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Electronics - Neural Networks and Applications

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Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics and Electrical Communication Engineering, IIT Kharagpur.

Self-Study Content
  1. Lec-1 Introduction to Artificial Neural Networks

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  2. Lec-2 Artificial Neuron Model and Linear Regression

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  3. Lec-3 Gradient Descent Algorithm

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  4. Lec-4 Nonlinear Activation Units and Learning Mechanisms

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  5. Lec-5 Learning Mechanisms-Hebbian,Competitive,Boltzmann

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  6. Lec-6 Associative memory

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  7. Lec-7 Associative Memory Model

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  8. Lec-8 Condition for Perfect Recall in Associative Memory

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  9. Lec-9 Statistical Aspects of Learning

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  10. Lec-10 V.C. Dimensions: Typical Examples

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  11. Lec-11 Importance of V.C. Dimensions Structural Risk Minimization

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  12. Lec-12 Single-Layer Perceptions

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  13. Lec-13 Unconstrained Optimization: Gauss-Newtons Method

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  14. Lec-14 Linear Least Squares Filters

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  15. Lec-15 Least Mean Squares Algorithm

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  16. Lec-16 Perceptron Convergence Theorem

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  17. Lec-17 Bayes Classifier&Perceptron: An Analogy

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  18. Lec-18 Bayes Classifier for Gaussian Distribution

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  19. Lec-19 Back Propagation Algorithm

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  20. Lec-20 Practical Consideration in Back Propagation Algorithm

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  21. Lec-21 Solution of Non-Linearly Separable Problems Using MLP

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  22. Lec-22 Heuristics For Back-Propagation

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  23. Lec-23 Multi-Class Classification Using Multi-layered Perceptrons

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  24. Lec-24 Radial Basis Function Networks: Cover's Theorem

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  25. Lec-25 Radial Basis Function Networks: Separability&Interpolation

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  26. Lec-26 Radial Basis Function as ill-Posed Surface Reconstruc

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  27. Lec-27 Solution of Regularization Equation: Greens Function

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  28. Lec-28 Use of Greens Function in Regularization Networks

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  29. Lec-29 Regularization Networks and Generalized RBF

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  30. Lec-30 Comparison Between MLP and RBF

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  31. Lec-31 Learning Mechanisms in RBF

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  32. Lec-32 Introduction to Principal Components and Analysis

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  33. Lec-33 Dimensionality reduction Using PCA

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  34. Lec-34 Hebbian-Based Principal Component Analysis

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  35. Lec-35 Introduction to Self Organizing Maps

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  36. Lec-36 Cooperative and Adaptive Processes in SOM

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

  37. Lec-37 Vector-Quantization Using SOM

    Lecture Series on Neural Networks and Applications by Prof.S. Sengupta, Department of Electronics an

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