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Download Numerical analysis epub

by Richard L Burden

The new Seventh Edition of Burden and Faires' well-respected Numerical Analysis provides a foundation in modern numerical-approximation techniques. Explaining how, why, and when the techniques can be expected to work, the Seventh Edition places an even greater emphasis on building readers' intuition to help them understand why the techniques presented work in general, and why, in some situations, they fail. Applied problems from diverse areas, such as engineering and physical, computer, and biological sciences, are provided so readers can understand how numerical methods are used in real-life situations. The Seventh Edition has been updated and now addresses the evolving use of technology, incorporating it whenever appropriate.
Download Numerical analysis epub
ISBN: 087150314X
ISBN13: 978-0871503145
Category: Science
Subcategory: Mathematics
Author: Richard L Burden
Language: English
Publisher: Prindle, Weber & Schmidt; 2nd edition (1981)
Pages: 598 pages
ePUB size: 1861 kb
FB2 size: 1186 kb
Rating: 4.5
Votes: 178
Other Formats: lrf rtf azw doc

I'm a grad student and I recently had to learn how to numerically solve PDE's. I'm rather new to computer programming and numerical analysis in general. I've really only been in my field for about 1 year now.

I picked up this book and went straight to Chapter 12. It explained everything quite concisely and had very clear descriptions and diagrams. Armed with pen and paper, I learned how to numerically solve these PDE's quite quickly. It was honestly a fun experience. Whenever there were tools that I was missing, the authors would reference the section and chapter where you could find the necessary tools.

I believe this book was written as a reference, as well as, textbook. A problem that many textbooks suffer from, is that the material is written in sequential order, with newer material depending heavily on the previous chapters. These types of books are not adept to being just picked up and read, to gather the relevant information. They require you to pretty much read all the preceding text to understand it, and who has time for that? This book is NOT like that.

You can just pick it up and easily learn from it. Unlike Numerical Recipes, this provides the method with a very clear explanation and justification for the algorithms. Numerical Recipes is good, but its purpose is not to provide detailed explanations of why and how the algorithms work.

To be able to use this text, I would suggest having taken Calc 1,2 & 3, differential equations, linear algebra class, and be comfortable with programming. I suspect that the folks complaining heavily about this text, are not very comfortable with with Calculus, linear algebra, and/or programming. If you are an undergrad and have not taken those classes or are not comfortable with the material, I can see you struggling. If you are a grad student in Math or Physics, this text will be rather refreshingly easy to read. It will help fill in the necessary gaps in your knowledge of computational work, if you have any like I did. Enjoy!
I'm Biased since I had Richard Burden(Author) as my professor for Numerical Analysis and this is the book we used in his course (obviously).

I doubt you'll be looking into any of these books unless you need a reference material for a course or something, but there wasn't significant differences between this version and the next one. But from what I understand the most recent version has enough differences that if you need this for a course, to get the newest version. But, if you are just buying this for your own sake, this is a great book/version.

The material in the book itself is a great resource, and I would argue that any CS student (or even just programmer who wants to be a bit better in his field) should know this material, that way they know how to evaluate run-time performance of a program (if nothing else). The book is fairly well understandable even if you aren't the best in math, so don't let that stop you if you are interested, there are online code snippets and evaluation programs you can try out and learn from also.
They sold me a book that says in the lower right-hand corner of the cover (though you can't read it in the image they show) that "This edition is licensed for sale only in India, Pakistan, Bangladesh, Nepal and Sri Lanka. Circulation of this edition outside of these countries is UNAUTHORIZED AND STRICTLY PROHIBITED." So, a little ways into my semester, we were being assigned problem numbers from the textbook; however, the context of the problem was not matching that from my professor's book. It was discovered that this was why his was not matching mine: because this is an illegal copy here in the United States, and clearly does not match up as to content.
By reading the material in this book, the student is left with the theory and the examples necessary to understand and appreciate Numerical Methods in Engineering. There is no need to memorize formulas. Most students, with little bit of effort, can derive their own formulas to solve a specific problem. While the book is starting as a Numerical Methods Textbook, yet it helps the student to smoothly enter the world of Numerical Analysis. The topics included are more than enough for a two semester course presented in an easy-to-read style with lots of solved examples. I have been teaching Numerical Methods and Numerical Analysis for many years now and have found that this textbook provides adequate background and the necessary skills for my students. This book teaches how to derive numerical solutions to problems. That is perhaps the most important lesson of all.
Unfortunatelly on the 7th edition they changed a lot of stuffs (and have even took ride of some examples). I loved the 3rd edition of this book, which has a better look, not so thin characters and better graphics, easy to find anything just by browsing the pages. Anyway, the book as a whole, is still is a nice reference.
Required textbook for a course in Numerical Analysis. I would probably seek another reference if given an opportunity, but that means I would have to read a lot of dry books to get there. It has some good sample code to assist in understanding the development of certain algorithms.
Fantastic reference for anyone with a solid mathematical background and in a research field requiring data analysis.
As described.