Introduction to Pattern Recognition Book

Introduction to Pattern Recognition

  • Author : Sergios Theodoridis
  • Publisher : Academic Press
  • Release Date : 2010-03-03
  • Genre: Computers
  • Pages : 231
  • ISBN 10 : 0080922759
  • Total Read : 99
  • File Size : 17,7 Mb

Introduction to Pattern Recognition Summary:

Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes 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. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition Solved examples in Matlab, including real-life data sets in imaging and audio recognition Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)

Introduction to Statistical Pattern Recognition Book
Score: 4.5
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Introduction to Statistical Pattern Recognition

  • Author : Keinosuke Fukunaga
  • Publisher : Elsevier
  • Release Date : 2013-10-22
  • Genre: Computers
  • Pages : 592
  • ISBN 10 : 9780080478654
  • Total Read : 90
  • File Size : 11,9 Mb

Introduction to Statistical Pattern Recognition Summary:

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.

Pattern Recognition and Classification Book

Pattern Recognition and Classification

  • Author : Geoff Dougherty
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-10-28
  • Genre: Computers
  • Pages : 196
  • ISBN 10 : 9781461453239
  • Total Read : 83
  • File Size : 13,5 Mb

Pattern Recognition and Classification Summary:

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Pattern Recognition Book

Pattern Recognition

  • Author : Sergios Theodoridis
  • Publisher : Elsevier
  • Release Date : 2003-05-15
  • Genre: Technology & Engineering
  • Pages : 689
  • ISBN 10 : 008051362X
  • Total Read : 99
  • File Size : 7,5 Mb

Pattern Recognition Summary:

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms. *Approaches pattern recognition from the designer's point of view *New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere *Supplemented by computer examples selected from applications of interest

Introduction to Pattern Recognition and Machine Learning Book

Introduction to Pattern Recognition and Machine Learning

  • Author : M Narasimha Murty
  • Publisher : World Scientific
  • Release Date : 2015-04-22
  • Genre: Computers
  • Pages : 404
  • ISBN 10 : 9789814656276
  • Total Read : 89
  • File Size : 9,7 Mb

Introduction to Pattern Recognition and Machine Learning Summary:

This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter. Contents:IntroductionTypes of DataFeature Extraction and Feature SelectionBayesian LearningClassificationClassification Using Soft Computing TechniquesData ClusteringSoft ClusteringApplication — Social and Information Networks Readership: Academics and working professionals in computer science. Key Features:The algorithmic approach taken and the practical issues dealt with will aid the reader in writing programs and implementing methodsCovers recent and advanced topics by providing working exercises, examples and illustrations in each chapterProvides the reader with a deeper understanding of the subject matterKeywords:Clustering;Classification;Supervised Learning;Soft Computing

Introduction to Pattern Recognition Book
Score: 1
From 1 Ratings

Introduction to Pattern Recognition

  • Author : Menahem Friedman
  • Publisher : World Scientific
  • Release Date : 1999
  • Genre: Computers
  • Pages : 350
  • ISBN 10 : 9810233124
  • Total Read : 71
  • File Size : 20,6 Mb

Introduction to Pattern Recognition Summary:

This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. 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. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

Statistical Pattern Recognition Book

Statistical Pattern Recognition

  • Author : Andrew R. Webb
  • Publisher : John Wiley & Sons
  • Release Date : 2003-07-25
  • Genre: Mathematics
  • Pages : 517
  • ISBN 10 : 9780470854785
  • Total Read : 79
  • File Size : 18,9 Mb

Statistical Pattern Recognition Summary:

Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref=""

Introduction to Recognition and Deciphering of Patterns Book

Introduction to Recognition and Deciphering of Patterns

  • Author : Michael A. Radin
  • Publisher : CRC Press
  • Release Date : 2020-08-09
  • Genre: Mathematics
  • Pages : 148
  • ISBN 10 : 9781000078558
  • Total Read : 96
  • File Size : 8,8 Mb

Introduction to Recognition and Deciphering of Patterns Summary:

Introduction to Recognition and Deciphering of Patterns is meant to acquaint STEM and non-STEM students with different patterns, as well as to where and when specific patterns arise. In addition, the book teaches students how to recognize patterns and distinguish the similarities and differences between them. Patterns, such as weather patterns, traffic patterns, behavioral patterns, geometric patterns, linguistic patterns, structural patterns, digital patterns, and the like, emerge on an everyday basis, . Recognizing patterns and studying their unique traits are essential for the development and enhancement of our intuitive skills and for strengthening our analytical skills. Mathematicians often apply patterns to get acquainted with new concepts--a technique that can be applied across many disciplines. Throughout this book we explore assorted patterns that emerge from various geometrical configurations of squares, circles, right triangles, and equilateral triangles that either repeat at the same scale or at different scales. The book also analytically examines linear patterns, geometric patterns, alternating patterns, piecewise patterns, summation-type patterns and factorial-type patterns. Deciphering the details of these distinct patterns leads to the proof by induction method, and the book will also render properties of Pascal’s triangle and provide supplemental practice in deciphering specific patterns and verifying them. This book concludes with first-order recursive relations: describing sequences as recursive relations, obtaining the general solution by solving an initial value problem, and determining the periodic traits. Features • Readily accessible to a broad audience, including those with limited mathematical background • Especially useful for students in non-STEM disciplines, such as psychology, sociology, economics and business, as well as for liberal arts disciplines and art students.