Customer Reviews


7 Reviews
5 star:
 (5)
4 star:
 (1)
3 star:
 (1)
2 star:    (0)
1 star:    (0)
 
 
 
 
 
Average Customer Review
Share your thoughts with other customers
Create your own review
 
 
Only search this product's reviews

The most helpful favorable review
The most helpful critical review


44 of 44 people found the following review helpful:
5.0 out of 5 stars A Great Book for Mathematicians and Engineers
The following is the review I published in The UMAP Journal (Summer, 2009, Vol 30, no. 2) pp. 175-178.

My second review for this journal [1986] was of Gilbert Strang's Introduction to Applied Mathematics (hereafter IAM). I have never been too happy with that review, where I said that it is a "wonderful book." True enough; but more appropriately, it is an...
Published on August 20, 2009 by James M. Cargal

versus
9 of 10 people found the following review helpful:
3.0 out of 5 stars Not as good as his linear algebra book
Even though I love Prof. Strang for making his lectures available for people like me and even though I liked his linear algebra book, I can not say that this book is excellent. I think that he puts too many topics in one book without giving enough details or depth on any of them. The book is more like a collection of lecture notes rather than a book. If you like to...
Published 17 months ago by Xiao Hu


Most Helpful First | Newest First

44 of 44 people found the following review helpful:
5.0 out of 5 stars A Great Book for Mathematicians and Engineers, August 20, 2009
By 
James M. Cargal (Montgomery, AL USA) - See all my reviews
(REAL NAME)   
This review is from: Computational Science and Engineering (Hardcover)
The following is the review I published in The UMAP Journal (Summer, 2009, Vol 30, no. 2) pp. 175-178.

My second review for this journal [1986] was of Gilbert Strang's Introduction to Applied Mathematics (hereafter IAM). I have never been too happy with that review, where I said that it is a "wonderful book." True enough; but more appropriately, it is an important book, as is the book reviewed here, Computational Science and Engineering (hereafter CSE).

CSE is--and is not--a second edition of IAM. Apparently, it is the result
of more than 20 years of Strang teaching his favorite course at MIT,
presumably out of IAM. Since CSE does not contain everything in IAM
and also contains topics not in IAM, it is a different text. CSE contains
Strang's further ruminations on the nature of applied mathematics, and
I view it as the superior text, but some individuals might prefer IAM. To
some extent, either book represents Strang's philosophy of teaching applied mathematics--that we need a new approach--but this conviction is much more explicit in CSE.

In particular, Strang believes that we should focus on both modeling and
computation. Many books are about one or the other, and he feels that applied mathematics is both. Furthermore, Strang believes that applied problems tend to have a common structure, and Chapter 2 is devoted to illustrating this principle through a wide variety of problems.

In my review of IAM, I tried to give an idea of the range of topics without enumerating the contents. CSE has the same difficulty: Enumerating the topics is tedious, but the titles of the chapters are informative (though listing them does not do justice to the sheer range of content):
1. Applied Linear Algebra
2. A Framework for Applied Mathematics
3. Boundary Value Problems
4. Fourier Series and Integrals
5. Analytic Functions
6. Initial Value Problems
7. Solving Large Systems
8. Optimization and Minimum Principles

Strang suggests that a course designed out of this text might follow the
structure that he uses (p. v):
* Applied linear algebra
* Applied differential equations
* Fourier series

I have long been a champion of Strang's books. I have reviewed different
editions of two texts on linear algebra, making clear that that I think he is the most influential author in linear algebra in the last 50 years. I have heaped high praise on his calculus text in my recent editorial on calculus [Cargal 2008]. I have done this for the exact reason that I have championed John Stillwell's books on geometry and algebra. These two authors, as well as a handful of others, write with authority leavened with the great enthusiasm of the born teacher. They are superb pedagogues.

What makes IAM and CSE so important is that they cover a great deal
of applied mathematics, and there is nothing in the literature that compares to them. Pedagogical works, as opposed to dry tomes, are simply
rarer in applied mathematics than they are in, say, calculus, linear algebra,geometry, and number theory. There are pedagogical works in differential equations and probability. But there is nothing that covers so much applied mathematics as these with comparative pedagogical skill and acumen.

Like IAM, CSE has a long first chapter that is a summary of applied linear
algebra (86 pp in IAM, 97 pp in CSE). Linear algebra is a key to applied
mathematics; it is the most important tool after calculus (this apparently is Strang's view). However, the first chapter is definitely a review. The reader needs to have had a course in linear algebra as well as the usual course in differential equations. These things are minimal. Courses in probability,numerical analysis, and so on certainly help. Knowledge of physics is a definite plus. These days, there are students of applied mathematics(computer science, statistics, operations research) who are physics-phobic. They would have problems with parts of the book. This necessity of a modicum of prior knowledge of applied mathematics means that the level of the book is for seniors and graduate students. The online comments about IAM are striking in their simplicity: Students who are not prepared despise the book, the others are enamored with it; there is no middle ground. The reader who is prepared should love this book. In particular, engineers and physicists should love this book.

People in industry, too, should love this book. Mathematicians and
engineers in industry benefit particularly froma book such as this for a very simple reason. Mathematicians in academia tend to specialize because of the need to publish. However, mathematicians in industry are motivated
to generalize. They don't have tenure; often they depend on contracts, so
that specializing can limit opportunities to get work. If a book like CSE (or AIM) had been available when I went into industry more than 30 years ago,it would have changed my life; it certainly would have made those first years easier. In fact, one topic that Strang covers very nicely in both books is the Kalman filter, a topic that is very big in industry and that occupied me in my first job.

The most important thing I tell my students is the need to study if they go into industry. This is particularly true if the student has stopped at the bachelor's degree, since a bachelor's degree is essentially a learner's permit. Few students go to work for national labs (those who do, do not need my advice--I need theirs), which means that on-the-job training is unlikely or superficial. Of people who have technical degrees, only a small portion maintain their technical skills; most simply travel along and forget much of what they learned. People tend to learn or they forget; nobody remains in stasis. In industry, you should take some of your time on the job to study.

Is spending work time studying material that is not clearly work related
to the work unethical? Typically, doing so does not create a problem (as
long as one gets one's tasks done). However, if your supervisor sees you
reading a newspaper, that could create a problem. On the other hand, if
you are studying number theory, there is no problem; that number theory
has nothing to do with your current job tasks will almost certainly not
register. Moreover, the worker who studies number theory will tend to
retain competence in differential equations far better than a worker who
just lets technical skills dissipate. In fact, those few workers who develop good technical reputations almost always study widely while on the job. Their ability to quickly respond to new problems on the job is a result of having used work time not to do company tasks. I view this behavior as a survival skill. The fact is, if one "steals" company time to study mathematics and engineering--even topics that have nothing to do with the job--one is far more likely to be promoted because of it than to be reprimanded.

However, the young worker almost always would benefit not only from
learning more number theory but--more urgently--needs to learn a lot
more applied mathematics. The undergraduate curriculum can't cover it
all. Key core areas are not just physics and differential equations, but probability,numerical analysis, and programming. For a worker in industry, CSE would be invaluable, and yet experienced engineers and mathematicians will also be impressed by this book.

Computational Science and Engineering should be in the library of every
applied mathematician, not to mention engineers. As a textbook, it is well suited for a senior or graduate course in applied mathematics.

References
Cargal, J.M. 1986. Review of Strang [1986]. The UMAP Journal 7 (4): 364-
365.

Cargal, J.M. 2008. Calculus: Textbooks, aids, and infinitesimals. The UMAP
Journal 29 (4): 399-416.

Strang, Gilbert. 1986. Introduction to Applied Mathematics. Wellesley, MA:
Wellesley-Cambridge Press.

[...]
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


9 of 10 people found the following review helpful:
3.0 out of 5 stars Not as good as his linear algebra book, August 23, 2010
Amazon Verified Purchase(What's this?)
This review is from: Computational Science and Engineering (Hardcover)
Even though I love Prof. Strang for making his lectures available for people like me and even though I liked his linear algebra book, I can not say that this book is excellent. I think that he puts too many topics in one book without giving enough details or depth on any of them. The book is more like a collection of lecture notes rather than a book. If you like to study linear algebra, use his linear algebra book. If you study finite difference method for PDEs, Hoffman's is a much better choice. For numerical linear algebra, there is the book by Trefethen.

So, my suggestion for you is as follows. Pick up the book from a library. And go straight to a topic that you are somewhat familiar with. And try to see if Prof. Strang does an excellent job on that topic. I did that for a few of them, and I found that the book is not sufficient explaining those topics.

By the way, for CG method neither the book nor the video lectures are very useful. You will need the article by Jonathan Richard Shewchuk. You can find it online. This is the best for CG.

Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


3 of 3 people found the following review helpful:
4.0 out of 5 stars Excellent for making connections, but not a text book, May 26, 2010
By 
This review is from: Computational Science and Engineering (Hardcover)
This books gives a unified view to topics which can seem unrelated.
For someone who has prior knowledge in CSE or applied mathematics, this book is good. Keep it in your shelf and read it to enjoy the beauty of the subject, not to learn from it.

This book is not any where close to Strang's linear algebra book.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


2 of 2 people found the following review helpful:
5.0 out of 5 stars Great lectures - but lectures, July 18, 2011
This review is from: Computational Science and Engineering (Hardcover)
This is a super collection of lectures. I read it because I wanted to know properly about numerical analysis, something that I've never systematically studied (as an unexpected bonus, I also pícked up a bunch of useful new linear algebra intuitions). If you want a coherent view of this stuff, then this has got to be as good a place to start as you can get. I can't compare the literature, since being painfully aware that I wasn't able to compare the literature was the reason I read it, but if I can't be comparative, I can certainly be positive: Strang is in effortless and complete command of his material, and a pleasure to read.

However, note that these are _lectures_ and consciously written as such (Strang takes a great deal of - entirely justifiable, if you check him out on youtube - pride in his classroom teaching), which means that there are occasional leaps (no bad thing, they make you think), minor lacunae, forward references and so on, all of which would be dealt with in a lecture as casual asides. If you don't want to deal with this sort of thing without him in the room with you, there may be other books out there that are more suitable (though I sort of doubt it).
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


2 of 2 people found the following review helpful:
5.0 out of 5 stars The best, July 25, 2010
Amazon Verified Purchase(What's this?)
This review is from: Computational Science and Engineering (Hardcover)
This book has a modest amount of information on a whole range of topics in applied mathematics. The authors writing style makes it a lot easier on the eyes than other textbooks in the field. I recommend it to anyone who is interested in numerical methods.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


22 of 32 people found the following review helpful:
5.0 out of 5 stars Pure love, February 5, 2008
Amazon Verified Purchase(What's this?)
This review is from: Computational Science and Engineering (Hardcover)
Dr Strangs book, is simply a work of love. If you have no idea of computational engineering, yet you want to see a man who had spent a lifetime in love, and still burried deep within it, experience Dr Strang's words. Pure and perfect. His style unparalleled, his passion unbounded. It needs to be there on every engineers desk, regardless of his discipline.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


1 of 1 people found the following review helpful:
5.0 out of 5 stars absolutely recommended, December 10, 2009
Amazon Verified Purchase(What's this?)
This review is from: Computational Science and Engineering (Hardcover)
This book is a must in bring all the main notions of scientific and engineering computation and establishing the links between them in a very comprehensive manner. Unmissable book for who is interested in the topic.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No


Most Helpful First | Newest First

This product

Computational Science and Engineering
Computational Science and Engineering by Gilbert Strang (Hardcover - November 1, 2007)
$90.00 $81.00
In Stock
Add to cart Add to wishlist