Pattern Recognition 4th Edition by Konstantinos Koutroumbas (PDF)

Description

This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback.Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included–now in two color–to provide greater insight through visual presentation Matlab code of the most common methods are given at the end of each chapter An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐The book “Pattern Recognition” of Theodoridis and Koutroumbas is an excellent one.It covers the field thoroughly, and the material is presented very clearly, bothfrom the mathematical and the algorithm point of view.It includes superb examples andcomputer experiments with which the reader can gain insight to the topics.Also, it is updated with a lot of recent advances on the Pattern Recognition domain,as e.g. Semi-supervised learning, combining classifiers, spectral clustering,nonlinear dimensionality reduction. The presentation of all these advanced material isvery well organized and the reader can follow and understand thesesophisticated mathematically concepts.It is one of my three best books on the topic,the other ones are the “Neural Networks” of S. Haykin, and “Pattern Recognition and Machine Learning”,of C. Bishop.I think all these three books are excellent,in their own way,and should not be missed from the bookshelf of anyone that copes with the Pattern Recognition field,either student or researcher.However, for the reader interested in developing computer algorithms in the Pattern Recognition area,the book of Theodoridis and Koutroubas is the superior choice.

⭐The book describes the field, including classification and clustering, clearly and concisely, while not ignoring the key mathematical concepts. I’m a CS grad student studying this area and have been subjected to a number of textbooks that are math-heavy and fail to give any descriptive context of what’s being presented. A good textbook on a subject should actually TEACH the reader the concepts. This one does that quite well. In addition, three chapters on feature generation and processing are included, a subject most other texts barely cover at all. This revised addition is a substantial expansion of the previous one and now includes many recently-developed concepts. If I were teaching an advanced undergrad or graduate course on the subject I would probably choose this as my primary text.

⭐Although there is a TON of info in this book it’s really not that great for learning pattern recognition. It’s definitely more of a reference than anything else. You can’t really read a section and then sit down at your computer and code it up. There a so many details missing. And the equations are so compact that you spend most your time decoding bad notation. If this book were a piece of software it would suffer from feature bloat. If you need to actually do any real applications using the techniques in this book you should definitely by the MATLAB companion text.

⭐Awesome book! I really love it. Mathematics in this books are pretty easy, and the exposition of each topic is magnificent. Also it gives a lot of references which are useful for the practicant and the researcher.

⭐My graduate Statistical Machine Learning course required me to purchase 2 books!…this one and another (not naming the other here). This book does SUCH A BETTER JOB at explaining the subtle assumptions the equations are making. My other book makes tons of assumptions making it easy to get lost :(. This book saved my butt in this class (no pun intended)!

⭐This book is horrible for any teacher to assign for a class.This book is really for those of you who really understand proofs and like to work them out. For those of you trying to lean and understand the algorithms and concepts, THIS BOOK IS NOT FOR YOU.The authors have nothing but pages of text with no paragraphs, relatively few diagrams, the diagrams that are in the text book don’t provide enough related detail.The author fails to summarize the most important details of the processes, and blathers on about unrelated information. He also writes in an extremely passive voice. Most of his sentences can be cut in half because of it.This book is only useful as a reference to those who are very knowledgeable about the field, and is useless to near learners. If your professor ever makes you get this text, tell him you’re getting the text book by Bishop instead…its a better read.

⭐Man, this IS the book on pattern recognition! Lengthy, simple, direct, clean; contains the most essential one must know about all the techniques when working with pattern recognition. I have also Duda et al Pattern Classification. But THIS one is far better and far didactic. If you want to learn how to classify patterns, this is THE book.

⭐I agree with previous reviewers about the broadth and depth of the material in this book. Yes, i didn’t read everything but the topics i was looking for were briefly and clearly explained. Exactly what is needed for an phD student doing his work in this field.I am a phD candidate in computer vision lab doing the research on image based localization.

⭐One of the best pattern recognition / machine learning books. Highly recommended. The mathematical aspects are very well detailed although some prior knowledge is required. Also, a broad range of topics is covered.

⭐This book is considered “the text” on the topic and it is, with ample math-lab examples and exercises.It would be good if author consider releasing the CD/ web-link along the book as well.

⭐Some pages in the book are obviously a wrong content, which means some pages are repeated and the corresponding pages are missing.Due to my heavy study load, I have no time to change it, but I am so satisfied with it. It is easier to check the photo I took, where the page number is totally not correct.

Keywords

Free Download Pattern Recognition 4th Edition in PDF format
Pattern Recognition 4th Edition PDF Free Download
Download Pattern Recognition 4th Edition 2008 PDF Free
Pattern Recognition 4th Edition 2008 PDF Free Download
Download Pattern Recognition 4th Edition PDF
Free Download Ebook Pattern Recognition 4th Edition