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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4.0 out of 5 stars
Excellent Introduction,
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This review is from: Introduction to Pattern Recognition : Statistical, Structural, Neural and Fuzzy Logic Approaches (Series in Machine Perception and Artificial Intelligence) (Hardcover)
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
3.0 out of 5 stars
Weak notation but simplified ideas,
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Amazon Verified Purchase(What's this?)
This review is from: Introduction to Pattern Recognition : Statistical, Structural, Neural and Fuzzy Logic Approaches (Series in Machine Perception and Artificial Intelligence) (Hardcover)
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.
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Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Inside This Book
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First Sentence:
Pattern recognition is characteristic to all living organisms. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
fuzzy tolerance relation, generalized decision functions, intraset distance, linear dichotomies, submedian chromosome, final cluster centers, pairwise separation, linear decision functions, bipolar activations, incoming pattern, clustering transformation, crisp classification, associative units, linear separator, perceptron learning rule, initial cluster centers, linear decision boundary, fuzzy classification, pattern classification problems, loss matrix, fuzzy partition, enddo enddo, pattern classes, membership values, training patterns Key Phrases - Capitalized Phrases (CAPs): (learn more)
Academic Press, John Wiley, Englewood Cliffs, Prentice Hall New!
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Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Pattern recognition is characteristic to all living organisms. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
fuzzy tolerance relation, generalized decision functions, intraset distance, linear dichotomies, submedian chromosome, final cluster centers, pairwise separation, linear decision functions, bipolar activations, incoming pattern, clustering transformation, crisp classification, associative units, linear separator, perceptron learning rule, initial cluster centers, linear decision boundary, fuzzy classification, pattern classification problems, loss matrix, fuzzy partition, enddo enddo, pattern classes, membership values, training patterns Key Phrases - Capitalized Phrases (CAPs): (learn more)
Academic Press, John Wiley, Englewood Cliffs, Prentice Hall New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Citations (learn more)
This book cites 44
books:
See all 44 books this book cites
- Advances in Knowledge Discovery and Data Mining (American Association for Artificial Intelligence) by Usama M. Fayyad on page 9, and page 12
- Pattern Recognition: Human and Mechanical by Satosi Watanabe on page 16
- Fuzzy Sets and Fuzzy Logic: Theory and Applications by George J. Klir on page 14
- Foundations of Neural Networks (Addison-Wesley Series in New Horizons in Technology) by Tarun Khanna on page 14
- Algorithms for Clustering Data (Prentice Hall Advanced Reference Series : Computer Science) by Anil K. Jain on page 13
See all 44 books this book cites
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