don't lead to the introduction of bugs. Very solid approach...
I will end up keeping this book around for a couple of purposes. First, I'm sure to end up referring to it when I need to understand a certain fundamental like Soundex or searching. I'll get more out of this book and it's focus on practicality than I would out of some academic treatise on the subject. And second, if I have to code something related to one of these algorithms, I'll have some good example code to pull from. Can't ask much more from a book than that...
If this is a weak point in your programming portfolio, getting a copy of this book to study and reference would be a good investment in your career.
the book's examples are in Java.......2005-11-13
Neither the front or back cover says this, so I will. The source code examples in this book are all written in Java. I suspect the book is being a little coy about this because the authors want to maximise the potential audience. Fair enough. Granted, the text mentions Java immediately inside, but you have to actually open a physical copy, to see this.
If you are already conversant in Java, that's great, because the book offers an indepth guide to several crucial classes. But what if you program in C++ or C#? In the Standard Template Library for C++ and in the default libraries for C#, you should be able to easily find the equivalent classes to those used in the text. Of course, you will then have to rewrite the examples that use those classes. Straightforward. None of the examples are long. And since this book is fundamentally about computations, and not about making a user interface, the syntax for using the system classes is roughly the same, across these languages. Also, some examples might use the object oriented property of extending a base class. As you can do this in C++ and C#, there is no problem here either. A problem might have arisen if the authors had used C++ with multiple inheritance, because Java and C# forbid this. But since they didn't, it's not an issue. As an OO language, Java is actually pretty minimal.
Another way of looking at the topic of your language is that if you don't use Java, you can potentially use the book to better effect. Because you can't simply copy the Java code, then you have to actually get an accurate understanding of what it is doing, before manually recoding.
The text covers the most common structures and methods for using those structures, that you are likely to need. Lists, stacks, iteration, recursion, queues, sorting, searching, hashing etc. Some of these subjects have immense depth. For example, sorting and searching takes up one volume of Knuth's "Art of Computer Programming". But that is a very advanced text, and ill suited to someone new to the basic algorithms. Harris and Ross give you enough complexity to be challenging and understandable. While perhaps giving some indications as to more intricate underlying issues.
As alluded to above, if you proceed through the text, several important Java classes are used. Vector, List, Hashtable, HashSet and others. You would be well advised to gain fluency in these, as the book shows how they form the basis of much computational work. You also get an appreciation for the beauty of Java, inasmuch as it comes with those classes. While you could certainly write these from scratch, not having to do so is a huge timesaver. And by using the system classes, you are assured of very stable, highly debugged classes.
Book Description
This book is for all financial professionals whose work, to a greater or lesser degree, involves complex spreadsheets and financial models. This includes investment bankers, commercial banks, accountancy firms, property firms, public sector including local government and healthcare, PFI/PPP enterprises, financial managers and financially literate general managers. Junior/middle management, where the focus would be on cash flow forecasting and budgeting tasks, will also find this book of value.
For the vast majority of people involved in this subject, financial modelling is an activity, a task requiring skills. Once people have the ability to structure the model, they have a better starting point from which to address the financial problems. This new book proposal intends to offer that starting point.
Theory is limited to the absolute essentials that aid understanding; thus the focus with this new book is very practical - this is "how-to-do-it", showing best practice, and is illustrated with many practical worked examples.
* Practical financial modelling- all the essentials in one book
* How-to approach, with numerous worked examples
* Explains the techniques and functions of Excel most use in financial modelling and budgeting
Average customer rating:
- cd format mac incompatibility fixed (for me)
|
Computer Algebra Recipes: An Advanced Guide to Scientific Modeling
Richard H. Enns , and
George C. McGuire
Manufacturer: Springer
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Computer Algebra Recipes for Classical Mechanics
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Computer Algebra Recipes for Mathematical Physics
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Dynamical Systems with Applications using Maple
ASIN: 0387257683 |
Book Description
Modern computer algebra systems are revolutionizing the teaching and learning of mathematically intensive subjects in science and engineering, enabling students to explore increasingly complex and computationally intensive models that provide analytic solutions, animated numerical solutions, and complex two- and three-dimensional graphic displays.
This self-contained text benefits from a spiral structure that regularly revisits the general topics of graphics, symbolic computation, and numerical simulation with increasing intricacy at each turn. The text is built around a large number of computer algebra worksheets or "recipes" that have been designed using MAPLE to provide tools for problem solving and to stimulate critical thinking. No prior knowledge of MAPLE is assumed. All relevant commands are introduced on a need-to-know basis and are indexed for easy reference. Each recipe is associated with a scientific model or method and an interesting or amusing story designed to both entertain and enhance concept comprehension and retention. All recipes are included on the CD-ROM enclosed with the book.
Aimed at third- and fourth-year undergraduates in science and engineering, the text contains numerous examples in disciplines that will challenge students progressing in mathematics, physics, engineering, game theory, and physical chemistry.
Computer Algebra Recipes: An Advanced Guide to Mathematical Modeling can serve as an effective computational science text, with a set of problems following each section of recipes to enable readers to apply and confirm their understanding. The book may also be used as a reference, for self-study, or as the basis of an on-line course.
Customer Reviews:
cd format mac incompatibility fixed (for me).......2002-02-27
Contacted Springer who manufactured cd in microsoft format incompatible to mac today (26Feb2002).
... These authors are masters. Each author, I find from surfing on the web, has a computer learning lab. The early reading introduces the fact that without the constraints of paper, undergraduates can learn to compose solutions to more realistic problems, eg. golf balls do not go on parabolas but do depend on your irons and crosswinds.
My last read text by the same authors, "Nonlinear Physics with Maple" edition 1 was a really inspiring book full of exercises. A master of solitons, Ablowitz, wrote (with) "Complex Variables" available at [Amazon.com]. Riemann Hilbert problems chapter 7 ought to further flesh out "Nonlinear Physics with Maple" last chapter concerning inverse scattering method in a to me readable manner.
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An Illustrated Guide to Theoretical Ecology
Ted J. Case
Manufacturer: Oxford University Press, USA
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Elements of Mathematical Ecology
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Primer of Ecological Theory
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Population Ecology: First Principles
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Population Biology: Concepts and Models
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Ecology: From Individuals to Ecosystems
ASIN: 0195085124 |
Book Description
An Illustrated Guide to Theoretical Ecology uses a combination of visual presentations and the symbolic logic of algebra and calculus to provide the most accessible introduction to ecological theory available. It gives students the basic tools they need to understand the complexities of ecological systems and to analyze simple quantitative ecological problems. The author walks students through the most common models in ecology, beginning with first principles and then gently making each formulation accessible through a step-by-step development of equations paired with lavish illustrations. He also applies theoretical developments to practical issues in conservation and resource management, offering a more visceral understanding of the purpose and utility of the theory and demonstrating how it may need modification in its application to real-world problems and future directions. The text also includes some basic ecological genetics and an exploration of metapopulation dynamics. An Illustrated Guide to Theoretical Ecology is enhanced by over 500 two-color diagrams, many end-of-chapter problems, and a website that includes simulation models that parallel each chapters development (http://www.nceas.ucsb.edu/BookCase). Ideal as a main text for advanced undergraduate courses in theoretical and mathematical ecology or conservation biology, this unique book can also serve as a supplement or a self-guided tutorial in general ecology, population ecology, and community ecology courses.
Average customer rating:
- No substitute for Handbook of Mathematical Functions
|
Atlas for Computing Mathematical Functions: An Illustrated Guide for Practitioners With Programs in C and Mathematica
William J. Thompson
Manufacturer: Wiley-Interscience
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ASIN: 0471002607 |
Book Description
Introducing a comprehensive book and CD-ROM for visualizing and computing special functions
Here is an invaluable reference and learning guide to more than 150 special functions of applied mathematics, statistics, physics, chemistry, computer science, and engineering. The Atlas contains over 700 graphics of the functions, which readers can also create by using the annotated Mathematica files provided. It offers complete, consistent instructions and test values for computing the functions accurately and efficiently with the full ANSI C source programs on the CD-ROM, which is both Windows and Macintosh compatible.
With extensive references and indexing, this integrated package is superbly designed and easy to use-ideal for anyone who works with special functions. Contents include:
* Elementary Transcendental Functions
* Exponential Integrals and Related Functions
* Gamma and Beta Functions
* Combinatorial Functions
* Number Theory Functions
* Probability Distributions
* Error Function, Fresnel, and Dawson Integrals
* Orthogonal Polynomials
* Legendre Functions
* Spheroidal Wave Functions
* Bessel Functions
* Struve, Anger, and Weber Functions
* Hypergeometric Functions and Coulomb Wave Functions
* Elliptic Integrals and Elliptic Functions
* Parabolic Cylinder Functions
* Miscellaneous Functions for Science and Engineering
* Mathematica Notebooks
* C Driver Programs
Customer Reviews:
No substitute for Handbook of Mathematical Functions.......2000-09-07
According to the author, the practicality of books on functions is often limited by the graphical content, and that books of tables like Abrahamowitz & Stegun "serve a very limited purpose" today (primarily to check function evaluating software). This "Atlas" tries to fill this void, and it does a respectable job. However, detailed function exploration and visualization is left to Mathematica users, the primary audience for this book. Without Mathematica 2.2 or later, and/or a C complier, a great deal in this title cannot be fully appreciated. Of course, the reader can often explore function behavior by plotting an equation using common spreadsheet software that came with his computer w/o using C or Mathematica. But much of this high-priced textbook consists of small blocks of C code and everlasting references to Mathematica notebook calls. Part II contains ~200 pages of Mathematica notebook descriptions and ~100 pages of C driver programs, not to mention the C code documented throughout the first 600 pages.
Most the "Atlas" graphics are small (~2") gray-scale screenshots of Mathematica plots. The quality of some graphics leaves something to be desired though (Figure 7.2.2 p. 119 for example), since many figures are obviously grainy (vertical lines and text characters often appear as broken line segments, not unlike a tilted faxed image). These gray-scale images are fairly bland - I expected at least a little color and only the highest quality graphics for a book calling itself an "atlas", especially for the asking price.
"Atlas" is no substitute for the timeless books of tables and equations such as the (inexpensive) A&S (ISBN 0486612724) or the CRC Standard Math Tables. In computing the error function (erf), for example, Dr. Thompson defines erf in terms of a function call of the gamma function, while A&S provides many, many more alternatives suitable for machine solution. The discussions here, while more generous than A&S, are much less detailed than an explanatory book like Numerical Recipes. Instead, pictorial surveys primarily forego a lot of the detailed explanation of the underlying function theory. A few of the functions, such as the Voight distribution, are hard to find in the classic references, but the reader will find very few new topics here.
I expect this title, being heavily tied to a particular software package and computer language, will find itself being re-issued in later editions as software inevitably evolves. I therefore wouldn't expect too many individuals paying $175 for what is almost a software book. All in all, a well packaged presentation but not quite the insightful, general purpose book for which I had hoped.
Average customer rating:
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Model Theory (Oxford Logic Guides, 37)
Maria Manzano
Manufacturer: Oxford University Press, USA
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Binding: Hardcover
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ASIN: 0198538510 |
Book Description
Logic languages are free from the ambiguities of natural languages, and are therefore specially suited for use in computing. Model theory is the branch of mathematical logic which concerns the relationship between mathematical structures and logic languages, and has become increasingly important in areas such as computing, philosophy and linguistics. As the reasoning process takes place at a very abstract level, model theory applies to a wide variety of structures. It is also possible to define new structures and classify existing ones by establishing links between them. These links can be very useful since they allow us to transfer our knowledge between related structures. This book provides a clear and readable introduction to the subject, and is suitable for both mathematicians and students from outside the subject. It includes some historically relevant information before each major topic is introduced, making it a useful reference for non-experts. The motivation of the subject is constantly explained, and proofs are also explained in detail.
Average customer rating:
- A good introduction to Verification and Validation of CFD
|
Aiaa Guide for the Verification and Validation of Computational Fluid Dynamics Simulations
American Institute of Aeronautics and As
Manufacturer: AIAA (American Institute of Aeronautics & Ast
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Binding: Paperback
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ASIN: 1563472856 |
Customer Reviews:
A good introduction to Verification and Validation of CFD.......2001-08-21
The book covers the basics of verification and validation of CFD simulations. It is not an advanced text for scientists, but an introductory text for beginners or CFD engineers. It is divided into 5 chapters, with a solid background presentation in chapter 1, followed by a description of the terminology (chapter 2). In the rest of the book, the author divides the subject into verification (grid and time step sizes tests) and validation (comparasion with previous or experimental data), presenting good descriptions of both itens.
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