[ download Textbooks ] Pattern RecognitionAuthor Sergios Theodoridis Dr. – Carcier.co

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 Worked Examples To Give Greater Understanding Of The Various Methods And Techniques Many 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 More Matlab Code Is Available, Together With An Accompanying Manual, Via This Site 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 An Accompanying Book With Matlab Code Of The Most Common Methods And Algorithms In The Book, Together With A Descriptive Summary, And Solved Examples Including Real Life Data Sets In Imaging, And Audio Recognition The Companion Book Will Be Available Separately Or At A Special Packaged Price ISBN Thoroughly Developed To Include Many Worked Examples To Give Greater Understanding Of The Various Methods And Techniques Many 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 Package ISBN 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 Register At Textbookselsevier And Search On Theodoridis To Access Resources For Instructor


9 thoughts on “Pattern Recognition

  1. CORNELIU COFARU CORNELIU COFARU says:

    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.


  2. 14th-century.se Customer 14th-century.se Customer says:

    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.


  3. N. Tregenza N. Tregenza says:

    It s a magnificent collection of mathematical tools used in pattern recognition However a lot of pattern recognition is done successfully by programmers using quite low level maths in quite long series of problem oriented processes As one such I found it interesting to learn the names of what I ve been doing on a common sense basis and see how impressive the formal maths looked, but I didn t find it very useful the maths notation being the first hurdle Worse there are almost no descriptions of the earthy realities of a whole process of a serious applications.Many pattern recognition tasks are solved through elaborate, intelligent, but somewhat arbitrary numerical cookery and there s little discussion of this e.g just try outliers in the index.As a chunky box of mathematical confectionery it will delight mathematicians


  4. E. Fighter E. Fighter says:

    This book was the perfect companion course book It is well written, easy to understand, and works extremely well with the MATLAB text for illustrating ideas covered within the book.


  5. Stergios Papadimitriou Stergios Papadimitriou says:

    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.


  6. T. Olaes T. Olaes says:

    This is not a review on the book itself, but rather the KINDLE EDITION As a person who bought this book as text for a graduate class, it was very hard to distinguish some of the letters in the formulas contained within Also, some characters don t seem to have been translated properly Especially misleading was when a subscript was rendered within the kindle cloud reader as a superscript which gives any equation an entirely different meaning when such a thing is done.I do not recommend purchasing the Kindle edition of this textbook stick with good old paper until this gets revised.


  7. Abel Brown Abel Brown says:

    Although there is a TON of info in this book it s really not that great for learning pattern recognition It s definitely 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.


  8. Jose I. Miranda Jose I. Miranda says:

    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.


  9. Gene Shuman Gene Shuman says:

    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.