Algorithms Books

This book is not an ideal text for college students because it does not explain concepts in a clear understandable manner. The target readers for this book are computer scienctists and mathematicians. College students who are just beginning to learn about data structures will not easily grasp the full meaning of this book.

The overall scope of the book is perfect for a two quarter data structures class. It goes into just enough depth to teach you something new, and something useful. But if you actually try to follow code examples or try to understand a diagram, beware because there are a lot of errors in them. Every chapter has at least two errors. Problem is, we are supposed to be learning something new and if the diagrams can't explain the situation correctly how can we not help but be confused. Don't buy this book unless you have to have it for a class, there are better books.

this book has all the fundamental algorithms on graph problems and is written in a easy to understand manner

This is a good book in terms of gaining background information. The work is very theoretical, and does leave a lot to the imagination.

This book is not really intended for the working engineer, but perhaps the graduate student. This does go into iterative methods, and never touches on other optimization algorithms in use (simulated annealing, genetic algorithms, etc).

Much of the information can be found in the authors' publications (a trip to the library is called for).

This is an average book. But I liked the Distributed Algorithms by Nancy Lynch better. It is a much better presented book that this one though most of the material covered is the same give or take a few. Over all a good book worth the money but there are better books.

I bought this book for a graduate course. Despite the applause I see in the back cover, it is not so good as a textbook. It might be good if you are well-versed in the lexicon of optimization and optimization is your main area, then I think this book is good to understand the quantitative as well as the qualitative dimensions of each technique. For a novice researcher or student in the field, this is not the right book.

This book is poorly edited and too expensive for what you get. However, it is the only book I know of on the topic. It does an Ok job of describing the various techniques for motion estimation, and also delves into theory. What I like about this book is the many numeric experimental results that can be helpful in evaluating and comparing the various techniques. You may find this book useful as a supliment to some of the books on MPEG.

While the book contained an enormous amount of useful information and is elagantly written, it missed the mark on providing useful, "here's how you do it..", numerical methods and algorithms for MBS as the title implies. Since the book originated from lecture notes, it was assumed there would be a few simple examples of MBS which would be solved, in detail, using different methods to illustrate various techniques and formulations. The Chapter on software engineering, I feel, is completely out of place. Again, a useful view but not necessary within the topic of MBS and in the context of this book. To the extent software engineering is discussed, it's best left to a book explicitily on software engineering. It's between too much and not enough. In my opinion, this book would be most useful as a reference to individuals who already have an intimate knowledge of MBS and numerical methods and not to individuals with knowledge in mechanics and software seeking to learn practical formulations and numerical methods for MBS. For the price of the book, I was quite dissapointed amount of useful, "hands on" material. On a positive note, the book does cover many topics in numerical methods (e.g. integrators, contraints..) with great detail. The book is very well written, easy to read, and it apparent that great deal of effort was made to provide elegant formulas and consise notation.

Winkler presents an extremely concise overview of the major algorithms of polynomial algebra. In order to understand the text fully you must have a very strong background in abstract algebra. Even then you'll probably find yourself re-reading sections of the book in an attempt to reach an understanding. The advantage of this book over more explanatory texts (like Geddes) comes from the meticulous quality of the proofs and algorithms.

This monograph is a very good survey of the QAP and its variations. The treatment is however far from complete. The exact method section excludes a lot of recent developments including RLT of Sherali and Adams. Recent results on polyhedral studies into the QAP polytope are missing. The heuristic methods is skinny and is missing neural network methods. Certain QAP variations such as placement problem are not covered. A chapter on QAP applications would have been helpful.

Nevertheless, it provides a very good overview of a very important NP-hard problem: QAP