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Elsevier

Methodologies of Pattern Recognition

  • 1st Edition - January 1, 1969
  • Latest edition
  • Editor: Satosi Watanabe
  • Language: English

Methodologies of Pattern Recognition is a collection of papers that deals with the two approaches to pattern recognition (geometrical and structural), the Robbins-Monro procedures,… Read more

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Description

Methodologies of Pattern Recognition is a collection of papers that deals with the two approaches to pattern recognition (geometrical and structural), the Robbins-Monro procedures, and the implications of interactive graphic computers for pattern recognition methodology. Some papers describe non-supervised learning in statistical pattern recognition, parallel computation in pattern recognition, and statistical analysis as a tool to make patterns emerge from data. One paper points out the importance of cluster processing in visual perception in which proximate points of similar brightness values form clusters. At higher levels of mental activity humans are efficient in clumping complex items into clusters. Another paper suggests a recognition method which combines versatility and an efficient noise-proofness in dealing with the two main problems in the field of recognition. These difficulties are the presence of a large variety of observed signals and the presence of interference. One paper reports on a possible feature selection for pattern recognition systems employing the minimization of population entropy. Electronic engineers, physicists, physiologists, psychologists, logicians, mathematicians, and philosophers will find great rewards in reading the above collection.

Table of contents


Contributors

Preface

Remarks on Two Problems Connected with Pattern Recognition

Research on Pattern Recognition in France

Implications of Interactive Graphic Computers for Pattern Recognition Methodology

Statistical Analysis as a Tool to Make Patterns Emerge from Data

Pattern Recognition, The Challenge, Are We Meeting It?

Nonsupervised Learning in Statistical Pattern Recognition

Learning in Pattern Recognition

Parallel Computation in Pattern Recognition

Descriptive Pattern-Analysis Techniques: Potentialities and Problems

On Sequential Pattern Recognition Systems

Introduction to Biological and Mechanical Pattern Recognition

On the Automatic Classification of Fingerprints

Network Properties for Pattern Recognition

Goal-Directed Pattern Recognition

Cluster Formation at Various Perceptual Levels

Recognition, Machine 'Recognition'and Statistical Approaches

Pattern Recognition Applied to the Counting of Nerve Fiber Cross-Sections and Water Droplets

Recognition by Imitating the Process of Pattern Generation

Designing Pattern Categorizers with Extremal Paradigm Information

The Importance of Pattern Recognition for General Purpose Adjustment Systems

Recognition and Action

Some Views on Pattern-Recognition Methodology

The Evaluation of the Statistical Classifier

Adaptive System of Pattern Recognition

Nonparametric Learning and Pattern Recognition Using a Finite Number of States

Feature Selection for Pattern Recognition Systems

A Contribution to the Informational Analysis of Pattern

Pattern Recognition as an Inductive Process

Invariant Recognition of Geometric Shapes

Comments

Name Index

Subject Index

Product details

  • Edition: 1
  • Latest edition
  • Published: January 1, 1969
  • Language: English

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