Customer Reviews

The Nature of Mathematical Modeling

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4 star:		(3)
3 star:		(0)
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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.

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.

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.

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.

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.

Neil Gershenfeld "The Nature of Mathematical Modeling" is a unique and a successful attempt to enclose in a single book the main ideas of mathematical view on nature, numerical methods, modeling techniques and computer software. The unifying concept of mathematics and philosophy of extraction of the main modeling concepts from nature observations enabled the success with the apparently impossible task. The book lacks rigor in mathematical derivations, but excels in unification of ideas. It can be recommended to students of mathematics and computer science to learn about complexity of natural phenomena, and vice versa, to students of engineering fields to gain a broader view on richness of mathematical theories.

This is an excellent overview of various mathematical techniques used in creating models.

There are many code snippets in C, Java and Matlab but this is mainly a mathematics book, and only incidentally a programming book. The code is presented to show "simple efficient implementations on computers."

Great as a refresher when you know a technique will be useful in a model but you've forgotten the details.

The first two sections of the book (Analytical Models and Numerical Models) assume you know what model you are going to use. The last, Observational Models, is concerned with "inferring a model from measured data."

The is a new version of this book being released in Jan 08. I look forward to it.

This is the book that I always wanted to read on mathematical modeling. I only wish he had written it earlier.