An Introduction to Programming with IDL: Interactive Data Language Review

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(More customer reviews)Nothing is more intimidating to a new user of IDL than to sit down at a computer with an empty command line prompt and a stack of manuals on their desk and be told to write an IDL program. Where to begin!? And the experience is especially frightening to a new user with little or no programming experience in any language, let alone IDL.
Ken Bowman has written an IDL book specifically for this user. It is intended as an introductory computer programming course for the research user with little or no training in any computer language, and it evolved from notes Ken uses in his own undergraduate IDL programming courses. It is meant to get the new IDL user analyzing and plotting data as soon as possible.
It is a narrow path he treads, because it is just as easy to offer too much detail as it is to offer too little information to the beginning user. Ken, for the most part, gets it exactly right in covering a broad selection of topics. I quibble with just two chapters. He sweeps aside the complexity of PostScript output by offering the new user two utility programs he fails to explain in the text, and his theoretical explanation of the FFT function left me gasping for breath and lamenting I hadn't paid closer attention in those long-ago math classes.
This is a book that will get you started, but probably won't answer all your questions when you turn your attention to more difficult research problems. Ken doesn't pretend it is anything other than what it is, however, and provides generous and helpful suggestions for where you can find additional information as you become ready for it. Readers already familiar with another programming language will appreciate this introduction to IDL, but might become frustrated with the slower pace and lack of specific detail on many topics.
The book has an associated web page, where you can find, among other things, the source code for all the programs mentioned in the book. Pay particular attention to the Errata section, especially if you are interested in structures in IDL. A printer glitch removed all the curly brackets from Ken's IDL code in the structure chapter and none of the examples will work as written in the book. A software problem, no doubt. (The example programs for the chapter are correct.) It serves as a reminder to me of how complex a topic software programming can be. This friendly book will be a welcome introduction to the subject for many a potential IDL programmer.

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In today's information age, scientists and engineers must quickly and efficiently analyze extremely large sets of data. One of the best tools to accomplish this is Interactive Data Language (IDLÂ), a programming and visualization environment that facilitates numerical modeling, data analysis, and image processing.IDL's high-level language and powerful graphics capabilities allow users to write more flexible programs much faster than is possible with other programming languages.An Introduction to Programming with IDL enables students new to programming, as well as those with experience in other programming languages, to rapidly harness IDL's capabilities: fast, interactive performance; array syntax; dynamic data typing; and built-in graphics. Each concept is illustrated with sample code, including many complete short programs. ÂMargin notes throughout the text quickly point readers to the relevant sections of IDL manualsÂEnd-of-chapter summaries and exercises help reinforce learningÂStudents who purchase the book are eligible for a substantial discount on a student version of the IDL software

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Numerical Simulation in Fluid Dynamics: A Practical Introduction (Monographs on Mathematical Modeling and Computation) Review

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(More customer reviews)I found this book to be a a very good reference for the development of my first simple finite difference code for the solutions of the incompressible Navier-Stokes equations.
It is not extremely detailed in terms of all the methods exsisting in computational fluid dynamics, but it gives you those information that for a beginner might be hard to find. Good practical examples and a detail explanation on the development of a N-S solver also for FREE SURFACE problems.
Practical things as writing a makefile or how to set your code environment are explained aside of the mathematical analysis of the numerical methods involved.
I highly reccommend this book to those who study the subject but never put into practice that knowledge.
The practical examples are written in C.

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In this translation of the German edition, the authors provide insight into the numerical simulation of fluid flow. Using a simple numerical method as an expository example, the individual steps of scientific computing are presented: the derivation of the mathematical model; the discretization of the model equations; the development of algorithms; parallelization; and visualization of the computed data. In addition to the treatment of the basic equations for modeling laminar, transient flow of viscous, incompressible fluids - the Navier-Stokes equations - the authors look at the simulation of free surface flows; energy and chemical transport; and turbulence. Readers are enabled to write their own flow simulation program from scratch. The variety of applications is shown in several simulation results, including 92 black-and-white and 18 color illustrations. After reading this book, readers should be able to understand more enhanced algorithms of computational fluid dynamics and apply their new knowledge to other scientific fields.

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Modeling MEMS and NEMS Review

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(More customer reviews)This is among the finest books for modeling MEMS. Most other books give a mish-mash of fabrication and modeling, but you never figure out how to model!! This one is different. This is the gold standard for MEMS books to come.. I picked it up along with many other MEMS books from the library, never thought I would use it, but this is the ONLY book I use. Good even for the the advanced MEMS designer as a quick reference. But great for a new reader who wants to grasp the fundamental of modeling.

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Designing small structures necessitates an a priori understanding of various device behaviors. The way to gain such understanding is to construct, analyze, and interpret the proper mathematical model.Through such models, Modeling MEMS and NEMS illuminates microscale and nanoscale phenomena, thereby facilitating the design and optimization of micro- and nanoscale devices. After some introductory material, a review of continuum mechanics, and a study of scaling, the book is organized around phenomena. Each chapter addresses a sequence of real devices that share a common feature. The authors abstract that feature from the devices and present the mathematical tools needed to model it. They construct, analyze, and interpret a series of models of increasing complexity, then at the end of the chapter, they return to one of the devices described, apply the model to it, and interpret the analysis.In the beginning, the world of microdevices was dominated by experimental work and the development of fabrication techniques. As it matures, optimization and innovative designs are moving to the forefront. Modeling MEMS and NEMS not only provides the practical background and tools needed to design and optimize microdevices but it also helps develop the intuitive understanding that can lead to developing new and better designs and devices.

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Introduction To Three-dimensional Climate Modeling Review

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(More customer reviews)While this isn't a complete introduction, and while it may inevitably be slightly out of date, this is nonetheless the best introduction to climate modeling I've found. It presents the primary methods, and discusses the accomplishments and shortcomings of the field honestly (if at times a bit defensively).
There are clear limitations to climate modeling. For anyone with training in more mainstream Artificial Intelligence techniques, it's very uncomfortable to "test on the training data," which is exactly what climate modelers must do (i.e., they must run their models on the recent past, and if their models don't perform well on it, they will be tweaked until they do--effectively "cheating" because fidelity to the recent past is obviously no indication of predictive power if you tweak the model specifically to work on the recent past). Much of the uncertainty comes from sub-grid interactions that must be parameterized. For example, the formation of clouds is still an area of great uncertainty, and yet has an enormous effect on the climate. The authors recognize this issue, and identify it as a field where future research should focus.
On the other hand, climate modeling has been extremely useful as an inspiration to the imagination, and in working out the logical implications of what we currently believe to be true (both through those things that can be tested in a lab, like the absorption spectrum of carbon dioxide, or those that need to be parameterized, like cloud formation). We can't predict the future, but models allow us to get a sense of what may happen.
The authors discuss all of this, and illustrate it throughout. Of course, as scientists who have spent their lives in climate modeling, they are as supportive of climate modeling as one might expect. But they are also good scientists, and therefore open about the shortcomings.
In short, I'd recommend this book to anyone who wants an introduction to climate modeling. It's a fascinating and important subject that more people should know more about.

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This book provides an introduction to the development of three-dimensional climate models, including their four major components: atmosphere, ocean, land/vegetation, and sea ice. The fundamental processes in each component and the interactions among them are explained using basic scientific principles, and elements of the numerical methods used in solving the model equations are also provided. The authors show how the theory and models grew historically and how well they are able to account for known aspects of the climate system. This book is written so that a reader who is only vaguely aware of climate models will be able to gain an understanding of what the models are attempting to simulate, how the models are constructed, what the models have succeeded in simulating, and how the models are being used. Examples illustrating the use of the models to simulate aspects of the current climate system are followed by examples illustrating the application of the models to important scientific areas such as understanding paleoclimates, the last millennium, the El Nino/Southern Oscillation, and the effects of increasing greenhouse gas concentrations on future climate change. The book is appropriate for scientists, graduate students, and upper-level undergraduates and can be used as a textbook or for self study and reference. The authors have considerably updated the book from the first edition by adding descriptions of many techniques and results developed since the mid-1980s.

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Advanced Kalman Filtering, Least-Squares and Modeling: A Practical Handbook Review

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(More customer reviews)The most thorough and complete work I have seen on the subject. This provides a lot of in-depth information and insight into various areas not found elsewhere. While quite a bit of theory is presented, the main concentration is providing practical information useful for a wide variety of filter implementations. This will be most useful for somebody with a strong mathematical background, particularly in linear algebra, who is looking for a comprehensive understanding and the best solution for a particular application.

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This book provides a complete explanation of estimation theory andapplication, modeling approaches, and model evaluation. Each topicstarts with a clear explanation of the theory (often includinghistorical context), followed by application issues that should beconsidered in the design. Different implementations designed to addressspecific problems are presented, and numerous examples of varyingcomplexity are used to demonstrate the concepts.This book is intended primarily as a handbook for engineers who must design practical systems. Its primarygoal is to explain all important aspects of Kalman filtering and least-squares theory and application. Discussion of estimator design and model development is emphasized so that the reader may develop an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the "best" model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior.A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared.The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems.The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering.

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Modeling and Simulation in Scilab/Scicos with ScicosLab 4.4 Review

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(More customer reviews)The book "Modeling and Simulation with Scilab/Scicos"
is well written and understandable to
readers with the basic signal processing and programming
background.
The reader can refresh/improve the knowledge of
some basic control theory material, while at the
same time learns how to apply Scilab/Scicos at simulation and
modeling problems.
I worked with Matlab for many years before and I found
Scilab/Scicos a very powerful alternative to Matlab/Simulink
and is free!
I recommend strongly this book to any scientist/engineer that
plans to explore the benefits of the excellent open
source Scilab/Scicos environment.

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Scilab and its Scicos block diagram graphical editor, with a special emphasis on modeling and simulation tools. The first part is a detailed Scilab tutorial, and the second is dedicated to modeling and simulation of dynamical systems in Scicos. The concepts are illustrated through numerous examples, and all code used in the book is available to the reader.

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Simulation and Optimization in Finance + Website: Modeling with MATLAB, @Risk, or VBA (Frank J. Fabozzi Series) Review

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(More customer reviews)Prof.Pachamanova has written one of the best introductions to Simulation and Optimization methods in finance. This book provides a strong theoretical foundation and the website provides a lot of cases and useful hands-on exercises to apply and understand the concepts explained in the book. This book is highly recommended for business and engineering students who are interested in a career in the quantitative finance industry. This book is also recommended to new entrants to the quant finance industry and to financial practitioners who primarily use Excel for quantitative modeling but are interested in building more rigorous models using VBA, @RISK and MATLAB.
This book has the optimal combination of theory and practice. It starts out with a through introduction to statistics, finance and optimization concepts. In the second part, the book describes portfolio optimization theory and applications in equity and fixed income markets. The third part focuses on asset pricing models discussing classical and dynamic models. The fourth section mainly focuses on derivative pricing and provides a very good introduction to Monte-Carlo simulation methods. Topics of current interest such as pricing MBS products are also described in this section. Part five focuses on capital budget decisions and has a very good introduction to real options. The Software hints in each chapter and the supplementary materials on the website help students and practitioners to immediately try out examples and fortify their knowledge.
Prof.Pachamanova's didactic approach and the vast coverage of topics makes this book a must have for new quantitative analysts, business students and engineers interested in a career in finance. As a Financial Modeling consultant who works at MathWorks (the maker of MATLAB), I get a lot of questions on recommendations for books to apply financial theory using computational tools. This book is a gem and would makes great addition to your quantitative investing library.
Full Disclosure: I took a Statistics class with Prof.Pachamanova during my MBA program at Babson College

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An introduction to the theory and practice of financial simulation and optimization
In recent years, there has been a notable increase in the use of simulation and optimization methods in the financial industry. Applications include portfolio allocation, risk management, pricing, and capital budgeting under uncertainty.
This accessible guide provides an introduction to the simulation and optimization techniques most widely used in finance, while at the same time offering background on the financial concepts in these applications. In addition, it clarifies difficult concepts in traditional models of uncertainty in finance, and teaches you how to build models with software. It does this by reviewing current simulation and optimization methodology-along with available software-and proceeds with portfolio risk management, modeling of random processes, pricing of financial derivatives, and real options applications.
Contains a unique combination of finance theory and rigorous mathematical modeling emphasizing a hands-on approach through implementation with software
Highlights not only classical applications, but also more recent developments, such as pricing of mortgage-backed securities
Includes models and code in both spreadsheet-based software (@RISK, Solver, Evolver, VBA) and mathematical modeling software (MATLAB)

Filled with in-depth insights and practical advice, Simulation and Optimization Modeling in Finance offers essential guidance on some of the most important topics in financial management.

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