Introduction to Algorithms

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Aimed at any serious programmer or computer science student, the new second edition of Introduction to Algorithms builds on the tradition of the original with a truly magisterial guide to the world of algorithms. Clearly presented, mathematically rigorous, and yet approachable even for the math-averse, this title sets a high standard for a textbook and reference to the best algorithms for solving a wide range of computing problems.

With sample problems and mathematical proofs demonstrating the correctness of each algorithm, this book is ideal as a textbook for classroom study, but its reach doesn't end there. The authors do a fine job of explaining each algorithm. (Reference sections on basic mathematical notation will help readers bridge the gap, but it will help to have some math background to appreciate the full achievement of this handsome hardcover volume.) Every algorithm is presented in pseudo-code, which can be implemented in any computer language, including C/C++ and Java. This ecumenical approach is one of the book's strengths. When it comes to sorting and common data structures, from basic linked lists to trees (including binary trees, red-black, and B-trees), this title really shines, with clear diagrams that show algorithms in operation. Even if you just glance over the mathematical notation here, you can definitely benefit from this text in other ways.

The book moves forward with more advanced algorithms that implement strategies for solving more complicated problems (including dynamic programming techniques, greedy algorithms, and amortized analysis). Algorithms for graphing problems (used in such real-world business problems as optimizing flight schedules or flow through pipelines) come next. In each case, the authors provide the best from current research in each topic, along with sample solutions.

This text closes with a grab bag of useful algorithms including matrix operations and linear programming, evaluating polynomials, and the well-known Fast Fourier Transformation (FFT) (useful in signal processing and engineering). Final sections on "NP-complete" problems, like the well-known traveling salesman problem, show off that while not all problems have a demonstrably final and best answer, algorithms that generate acceptable approximate solutions can still be used to generate useful, real-world answers.

Throughout this text, the authors anchor their discussion of algorithms with current examples drawn from molecular biology (like the Human Genome Project), business, and engineering. Each section ends with short discussions of related historical material, often discussing original research in each area of algorithms. On the whole, they argue successfully that algorithms are a "technology" just like hardware and software that can be used to write better software that does more, with better performance. Along with classic books on algorithms (like Donald Knuth's three-volume set, The Art of Computer Programming), this title sets a new standard for compiling the best research in algorithms. For any experienced developer, regardless of their chosen language, this text deserves a close look for extending the range and performance of real-world software. --Richard Dragan

Topics covered: Overview of algorithms (including algorithms as a technology); designing and analyzing algorithms; asymptotic notation; recurrences and recursion; probabilistic analysis and randomized algorithms; heapsort algorithms; priority queues; quicksort algorithms; linear time sorting (including radix and bucket sort); medians and order statistics (including minimum and maximum); introduction to data structures (stacks, queues, linked lists, and rooted trees); hash tables (including hash functions); binary search trees; red-black trees; augmenting data structures for custom applications; dynamic programming explained (including assembly-line scheduling, matrix-chain multiplication, and optimal binary search trees); greedy algorithms (including Huffman codes and task-scheduling problems); amortized analysis (the accounting and potential methods); advanced data structures (including B-trees, binomial and Fibonacci heaps, representing disjoint sets in data structures); graph algorithms (representing graphs, minimum spanning trees, single-source shortest paths, all-pairs shortest paths, and maximum flow algorithms); sorting networks; matrix operations; linear programming (standard and slack forms); polynomials and the Fast Fourier Transformation (FFT); number theoretic algorithms (including greatest common divisor, modular arithmetic, the Chinese remainder theorem, RSA public-key encryption, primality testing, integer factorization); string matching; computational geometry (including finding the convex hull); NP-completeness (including sample real-world NP-complete problems and their insolvability); approximation algorithms for NP-complete problems (including the traveling salesman problem); reference sections for summations and other mathematical notation, sets, relations, functions, graphs and trees, as well as counting and probability backgrounder (plus geometric and binomial distributions).

Book Description

There are books on algorithms that are rigorous but incomplete and others that cover masses of material but lack rigor. Introduction to Algorithms combines rigor and comprehensiveness.

The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.

The first edition became the standard reference for professionals and a widely used text in universities worldwide. The second edition features new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming, as well as extensive revisions to virtually every section of the book. In a subtle but important change, loop invariants are introduced early and used throughout the text to prove algorithm correctness. Without changing the mathematical and analytic focus, the authors have moved much of the mathematical foundations material from Part I to an appendix and have included additional motivational material at the beginning.

Customer Reviews:

Excellent buy.......2007-09-24

I bought a new copy of the book, and was happy to receive it the way I expected. Got free shipping with this one.

Confusing to say the least.......2007-09-14

This book does not provide enough examples to really get the ideas across. It is a thick read that provides little help to the subject matter unless the reader already has a wealth of knowledge on mathematical proofs and algorithms to begin with.

If the book had a solution manual, or at least explained many of the things that occur in the problem sections that never show up in the actual reading, then it would be a much easier to understand textbook.

Fantastic algorithms book.......2007-06-03

This is one of the few books that I've kept from my undergrad days as a computer science major. Although I haven't been doing software development in a while, I still use it for reference once in a while. It's easy to understand and timeless reference book. I work for a large DoD company and quite a few of my co-workers have this book on their shelves as well. (We all went to different colleges.)

Good Reference, Poor Textbook.......2007-04-19

This is a good reference for researchers, but it is not suitable for beginners. For anyone who try to study algorithms in the beginning, he just needs the big picture of this course, but this book contains too many mathematical proofs. In other words, the beginners just want a cup of milk, but the authors of this book give them a whole cow.

Although this book is quite huge, it does not contain some important topics, like online algorithms, randomized algorithms ... etc. In fact, this book should try to 'lose its weight' in order to get more useful knowledge.

The book contains a lot of interesting exercises, but does not indicate any hints or solutions. In fact, some of those exercises are too hard for students, and the authors should try to announce all sloutions in the website.

Too much and too little.......2007-03-02

+ Defacto standard
+ Accompanying WebCourse

- Too deep if used as an intro book; lacks solutions if used for a reference book
- It's HUGE!; hard to carry around

= Tries to appease too wide an audience. Definately attractive to professors who already know the information and feel this is THE book yet probably too deep for an intro algorithms class. Wish there was a searchable pdf version that came with the book on a CD as well as odd numbered solutions.

The Mathematics of Financial Derivatives: A Student Introduction

Average customer rating:

Good Buy
Okay but not an introduction
Introduction to partial differential equations in finance
A good introduction to the PDE approach
waste of time

The Mathematics of Financial Derivatives: A Student Introduction
Paul Wilmott , Sam Howison , and Jeff Dewynne
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0521497892

Book Description

Finance is one of the fastest growing areas in the modern banking and corporate world. This, together with the sophistication of modern financial products, provides a rapidly growing impetus for new mathematical models and modern mathematical methods. Indeed, the area is an expanding source for novel and relevant "real-world" mathematics. In this book, the authors describe the modeling of financial derivative products from an applied mathematician's viewpoint, from modeling to analysis to elementary computation. The authors present a unified approach to modeling derivative products as partial differential equations, using numerical solutions where appropriate. The authors assume some mathematical background, but provide clear explanations for material beyond elementary calculus, probability, and algebra. This volume will become the standard introduction for advanced undergraduate students to this exciting new field.

Customer Reviews:

Good Buy.......2007-08-29

maps one to one with many chapters in Hull. more elaborate derivations than Hull. Fixed income area treatment is very slim though. Good Buy for the Price.

Okay but not an introduction.......2006-07-31

If you want an introduction, read another book like Hull. If you want to learn how to apply Partial Differential Equations (PDEs) approach to finance then it is a useful book. However, it is better to read an elementary PDEs book before reading this book. At least, learn how to solve parabolic PDEs analytically because the technical notes in the book would not help much.

Introduction to partial differential equations in finance.......2005-10-13

This book treats only the partial differential equations
in Finance and how to treat them using Finite Differences
and Tree. For this purpose it is very well written and
understandable. A very good beginning for student. Even
undergraduate.

Now after reading it you should understand the martingales reading the baxter and how to implement Monte Carlo using, for example Glasserman (see my reviews)

A good introduction to the PDE approach.......2005-10-10

Contrary to what many readers believe, this book explains the pricing of derivatives much better than Hull. Hull gives an overview of the mechanics and properties of the derivative pricing industry, along with its pricing methodologies, and this book provides an in depth method to one of the pricing methods.

Financial derivatives can be priced by a wide range of methodologies, among some the elegant equivalent martingale measure approach (or risk-neutral pricing), replication, multinomial tree approximation, Monte Carlo simulation, partial differential equations etc etc.

This book gives an excellent introduction, and an insight to the PDE approach. Although being a big fan of the Girsanov-change-of-measure method myself, these analytical methods often fail in the valuation of highly complex derivatives like the exotics. Pricing americans prove to be hard and inefficient too, even with simulation and the risk-neutral approach.

This is where PDE methods come in. Since most derivatives (or term structures) have a PDE describing its evolution, solving the PDE seems to be a good (or sometimes the best) way, no matter how complex the derivative can get. PDEs on the other hand, have very robust and easy methods for solving. Therefore, this book brings the reader through basic PDE solving methods, analytical solutions, techniques for fast and efficient numerical approximations as well as rigorous technical explanations for some of the mathematics of partial differential equations (which arise in the financial industry).

The authors are famous for their research in the field of Industrial and Applied Mathematics, and this book continues to be a classic for undergraduates in mathematics in Oxford. If you want to have an overview of the pde approach to option valuation, without the hassle of learning up Radon-Nikodým and martingales, I highly recommend this book!

waste of time.......2005-03-10

This book is very bad, lacks almost everything you can think of, but if you don't know any better you probably won't care. It certainly needs to be supplemented by a respectable book if you want to learn derivatives (c.f. Hull's textbook, for example), and on the other hand, the math isn't rigorous at all, so you'll need a book on stochastic calculus (e.g. Michael Steele's, actually there are tons of better books out there, it's not hard to find better).

Introduction to Computational Science: Modeling and Simulation for the Sciences

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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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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.

Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling

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Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling
Tom A.B. Snijders , and Roel Bosker
Manufacturer: Sage Publications Ltd
ProductGroup: Book
Binding: Paperback

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ASIN: 0761958908
Release Date: 1999-12-07

Book Description

The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines.

Modeling the Environment: An Introduction To System Dynamics Modeling Of Environmental Systems

Average customer rating:

Great Book for Anyone
Great interdisciplinary book on environmental modeling
Modeling the Environment

Modeling the Environment: An Introduction To System Dynamics Modeling Of Environmental Systems
Andrew Ford
Manufacturer: Island Press
ProductGroup: Book
Binding: Paperback

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ASIN: 1559636017

Book Description

Modeling the Environment is the first introductory textbook for a technique of rapidly growing importance. It requires little or no mathematical background, and is appropriate for undergraduate environmental students as well as professionals new to modelling. Developed from the author's own introductory course, it is classroom-tested and represents an important contribution to the field of system dynamics.

Modeling techniques that allow managers and researchers to see in advance the consequences of actions and policies are becoming increasingly important to environmental management. The models produced are vital analytical tools that aid the policy-setting and implementation process, and help us to understand how environmental systems respond to management interventions.

Modeling the Environment is a basic introduction to one of the most widely known and used modeling techniques, system dynamics. The book is designed to build the skills of students as they progress from learning fundamental ideas to constructing models of increasing complexity. Written in a clear and comprehensible style, the book:

presents basic concepts of modeling using system dynamics
illustrates the mechanics of model construction through a range of working models
offers a rich array of exercises for students to use in applying the principles and techniques described in the text
walks students through the design and application of models of specific types of environmental systems

In addition, the book contains more than 300 figures and model illustrations, and provides a guide to an interactive website where students can use the text to "navigate" management flight simulators ? models of both real and hypothetical systems developed by the author. The book also contains appendixes that help students review the necessary math, and which provide additional concepts and exercises for further study.

Customer Reviews:

Great Book for Anyone.......2006-12-12

This is a great book for anyone who wants to gain a thorough understanding of Stella software. The book is easy to read, and the examples and case studies are well chosen.

Great interdisciplinary book on environmental modeling.......2000-05-24

A highly readable introduction to environmental modeling. What distinguishes the book from other environmental science and environmental modeling works is its interdisciplinary treatment. In particular, the models integrate the physical world and the world of human behavior. Far too many environmental models fail to close the feedbacks between human behavior and the state of the environment, instead taking waste inputs or resource use as exogenous. This book helps students learn to model human behavior (social and economic) as an integral part of the ecological system. The models and software mean the book encourages active learning, and enable students to explore important issues on their own if they choose.

Modeling the Environment.......2000-04-24

This book is easy to read and contains clear examples of how to use stella software to model the environment. The marvel here is the software, not the book. For the software timid, it might suppliment the software users guide.

An Introduction to Statistical Modeling of Extreme Values

Average customer rating:

Practical text on extreme values statistics
A clearly written intro book on extremes
well written with a nice mix of theory and application

An Introduction to Statistical Modeling of Extreme Values
Stuart Coles
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Accessories:

ASIN: 1852334592

Book Description

Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.

Customer Reviews:

Practical text on extreme values statistics.......2006-11-10

Stuart Coles, who is well published on the open literature, has delivered this practical text on extreme values statistics by providing extreme values theory in a simplified manner with worked examples. Further, Coles has removed much of the complicating aspects (long mathematical proofs and overly complex notation) typical of statistical literature. The text provides any engineer or scientists with the tools required to complete routine extreme values analysis.

A clearly written intro book on extremes.......2002-10-05

I recently used the software accompanied to this book kindly made available by the author and was led to know more about this book and the author's other works. I like what I saw and think the author has done a supeb job in explaining the difficult theory in plain language and in the context of data analysis. Thus it is an "action" book instead of the "just theory" as with most other books. The book provides a balanced treatment of different approaches to extreme value analysis. Personally I prefer the generalized Pareto approach, though theoretically the point process approach may be very neat, if it can be realized.
I think extreme value theory in general is an important statistical area, since in practice one may be forced to deal with analyzing extreme events, such as in financial engineering, environmental or climate analysis, or network design. I wholeheartedly recommend this book for anyone who want to learn this area from one of the leading researchers.

well written with a nice mix of theory and application.......2002-01-29

This book is the most current text available on the theory of extreme values. The author eloquently provides us with an understanding of the theory and it vast applications. It is intended for researchers students and practitioners. So it provides an in-depth account of the theory with many real world examples. It contains an excellent up-to-date bibliography. Important theorems are presented with their implications but without mathematical proofs. Computations are done in SPlus. The author provides an appendix on computational aspects that tells the reader where to go to download examples and find the SPlus functions that are used.

Topics include classical extreme value theory and models, threshold models, extremes in dependent stationary cases, extremes for some nonstationary stochastic processes, the point process approach, multivariate extremes and some special topics including extremes in spatial processes and the Bayesian approach to extremes (with examples employing MCMC methods).

Average customer rating:

Good introduction

A great overview of the Volume Rendering Pipeline

Introduction to Volume Rendering (Hewlett-Packard Professional Books)
Barthold Lichtenbelt , Randy Crane , Hewlett-Packard Co. , and Shaz Naqvi
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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ASIN: 0138616833

Customer Reviews:

Good introduction.......2001-04-25

This book covers very well all the processes from rough data to volume rendering. No pre-requisites, all the terminology is explained with a lots of schemes. It also covers OpenGL rendering, but as it was published in 1997, this part is not really up-to-date. Nevertheless it is a good introduction to volume rendering, even if it is quite useless for real-time volume rendering with OpenGL for example.

A great overview of the Volume Rendering Pipeline.......1998-11-04

This book gives a good overview of the typical Volume Rendering by Ray Casting pipeline, and discusses the mathematics without going into too great a depth. The book gives many references on each subject so that the reader can then read more about the topics of interest. The only 'problem' is that the book never mentions a few popular algorithms, such as the Marching Cubes Algorithm.

Introduction to Physical Modeling with Modelica (The International Series in Engineering and Computer Science)

Average customer rating:

Good introductory book
Hands-on experience with Modelica

Introduction to Physical Modeling with Modelica (The International Series in Engineering and Computer Science)

Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Principles of Object-Oriented Modeling and Simulation with Modelica2.1

ASIN: 0792373677

Book Description

The first book on Modelica, a modeling language that can be used to simulate both continuous and discrete behavior, Introduction to Physical Modeling with Modelica provides the necessary background to develop Modelica models of almost any physical system. The author starts with basic differential equations from several engineering domains and describes how these equations can be used to create reusable component models. Next, he describes techniques for modeling complex non-linear behavior, exploiting the powerful array handling features and mixing continuous and discrete behavior. The second part of the book focuses on effective use of all the language features provided by the Modelica modeling language. This includes, among other things, discussions on maximizing the reusability of component models being developed, managing the model development process, and making models as computationally efficient as possible. Introduction to Physical Modeling with Modelica includes a companion CD-ROM with the Modelica source code for all examples as well as an evaluation copy of Dymola. Using Dymola, readers can immediately begin to explore the dynamics of the models included with the book or to develop their own models. Nearly 100 examples of mechanical, electrical, biological, chemical, thermal and hydraulic models are included. Introduction to Physical Modeling with Modelica will be of interest to all professional engineers and university researchers developing physical models. Students studying control system development or modeling of physical systems will also find it useful.

Customer Reviews:

Good introductory book.......2005-06-13

The book is well structured and have many interesting examples. The book is a good start point for anyone who wants to start learning Modelica. The price is in my opinion a little bit expensive since the book is based on Modelica 1.6 language specification and the latest spec is 2.2 with some relevant changes.

Hands-on experience with Modelica.......2001-12-11

One of the weakest points of the new object-oriented modelling language Modelica was the lack of an introduction to help engineers and scientists understand the differences to other modelling concepts. Using many examples from the automotive industry, electrical, mechanical and chemical engineering this book explains the concept of physical modelling, i. e. using basic laws to describe physical systems, and shows how to formulate these principles in Modelica. The Modelica language is presented in a series of examples that gradually grow more complex. The companion CD contains the complete source code of the examples and a working version of the commercial tool Dymola. The reader can thus start with the given examples and modify them to get some practise with the tool and the language.

The emphasis of the presentation is on the engineering task of building a model, for more theoretical questions references are given.

Book Description

This text provides a background view of the object approach, related geometric aspects, the different level of data modelling and the role of geo-information theory. The rest of the book builds upon these concepts describing the applicability of broader aspects such as topology, thematic object classes and class heirarchies, object aggregation and generalization and uncertainty.

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