Image processing and pattern association based on supervised learning in neural network ニューラルネットワークに於ける教師付き学習法に基づく画像処理と連想記憶
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著者
書誌事項
- タイトル
-
Image processing and pattern association based on supervised learning in neural network
- タイトル別名
-
ニューラルネットワークに於ける教師付き学習法に基づく画像処理と連想記憶
- 著者名
-
張, 偉
- 著者別名
-
チァン, ウェイ
- 学位授与大学
-
大阪大学
- 取得学位
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工学博士
- 学位授与番号
-
甲第4351号
- 学位授与年月日
-
1991-03-26
注記・抄録
博士論文
目次
- Contents / (0006.jp2)
- Preface / (0004.jp2)
- Acknowledgements / (0005.jp2)
- CHAPTER 1 GENERAL INTRODUCTION / p1 (0009.jp2)
- 1.1 Introduction / p1 (0009.jp2)
- 1.2 General Framework for Neural Network / p4 (0011.jp2)
- 1.3 What Follows... / p10 (0014.jp2)
- CHAPTER 2 LEANING IN FEEDFORWARD MODEL WITH LOCAL SPACE-INVARIANT INTERCONNECTIONS / p13 (0015.jp2)
- 2.1 Introduction / p13 (0015.jp2)
- 2.2 Feedforward Model With Local Space-Invariant Interconnections (FELSI model) / p15 (0016.jp2)
- 2.3 Learning in the FELSI Model / p17 (0017.jp2)
- 2.4 Discussion and Conclusion / p20 (0019.jp2)
- CHAPTER 3 IMAGE PROCESSING BASED ON LEARNING IN THE FELSI MODEL / p22 (0020.jp2)
- 3.1 Introduction / p22 (0020.jp2)
- 3.2 Model for Cell's boundary Detection / p24 (0021.jp2)
- 3.3 Experimental Results / p26 (0022.jp2)
- 3.4 Internal Representation and Structure Function of the FELSI Model for Image Processing / p32 (0025.jp2)
- 3.5 Discussion and Conclusion / p39 (0028.jp2)
- Appendix A: M³F Operator / p40 (0029.jp2)
- Appendix B: Ridge-Finding Processing / p40 (0029.jp2)
- CHAPTER 4 PATTERN CLASSIFICATION USING THE FELSI MODEL / p42 (0030.jp2)
- 4.1. Introduction / p42 (0030.jp2)
- 4.2 Learning for Pattern Classification in the FELSI Model / p42 (0030.jp2)
- 4.3 Simulation Results / p44 (0031.jp2)
- 4.4 Architecture for Optical Implementation of the FELSI Model / p53 (0035.jp2)
- 4.5 Discussion and Conclusion / p57 (0037.jp2)
- CHAPTER 5 LEARNING GENERALIZATION / p58 (0038.jp2)
- 5.1 Introduction / p58 (0038.jp2)
- 5.2 Generalization by Entropy Minimizing / p60 (0039.jp2)
- 5.3 Simplified Learning Algorithm / p63 (0040.jp2)
- 5.4 Simulation Results / p64 (0041.jp2)
- 5.5 Discussion and Conclusion / p69 (0043.jp2)
- CHAPTER 6 BIPOLAR ANALOG OPTICAL ASSOCIATIVE MEMORY (AM) OF HOPFIELD MODEL / p71 (0044.jp2)
- 6.1 Introduction / p71 (0044.jp2)
- 6.2 AM based on the Hopfield Model / p74 (0046.jp2)
- 6.3 Performance Comparison of Different Type AMs / p75 (0046.jp2)
- 6.4 Optoelectronic Implementation of Bipolar Analog AM of Hopfield Model / p77 (0047.jp2)
- 6.5 Discussion and Conclusion / p83 (0050.jp2)
- CHAPTER 7 OPTIMIZING BASED ON THE HOPFIELD MODEL WITH MULTIVALUED NEURONS (HMN) / p85 (0051.jp2)
- 7.1 Introduction / p85 (0051.jp2)
- 7.2 Number Representation in the Hopfiled Model / p86 (0052.jp2)
- 7.3 Hopfield Model With Multistate Neurons (HMN model) / p88 (0053.jp2)
- 7.4 Applications of the HMN Model / p92 (0055.jp2)
- 7.5 Comparing With the Linear Model / p99 (0058.jp2)
- 7.6 Optoelectronic Architecture for Implementation of the HMN Model / p101 (0059.jp2)
- 7.7 Discussion and Conclusion / p103 (0060.jp2)
- CHAPTER 8 CONCLUSION / p104 (0061.jp2)
- References / p108 (0063.jp2)
- List of Publications by the Author / p115 (0066.jp2)
