Pattern Recognition and Application

Pattern Recognition and Application

nptelhrd via YouTube Direct link

Mod-01 Lec-21 Perceptron Criterion (Contd.)

21 of 40

21 of 40

Mod-01 Lec-21 Perceptron Criterion (Contd.)

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Pattern Recognition and Application

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  1. 1 Mod-01 Lec-01 Introduction
  2. 2 Mod-01 Lec-02 Feature Extraction - I
  3. 3 Mod-01 Lec-03 Feature Extraction - II
  4. 4 Mod-01 Lec-04 Feature Extraction - III
  5. 5 Mod-01 Lec-05 Bayes Decision Theory
  6. 6 Mod-01 Lec-06 Bayes Decision Theory (Contd.)
  7. 7 Mod-01 Lec-07 Normal Density and Discriminant Function
  8. 8 Mod-01 Lec-08 Normal Density and Discriminant Function (Contd.)
  9. 9 Mod-01 Lec-09 Bayes Decision Theory - Binary Features
  10. 10 Mod-01 Lec-10 Maximum Likelihood Estimation
  11. 11 Mod-01 Lec-11 Probability Density Estimation
  12. 12 Mod-01 Lec-12 Probability Density Estimation (Contd.)
  13. 13 Mod-01 Lec-13 Probability Density Estimation (Contd. )
  14. 14 Mod-01 Lec-14 Probability Density Estimation ( Contd.)
  15. 15 Mod-01 Lec-15 Probability Density Estimation ( Contd. )
  16. 16 Mod-01 Lec-16 Dimensionality Problem
  17. 17 Mod-01 Lec-17 Multiple Discriminant Analysis
  18. 18 Mod-01 Lec-18 Multiple Discriminant Analysis (Tutorial)
  19. 19 Mod-01 Lec-19 Multiple Discriminant Analysis (Tutorial )
  20. 20 Mod-01 Lec-20 Perceptron Criterion
  21. 21 Mod-01 Lec-21 Perceptron Criterion (Contd.)
  22. 22 Mod-01 Lec-22 MSE Criterion
  23. 23 Mod-01 Lec-23 Linear Discriminator (Tutorial)
  24. 24 Mod-01 Lec-24 Neural Networks for Pattern Recognition
  25. 25 Mod-01 Lec-25 Neural Networks for Pattern Recognition (Contd.)
  26. 26 Mod-01 Lec-26 Neural Networks for Pattern Recognition (Contd. )
  27. 27 Mod-01 Lec-27 RBF Neural Network
  28. 28 Mod-01 Lec-28 RBF Neural Network (Contd.)
  29. 29 Mod-01 Lec-29 Support Vector Machine
  30. 30 Mod-01 Lec-30 Hyperbox Classifier
  31. 31 Mod-01 Lec-31 Hyperbox Classifier (Contd.)
  32. 32 Mod-01 Lec-32 Fuzzy Min Max Neural Network for Pattern Recognition
  33. 33 Mod-01 Lec-33 Reflex Fuzzy Min Max Neural Network
  34. 34 Mod-01 Lec-34 Unsupervised Learning - Clustering
  35. 35 Mod-01 Lec-35 Clustering (Contd.)
  36. 36 Mod-01 Lec-36 Clustering using minimal spanning tree
  37. 37 Mod-01 Lec-37 Temporal Pattern recognition
  38. 38 Mod-01 Lec-38 Hidden Markov Model
  39. 39 Mod-01 Lec-39 Hidden Markov Model (Contd.)
  40. 40 Mod-01 Lec-40 Hidden Markov Model (Contd. )

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