Algorithms Books

This book discusses algorithms in computer science but does integrate enough C++ code into the text, in spite of its title. Also, a lot of the code still has remnants of C philosophy, such as #define statements, in spite of the authors frequent use of "class" in their code. Buy this book with caution, as it is very expensive.

Don't waste your money on this text, it is rotten. I had it for a class and found this book to do very little in aiding the learning process due to its lack of any sort of coherent explaination. I ended up purchasing another text and used it from then and until now, after college.

this is the only textbook i have ever sold back after the semester.

... If the primary complaint against this text is that the authors have not provided enough C++ source code examples for the types of algorithms explained, take a look at the price tag. At a list price of [price], one can logically deduce that this text is for a university audience, emphasizing the theory behind the algorithms, as well as the synthesis it takes for you to generate modified versions from the templates presented. If you are looking for a more "how to"-oriented text (you know, the kind that "spoon feeds" you) with excessive source code examples, you definitely should look for another text. Nevertheless, I consider this book to be both highly appropriate and effective for its intended audience.

I'm a student at department of Computer Science and Information Engineering, National Taiwan University.We took the course "Algorithms",and used this book as a text book.After a semister learning, i never heard any good comments for this book.The most word given to this book is"This book can make easy to hard!"We'll never choose this book as a text book again.

This book is a textbook for a Computer Science course "Analysis of Algorithms" in Queens College, CUNY. The entire class suffers, because the book isn't readeable. The language isn't English!

Authors strive to make even the simplest algorithms difficult to understand. The code examples have almost no comments and are typed in a messy disordered fashion. Mathematical analysis requires huge background in analytical mathematics and prior knowledge of everything it talks about. Proofs of theorems are not clear. Where the authors state something like "... clearly this is so-and-so... " the argument isn't even logical!

Very often they don't even describe an algorithm - they just say "the algorithm is presented by the code on page ..." (this page is usually 10 pages away). The number of typographical mistakes is enormous. The examples are based on bizarre numbers and data structures.

Don't ever ever ever consider buying this book! For college professors: please don't use this book as a textbook in your class unless you want to have a "D" average at the end of the semester.

I'm in the middle of trying to complete Linear Algebra right now, with Liebler's book. I've never met Dr. Liebler, but all I can say is that his book makes no sense. I don't really have much of a teacher who likes to "explain" things, but rather have you figure them out on your own. And that way is fine and everything, but I seriously do not understand one thing this book is trying to convey. The use of notation and the terms are horrendous. I have never ever had such a difficult time understanding a math book (I'm a math major). I've done well in both my Calculus courses, and have been able to teach myself many applications of math, but this Linear Algebra book is TERRIBLE. If you have ANY choice whatsoever, take a course that uses a different book--you'll be very grateful.

I was in one of the first classes Dr. Liebler decided to unleash this atrocity on. It was horrible then with 2 or 3 pages of errata, and it isn't much better now. Just imagine how horrible it was trying to learn the material with this as a textbook and with the author giving lectures that were just as foggy and incoherent. If I could give this book a 0 star rating, I would.

This book is horrendous. I can't believe it's still being published. It claims to illuminate the ideas and claims to be effective in approaching the numerous topics. I've read and reread the chapters, but still the content makes no sense. The worst part about it is that I'm a math major, and so I shouldn't be having this much trouble with it.

It's even worse that I've had the actual author as a substitute teacher numerous times at Colorado State University, and he can't even explain the material concisely in person.

Good, but COULD be better . . I think the book, having few typos, lacks in concrete explanations ( although quite some are there ) and instead, beats a bit with words around the bush, etc . I interpret some sections of chapters in full clarity entirely, yet still get lots vaguely . Very clear objectives and nice examples with great practice problems; I would recommend more geometrical interpretative topics to aid with a visual relationship of some topics . Overall good .

After reading (and re-reading) this book, I began to realize just how insignificant my puny little brain is. This book definitely put me in my place, and brought my ego down a few notches. I barely made it past the introduction before being befuddled. I find it hard to recommend something i don't understand

This book has some interesting convergence proofs and is a good reference for people doing research in the area. However, the non-standard notation makes it very difficult to follow, and the abysmal explanations do not help much. Do not get me wrong, there is some elegant math in this book, I just wish they'd made it a little easier to read.

If you're a practicing engineer, you should probably look at Widrow's "Adaptive Signal Processing", Haykin's "Adaptive Filter Theory", or Farhang-Boroujeny's "Adaptive Filters" (an EXCELLENT, though not very well known book) instead. If you're a researcher, the book by Solo & Kong is useful, but not a must-have by any means.

I am sitting in my college library and have been reading this book for about 5 minutes and have already found a huge error. When the author talks about safe file opening proceddures in php when using client inputed paramaters for a filename he suggests adding an extension to the end of the string before opening such as .fgfdfg so when an attacker attempts a string such as:
../../../../../../../../etc/passwd
it will try to open the non existent file /etc/passwd.fgfdfg
but any hacker worth his weight would just enter the string with a null bytesuch as:
../../etc/passwd%00
thus clipping the extension from the end. cause opening /etc/passwd\0.bsbs will open passwd

I havent read much more of the book but this huge error makes me want to put it back on the shelf. Overall, good for begginers I guess.... but theres better books out there and I wouldnt trust this one.

Peace
HexaTex

While I found most of the information in this book to be valuable, and didn't find any errors, the types of attacks discussed seemed very lopsided. The author talks in great length about DOS attacks on websites as well as SQL injection and command injection by exploiting input validation errors, but only covers PHP, ASP, and to some degree Perl. The XSS discussion was only 7 pages, and authentication was only 5 pages! This book is a great starting place, but if you've got any experience with web security you might want to look elsewhere. Additionally the book provides demonstrations using only commercial software that the author wrote. This alone made me extremely suspicious. There were no significant examples or discussion of other tools for testing web applications for vulnerabilities.

I checked this out from the library and was glad that I didn't buy it without reading it. It has very few equations and algorithms, and is more of a general overview or listing of computations done in GIS. Those hoping for a cookbook for geometric and analytic geography operations would best turn to Keith Clark's Analytic and Computer Cartograhy or a even good survey handbook for a better overview of the most important algorithms and formulas.

Yes, there are algorithms here, but they are not only a mishmash, but not very important ones

After reading this book, there are some parts missing here. I just described as follows.

For video scaling part, the polyphase filter design give more details on FIR filter design for fractional ratio. However, other methods like spline interpolation or nearest neighboring pixel method is not described here. The nonlinear scaling method gives more or less hints to design them which are all based on the high order polynomials and related to warping theory.

For digial video warping, it is better to refer to Dr. George Wolberg's book "Digital Image Warping" as keystone correction implementation

This book gives some information regarding gardient
calculations on edge detection which are based on frame level of video sequence. The de-interlacing parts did not give more industry designs on motion adaptive algorithms which use multiple fields data for motion detection/motion history and motion compensation based methods.

The diagonal direction based deinterlacing is not described here such as simple ELA algorithm.

The polyphase filter based deinterlacer will not work on fast motion video sequences when intra-field interpolation should be used. For slow motion of video, it might be ok to use vertical temporal filtering or even the previous field pixel for almost static image to create good result as intra field interpolation.

Readers who want to learn motion compensation based deitnerlacing should refer to Dr. Erwin Bellers's book "De-interlacing" for more advanced algorithms such as majority selection on 3D recursive search block matcher.

The 3:2 reverse pulldown for film material part only describes
pixel differences method. Block based variance or deviation methods are not mentioned here.

Examples are cluttered, confusing, and book is not very organized. Book could use more simple examples similar to homework problems. More in-depth explanation of ideas.

Lack of simplified examples makes the book hard to read and apply the tools to business questions. Requires a lot of effort to translate the contents for applying to real-world problems.

In some ways, this book offers the most thorough introduction to reconfigurable computing (RC) that I've seen. It starts with the platforms themselves, from Estrin's work around 1960 up to this year's Virtex 5 family of FPGAs. That discussion includes mainstream technologies, as well as recent explorations into coarse-grained and other architectures and a few of the commercially failed ideas that have arisen over time.

The next two chapters address basic issues in logic synthesis, at the gate level and datapath level. No one intro can cover the entire literature of the field, but this goes into mathematically proven depth in a few important algorithms. Two more chapters (5 and 7) address re-use the computing fabric over time, first as a formal exercise combining geometric constraints with temporal dependencies and then as a pragmatic exercise in terms of current chips and tools. Despite the amount of research attention that partial reconfiguration has gotten, tools are still crude and researchy. Instead of a commercial tool flow, expect to find a series of isolated puddles. Two more chapters (6 and 8) address system-on-chip issues. Finally, chapter 9 devotes about 30 pages to RC applications - or does it?

Really, it just names the applications and mentions a bit of why reconfigurability suits them. It doesn't go into much depth about the computations themselves. Even then, the discussion has more multiprocessor-on-chip flavor than any real sense of what makes FPGA-based RC truly different from von Neumann. I don't think the term "systolic array" appears anywhere.

I suppose it depends on what you want. Tool-builders will find a solid intro that works forward from a cold start. They'll see familiar compilation technologies applied in distinctive ways, with plenty of references for anyone in need of details. They'll see many of the unique problems in swapping parts of the computation on and off a working chip. RC practitioners take synthesis for granted though - synthesis algorithms hold only incidental interest. Partial reconfiguration, as the author emphasizes it, works only on one or two of the most recent chip famiies from Xilinx, and not at all on the Altera chips that are becoming more common in the RC arena. Applications focus on the embedded - media, signal processing, and the like - with scant mention of performance computing, my central interest. Although wide-ranging and well-researched, I have trouble imagining the RC practitioner who will take this book to the lab bench.

-- wiredweird