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The Nature of Mathematical Modeling Hardcover – November 28, 1998

9 customer reviews

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Editorial Reviews


"In a compact but accessible manner, Gershenfeld offers a wide-ranging overview of mathematical ideas and techniques that provide a number of effective approaches to problem solving...a great compendium of techniques. It should be kept within easy reach of anyone who wants to build computer models to help understand the world

"...masterfully written, fun to read, and brimming over with useful information....This text is a marvelous handbook of mathematical modeling."
UMAP Journal

"Gershenfeld's style of giving brief overviews together with a concise summary of key results in the subject area makes [the book] invaluable for mathematical and computational modelers...Highly recommended."

"...I do not know any other single source of the material presented here."
Michael Marder, Physics Today

"Neil manages to combine new and old flavors like analysis and stochastic modeling, finite element methods and cellular automata, nonlinear function minimization and information-theoretic system identification in a single integrated overview that exposes the purposes and capabilities of each. Any of these areas can be a black hole, capable of swallowing a student in detail, with no observable output. This book performs the valuable service of teaching novice or practitioner of what the methods can offer to the overall purpose of modeling the world around us or before us."
Scott Kirkpatrick, IBM Research, inventor of simulated annealing

"This is a book for anyone who wants to use a computer to build models. The book draws on an enormous variety of sources, but Gershenfeld has seen through to the core ideas and has brought out the key relationships between the various methods. The book is a pleasure to read."
Michael I. Jordan, University of California, Berkeley

"Simulation and mathematical modeling will power the 21st Century the way steam powered the 19th. Gershenfeld masterfully compresses two armloads of dense textbooks into a single clear volume, including both classic and avant garde methods, and with well-selected references for further study. Every student of computing needs this book as the entry ticket into a vital and rapidly changing field."
William H. Press, Harvard University, author of Numerical Recipes

"The sheer breadth of material that this book surveys and unifies in surprising ways is one strong recommendation for including The Nature of Mathematical Modeling in your library. Readers will profit from physicist Neil Gershenfeld's background as he draws connections among the many, often seemingly disparate, facets of mathematical modeling...And, of course, this is a book for practicing mathematicians, computer scientists, physicists, engineers, and any and all others interested in both standard and not so standard techniques viewed in the rich and stimulating context that this book provides."
The American Mathematical Monthly

"This is a well-written and interesting book. It would make an excellent text for a final-year undergraduate course in modeling and a good reference for research students in any situation where data are to be examined."
Computing Reviews

"The exposition of the text is fluent and engrossing...As a mathematician I found many of the topics discussed in the text interesting and worthy of further investigation. I would certainly recommend the text to a colleague interested in understanding the connections that exist among the seemingly unrelated techniques of applied mathematics."
MAA Online

Book Description

This is a book about the nature of mathematical modeling, and about the kinds of techniques that are useful for modeling. The text is in four sections. The first covers exact and approximate analytical techniques; the second, numerical methods; the third, model inference based on observations; and the last, the special role of time in modeling. Each of the topics in the book would be the worthy subject of a dedicated text, but only by presenting the material in this way is it possible to make so much material accessible to so many people. Each chapter presents a concise summary of the core results in an area. The text is complemented by extensive worked problems.

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Product Details

  • Hardcover: 356 pages
  • Publisher: Cambridge University Press (November 28, 1998)
  • Language: English
  • ISBN-10: 0521570956
  • ISBN-13: 978-0521570954
  • Product Dimensions: 6.8 x 1.2 x 9.7 inches
  • Shipping Weight: 1.9 pounds
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (9 customer reviews)
  • Amazon Best Sellers Rank: #801,472 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

33 of 33 people found the following review helpful By A Customer on April 20, 1999
Format: Hardcover
Basically, this is a great book. I couldn't put down, really. It's sort of a 'everything you always wanted to know about modeling' book, and the author went to great lenghts to compress a huge amount of material in one handsome, managable volume without becoming superficial or less rigorous.
The only thing I'm not happy with is the author's own description of prerequisites: he claims the book is self-contained, and only requires "some calculus and linear algebra". In reality, readers had better be comfortable with complex numbers, operators, coordinate systems, probability theory and various other topics of mathematical physics. And instead of "some" calculus, there is serious calculus involved here. Laplace transforms, the 'del' operator and various other more-or-less advanced topics are presented in the first chapter in a way that suggests the reader's familiarity with them. To those of us that are familiar with these concepts, the book is a delight. To those of us that are not, the book is likely to be too fast-paced and advanced.
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15 of 15 people found the following review helpful By Thy Yem on July 25, 2002
Format: Hardcover Verified Purchase
This book concisely describes critical ideas, techniques, and results of a wide range of applied mathematics which are useful in physical modelings. It has well chosen exercises, though not many, with detail answers. It provides good references for further study. This is important because the explanations given in this book are terse.
I think the book is more valuable for those looking for concise reviews than those wanting to learn the materials the first time.
Also, Author states (at MIT website) that he is working on the second edition for this book. He wants to add "control theory" and correct some typos.
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16 of 17 people found the following review helpful By Oldman on April 3, 2000
Format: Hardcover
Very readable and enjoyable book if you like Applied Mathematics. In addition to very broad but not shallow coverage of the various techniques used to model physical phenomena, the author provides *excellent* references for those who want to dig further. The Matlab code and computer techniques are an excellent addition.
I agree with the previous reviewer, the book will become a classic.
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12 of 13 people found the following review helpful By Nathaniel Osgood on January 30, 2000
Format: Hardcover
This is the best general overview of applied mathematical modeling that I have seen. It succinctly characterizes the essential features of wide variety of tools rarely collected in a single volume. The author makes consistent use of notation and formalisms drawn from physics, which lends the book a uniform ground for all areas discussed. The usefulness of the book is not limited to the techniques presented, however -- there are gems of insight in the commentary scattered throughout the book. My only gripes are the inevitable compromises needed for brevity and the fact that I discussion of software tools struck me as quite weak and rather parochial.
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7 of 7 people found the following review helpful By W Boudville HALL OF FAMEVINE VOICE on January 18, 2006
Format: Hardcover
The book offers you a multidisciplinary survey of how to do modelling on a computer. Gershenfeld tries to give an appreciation of a wide variety of methods. Both in the diversity of these methods and in the fields to which they can be applied.

You might already be familiar with the classic "Numerical Recipes" text, which also offers a survey of the field. Gershenfeld takes the analysis to a slightly more advanced level. But not so much so as to be impenetrable to many readers.

The book also gives a nice summary of various maths packages that could be useful to you. Plus, as a further aid, the text has numerous problems and solutions. In fact, the solutions take up a considerable and worthy portion of the book.
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