Weekly outline

  • 1. 12 September - 18 September

    課程內容簡介、學期評分方式說明。

    • 2. 19 September - 25 September

      Introduction (I)

      1.1 History
      1.2 Biological neural networks

      • 3. 26 September - 2 October

        Introduction (II)

        1.3 Artificial intelligence and neural networks

        • 4. 3 October - 9 October

          Supervised Learning Network (I)

          2.1 Single-Layer Networks (Adalines)
          a. Single-Layer Perceptrons (SLPs)
          b. Optimization Method (Least-Square Learning Rule )

          • 5. 10 October - 16 October

            Supervised Learning Network (II)

            2.2 Multi-Layer Networks (Madalines)
            a. Multi-Layer Perceptrons (MLPs)
            b. Optimization Method ( Back propagation, Conjugate Gradient method, Levenberg-Marquardt (LM) method
            2.3 Radial-Basis Networks

            • 6. 17 October - 23 October

              Supervised Learning Network (III)

              2.4 Cascade-Correlation Networks
              2.5 Polynomial Networks

              • 7. 24 October - 30 October

                Supervised Learning Network (IV)

                2.6 Recurrent Networks (Time series, Back propagation through time, Finite Impulse Response (FIR) MLP ), Temporal Differences method (TD).

                • 8. 31 October - 6 November

                  Unsupervised Learning Network (I)

                  3.1 Simple Competitive Networks: Winner-take-all
                  3.2 Counter propagation Networks (CPN)

                  • 9. 7 November - 13 November

                    期中考

                    • 10. 14 November - 20 November

                      Unsupervised Learning Network (II)

                      3.3 Hamming Network
                      3.4 Principal Component Analysis and Hebbian Learning (PCA).

                      • 11. 21 November - 27 November

                        Unsupervised Learning Network (III)

                        3.5 Learning Vector Quantization (LVQ)
                        3.6 Adaptive Resonance Theory (ART)

                        • 12. 28 November - 4 December

                          Unsupervised Learning Network (III)

                          3.7 Learning Vector Quantization (LVQ)
                          3.8 Kohonen Self-Organizing Maps (SOMs)

                          • 13. 5 December - 11 December

                            Others

                            4.1 The Discrete Hopfield Net
                            4.2 Neural Network Based Control

                            • 14. 12 December - 18 December

                              Others

                              4.3 Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
                              4.4 Neural Networks and the Soft Computing

                              • 15. 19 December - 25 December

                                Final report (I)

                                分組討論、專題報告

                                • 16. 26 December - 1 January

                                  Final report (I)

                                  分組討論、專題報告



                                  • 17. 2 January - 8 January

                                    開國紀念日(放假)

                                    課程暫停一次。


                                    • 18. 9 January - 15 January

                                      Final report (II)

                                      分組討論、專題報告