Ying-Qian Zhang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 115-124). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Objective --- p.2 / Chapter 1.3 --- Contributions --- p.3 / Chapter 1.4 --- Thesis Overview --- p.4 / Chapter 2 --- Literature Review --- p.6 / Chapter 2.1 --- Takens' Theorem --- p.6 / Chapter 2.2 --- Linear Models for Prediction --- p.7 / Chapter 2.2.1 --- Autoregressive Model --- p.7 / Chapter 2.2.2 --- Moving Average Model --- p.8 / Chapter 2.2.3 --- Autoregressive-moving Average Model --- p.9 / Chapter 2.2.4 --- Fitting a Linear Model to a Given Time Series --- p.9 / Chapter 2.2.5 --- State-space Reconstruction --- p.10 / Chapter 2.3 --- Neural Network Models for Time Series Processing --- p.11 / Chapter 2.3.1 --- Feed-forward Neural Networks --- p.11 / Chapter 2.3.2 --- Recurrent Neural Networks --- p.14 / Chapter 2.3.3 --- Training Algorithms for Recurrent Networks --- p.18 / Chapter 2.4 --- Combining Neural Networks and other approximation techniques --- p.22 / Chapter 3 --- ForeNet: Model and Representation --- p.24 / Chapter 3.1 --- Fourier Recursive Prediction Equation --- p.24 / Chapter 3.1.1 --- Fourier Analysis of Time Series --- p.25 / Chapter 3.1.2 --- Recursive Form --- p.25 / Chapter 3.2 --- Fourier Recurrent Neural Network Model (ForeNet) --- p.27 / Chapter 3.2.1 --- Neural Networks Representation --- p.28 / Chapter 3.2.2 --- Architecture of ForeNet --- p.29 / Chapter 4 --- ForeNet: Implementation --- p.32 / Chapter 4.1 --- Improvement on ForeNet --- p.33 / Chapter 4.1.1 --- Number of Hidden Neurons --- p.33 / Chapter 4.1.2 --- Real-valued Outputs --- p.34 / Chapter 4.2 --- Parameters Initialization --- p.37 / Chapter 4.3 --- Application of ForeNet: the Process of Time Series Prediction --- p.38 / Chapter 4.4 --- Some Implications --- p.39 / Chapter 5 --- ForeNet: Initialization --- p.40 / Chapter 5.1 --- Unfolded Form of ForeNet --- p.40 / Chapter 5.2 --- Coefficients Analysis --- p.43 / Chapter 5.2.1 --- "Analysis of the Coefficients Set, vn " --- p.43 / Chapter 5.2.2 --- "Analysis of the Coefficients Set, μn(d) " --- p.44 / Chapter 5.3 --- Experiments of ForeNet Initialization --- p.47 / Chapter 5.3.1 --- Objective and Experiment Setting --- p.47 / Chapter 5.3.2 --- Prediction of Sunspot Series --- p.49 / Chapter 5.3.3 --- Prediction of Mackey-Glass Series --- p.53 / Chapter 5.3.4 --- Prediction of Laser Data --- p.56 / Chapter 5.3.5 --- Three More Series --- p.59 / Chapter 5.4 --- Some Implications on the Proposed Initialization Method --- p.63 / Chapter 6 --- ForeNet: Learning Algorithms --- p.67 / Chapter 6.1 --- Complex Real Time Recurrent Learning (CRTRL) --- p.68 / Chapter 6.2 --- Batch-mode Learning --- p.70 / Chapter 6.3 --- Time Complexity --- p.71 / Chapter 6.4 --- Property Analysis and Experimental Results --- p.72 / Chapter 6.4.1 --- Efficient initialization:compared with random initialization --- p.74 / Chapter 6.4.2 --- Complex-valued network:compared with real-valued net- work --- p.78 / Chapter 6.4.3 --- Simple architecture:compared with ring-structure RNN . --- p.79 / Chapter 6.4.4 --- Linear model: compared with nonlinear ForeNet --- p.80 / Chapter 6.4.5 --- Small number of hidden units --- p.88 / Chapter 6.5 --- Comparison with Some Other Models --- p.89 / Chapter 6.5.1 --- Comparison with AR model --- p.91 / Chapter 6.5.2 --- Comparison with TDNN Networks and FIR Networks . --- p.93 / Chapter 6.5.3 --- Comparison to a few more results --- p.94 / Chapter 6.6 --- Summarization --- p.95 / Chapter 7 --- Learning and Prediction: On-Line Training --- p.98 / Chapter 7.1 --- On-Line Learning Algorithm --- p.98 / Chapter 7.1.1 --- Advantages and Disadvantages --- p.98 / Chapter 7.1.2 --- Training Process --- p.99 / Chapter 7.2 --- Experiments --- p.101 / Chapter 7.3 --- Predicting Stock Time Series --- p.105 / Chapter 8 --- Discussions and Conclusions --- p.109 / Chapter 8.1 --- Limitations of ForeNet --- p.109 / Chapter 8.2 --- Advantages of ForeNet --- p.111 / Chapter 8.3 --- Future Works --- p.112 / Bibliography --- p.115
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323478 |
| Date | January 2001 |
| Contributors | Zhang, Ying-Qian., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, xi, 124 leaves : ill. (some col.) ; 30 cm. |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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