Item description for Introduction to Pattern Recognition : Statistical, Structural, Neural and Fuzzy Logic Approaches (Series in Machine Perception and Artificial Intelligence) by Menahem Friedman, Abraham Kandel, Hilary Owen, Amal El Fallah Seghrouchni, Samuel Kariuki, Ian Morson, Arthur Nersesian & Scott Silsby...
An introduction to pattern recognition, this text is meant for students in computer science and related fields in science and technology. Algorithms and real world applications accompany most of the topics in the text. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail.
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Studio: World Scientific Publishing Company
Est. Packaging Dimensions: Length: 1" Width: 7.25" Height: 10.25" Weight: 1.7 lbs.
Release Date Dec 1, 1999
Publisher World Scientific Publishing Company
ISBN 9810233124 ISBN13 9789810233129
Availability 0 units.
More About Menahem Friedman, Abraham Kandel, Hilary Owen, Amal El Fallah Seghrouchni, Samuel Kariuki, Ian Morson, Arthur Nersesian & Scott Silsby
Friedman (Nucear Research Center-Negv, Israel)
Menahem Friedman has an academic affiliation as follows - Ben Gurion University.
Reviews - What do customers think about Introduction to Pattern Recognition : Statistical, Structural, Neural and Fuzzy Logic Approaches (Series in Machine Perception and Artificial Intelligence)?
Excellent Introduction May 18, 2010
This is one of the best introductions into statistical pattern recognition that you will find. Explains the mathematics behind the algorithms very effectively. Used this text in a grad course a couple years ago but you don't need to be a grad student to understand and use the concepts in this text, I have re-read various chapters of this books while working and its a great asset. Note that although it has great coverage of the math used in pattern recognition it won't review the math, you should know it. If you don't have a good grasp of calculus and linear algebra then you probably should go back and learn the math before reading this book, and to be blunt you really shouldn't be getting into pattern recognition if you don't know the math anyway. I would have given 5 stars if they had code written in an actual language rather than pseudo code (with bad variable names). I still don't get why authors don't pick a descriptive language that any programmer can understand like Python or R to show you examples rather than pseudo code. But overall, you'll be happy with this purchase
Weak notation but simplified ideas Jul 29, 2008
This book is okay. It prevents some AI ideas in a simplified contexts. When resorting to mathematics, its notation is quite weak and can lead to confusion.
Its short, it prevents some intuitions that are nice but all in all, Duda, Heart and Storkes book is still far better.