Methodologies of Pattern Recognition
eBook - PDF

Methodologies of Pattern Recognition

  1. 590 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Methodologies of Pattern Recognition

About this book

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.

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Yes, you can access Methodologies of Pattern Recognition by Satosi Watanabe in PDF and/or ePUB format, as well as other popular books in Mathematics & Mathematics General. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2014
Print ISBN
9781483230931
eBook ISBN
9781483268989
Topic
Mathematics
Subtopic
Mathematics General
Index
Mathematics

Table of contents

  1. Front Cover
  2. Methodologies of Pattern Recognition
  3. Copyright Page
  4. Table of Contents
  5. CONTRIBUTORS
  6. PREFACE
  7. CHAPTER 1. REMARKS ON TWO PROBLEMS CONNECTED WITH PATTERN RECOGNITION
  8. CHAPTER 2. RESEARCH ON PATTERN RECOGNITION IN FRANCE
  9. CHAPTER 3. IMPLICATIONS OF INTERACTIVE GRAPHIC COMPUTERS FOR PATTERN RECOGNITION METHODOLOGY
  10. CHAPTER 4. STATISTICAL ANALYSIS AS A TOOL TO MAKE PATTERNS EMERGE FROM DATA
  11. CHAPTER 5. PATTERN RECOGNITION, THE CHALLENGE, ARE WE MEETING IT?
  12. CHAPTER 6. NONSUPERVISED LEARNING IN STATISTICAL PATTERN RECOGNITION
  13. CHAPTER 7. LEARNING IN PATTERN RECOGNITION
  14. CHAPTER 8. PARALLEL COMPUTATION IN PATTERN RECOGNITION
  15. CHAPTER 9. DESCRIPTIVE PATTERN-ANALYSIS TECHNIQUES: POTENTIALITIES AND PROBLEMS
  16. CHAPTER 10. ON SEQUENTIAL PATTERN RECOGNITION SYSTEMS
  17. CHAPTER 11. INTRODUCTION TO BIOLOGICAL AND MECHANICAL PATTERN RECOGNITION
  18. CHAPTER 12. ON THE AUTOMATIC CLASSIFICATION OF FINGERPRINTS -SOME CONSIDERATIONS ON THE LINGUISTIC INTERPRETATION OF PICTURES
  19. CHAPTER 13. NETWORK PROPERTIES FOR PATTERN RECOGNITION
  20. CHAPTER 14. GOAL-DIRECTED PATTERN RECOGNITION
  21. CHAPTER 15. CLUSTER FORMATION AT VARIOUS PERCEPTUAL LEVELS
  22. CHAPTER 16. RECOGNITION, MACHINE "RECOGNITION", AND STATISTICAL APPROACHES
  23. CHAPTER 17. PATTERN RECOGNITION APPLIED TO THE COUNTING OF NERVE FIBER CROSS-SECTIONS AND WATER DROPLETS
  24. CHAPTER 18. RECOGNITION BY IMITATING THE PROCESS OF PATTERN GENERATION
  25. CHAPTER 19. DESIGNING PATTERN CATEGORIZERS WITH EXTREMAL PARADIGM INFORMATION
  26. CHAPTER 20. THE IMPORTANCE OF PATTERN RECOGNITION FOR GENERAL PURPOSE ADJUSTMENT SYSTEMS
  27. CHAPTER 21. RECOGNITION AND ACTION
  28. CHAPTER 22. SOME VIEWS ON PATTERNā€”RECOGNITION METHODOLOGY
  29. CHAPTER 23. THE EVALUATION OF THE STATISTICAL CLASSIFIER
  30. CHAPTER 24. ADAPTIVE SYSTEM OF PATTERN RECOGNITION
  31. CHAPTER 25. NONPARAMETRIC LEARNING AND PATTERN RECOGNITION USING A FINITE NUMBER OF STATES
  32. CHAPTER 26. FEATURE SELECTION FOR PATTERN RECOGNITION SYSTEMS
  33. CHAPTER 27. A CONTRIBUTION TO THE INFORMATIONAL ANALYSIS OF PATTERN
  34. CHAPTER 28. PATTERN RECOGNITION AS AN INDUCTIVE PROCESS
  35. CHAPTER 29. INVARIANT RECOGNITION OF GEOMETRIC SHAPES
  36. COMMENTS
  37. NAME INDEX
  38. SUBJECT INDEX