Neural networks for identification, prediction and control:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | German |
| Veröffentlicht: |
London u.a.
Springer
1995
|
| Ausgabe: | 2. printing |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 238 S. zahlr. graph. Darst. |
| ISBN: | 3540199594 |
Internformat
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Datensatz im Suchindex
| DE-BY-862_location | 2000 |
|---|---|
| DE-BY-FWS_call_number | 2000/ST 300 P534 |
| DE-BY-FWS_katkey | 143847 |
| DE-BY-FWS_media_number | 083000216032 |
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| adam_text | I
DUC TRUONG PHAM AND LIU XING
NEURAL NETWORKS FOR IDENTIFICATION,
PREDICTION AND CONTROL
WITH 98 FIGURES
LONDON BERLIN HEIDELBERG NEW YORK
PARIS TOKYO HONGKONG
BARCELONA BUDAPEST
CONTENTS
CHAPTER 1 ARTIFICIAL NEURAL NETWORKS 1
1.1 TYPES OF NEURAL NETWORKS 1
1.1.1 STRUCTURAL CATEGORISATION 1
1.1.2 LEARNING ALGORITHM CATEGORISATION 2
1.2 EXAMPLE NEURAL NETWORKS 3
1.2.1 MULTI-LAYER PERCEPTRON (MLP) 4
1.2.2 LEARNING VECTOR QUANTIZATION (LVQ) NETWORK 7
1.2.3 CMACNETWORK 9
1.2.4 GROUP METHOD OF DATA HANDLING (GMDH) NETWORK 12
1.2.5 HOPFIELD NETWORK 15
1.2.6 ELMAN AND JORDAN NETS 16
1.2.7 KOHONEN NETWORK 17
1.2.8 ARTNETWORK 19
1.3 SUMMARY 21
REFERENCES 21
CHAPTER 2 DYNAMIC SYSTEM IDENTIFICATION USING
FEEDFORWARD NEURAL NETWORKS 25
2.1 DYNAMIC SYSTEM DESCRIPTIONS 25
2.1.1 INPUT-OUTPUT MODEL 25
2.1.2 STATE-SPACE MODEL 26
2.2 IDENTIFICATION BASED ON SYSTEM INPUTS AND OUTPUTS 27
2.3 IDENTIFICATION BASED ON MEASURABLE SYSTEM STATES 29
2.4 INPUT-OUTPUT MODEL IDENTIFICATION 30
2.4.1 SIMULATION INVESTIGATIONS 31
2.4.2 RESULTS 36
2.5 STATE-SPACE MODEL IDENTIFICATION 39
XII CONTENTS
2.5.1 PLANT MODEL AND IDENTIFICATION ARCHITECTURE 39
2.5.2 SIMULATIONS 41
2.6 DISCUSSION 41
2.6.1 HYBRID NETWORKS 41
2.6.2 INPUT-OUTPUT VERSUS STATE-SPACE MODELLING 42
2.7 ANALYSIS OFTHE HYBRID NETWORK 43
2.8 SUMMARY 44
REFERENCES 45
CHAPTER 3 DYNAMIC SYSTEM MODELLING USING
RECURRENT NEURAL NETWORKS 47
3.1 BASIC ELMAN NETWORK 48
3.1.1 STRUCTURE AND PRINCIPLEOF ELMAN NETWORK 48
3.1.2 ANALYSIS OF ELMAN NETWORK 49
3.2 MODIFIED ELMAN NETWORK 51
3.3 DYNAMIC SYSTEM MODELLING 52
3.4 FURTHER ANALYSIS OF ELMAN NETWORKS 56
3.4.1 DYNAMIC BACKPROPAGATION IN ELMAN NETWORKS 56
3.4.2 RELATION WITH THE MODIFIED ELMAN NETWORK 58
3.5 SUMMARY 60
REFERENCES 60
CHAPTER 4 MODELLING AND PREDICTION USING GMDH NETWORKS 63
4.1 N-ADALINE NETWORKS AND WIDROW-HOFF LEARNING 64
4.2 GMDH NETWORK BASED ON N-ADALINES 65
4.3 APPLICATIONS 69
4.4 DISCUSSION 80
4.5 SUMMARY 81
REFERENCES 81
CHAPTER 5 FINANCIAL PREDICTION USING NEURAL NETWORKS 83
5.1 STOCK MARKET PREDICTION 83
5.1.1 SYSTEM OVERVIEW 84
5.1.2 PREDICTION SIMULATION 85
5.2 CURRENCY EXCHANGE RATE PREDICTION 86
5.2.1 PREDICTION BASED ON NEURAL NETWORKS 87
5.3 DATA SETS ADOPTED FOR SIMULATION 89
CONTENTS
XIU
5.4 PREDICTION BASED ON GMDH NETWORKS 93
5.5 PREDICTION BASED ON MULTILAYER PERCEPTRON NETWORKS 99
5.6 PREDICTION BASED ON RECURRENT NETWORKS 103
5.7 DISCUSSION 107
5.8 SUMMARY
109
REFERENCES HO
CHAPTER 6 NEURAL NETWORK CONTROLLERS HL
6.1 NEURAL NETWORK CONTROLLERS 112
6.1.1 CMAC 112
6.1.2 HIERARCHICAL NEURAL NETWORK MODEL 116
6.1.3 MULTILAYERED NEURAL NETWORK CONTROLLER 119
6.2 COMPARISON OF NEURAL NETWORK CONTROLLERS 122
6.2.1 HIERARCHICAL NEURAL NETWORK MODEL AND
MULTILAYERED NEURAL NETWORK CONTROLLER 122
6.2.2 MULTILAYERED NEURAL NETWORK CONTROLLER (OR
HIERARCHICAL NEURAL NETWORK MODEL) AND CMAC 123
6.2.3 COMMON ASPECTS OF NEURAL NETWORK CONTROLLERS 124
6.2.4 COMPARISON WITH ADAPTIVE CONTROLLERS 124
6.3 SUMMARY 126
REFERENCES 126
CHAPTER 7 NEUROMORPHIC FUZZY CONTROLLER DESIGN 131
7.1 INTEGRATING NEURAL NETWORKS AND FLCS 131
7.1.1 REPRESENTATION OF A SIMPLE FUZZY LOGIC CONTROLLER
AS A NEURAL NETWORK 132
7.1.2 LEARNING ALGORITHM 135
7.2 RESULTS OF NEUROMORPHIC FUZZY CONTROLLERS DESIGN 137
7.2.1 PLANT 1 137
7.2.2 PLANT2 140
7.3 SUMMARY 142
REFERENCES 142
CHAPTER 8 ROBOT MANIPULATOR CONTROL USING NEURAL NETWORKS 143
8.1 MODELLINGOFAMULTI-JOINT ROBOT 144
8.2 CONTROL SYSTEM 147
8.3 APPLICATION TO A TWO-JOINT ROBOT ARM 149
XIV CONTENTS
8.4 DISCUSSION 158
8.5 SUMMARY 163
REFERENCES 164
APPENDIX A INTRODUCTION TO SOME CONVENTIONAL
TECHNIQUES OF IDENTIFICATION, PREDICTION AND CONTROL 167
APPENDIX B FUZZY SETS AND FUZZY LOGIC CONTROL 177
APPENDIX C GENETIC ALGORITHMS 189
APPENDIX D PROGRAM: FEEDFORWARD NETWORK FOR
SYSTEM IDENTIFICATION 197
APPENDIX E PROGRAM: MODIFIED ELMAN NETWORK FOR
IDENTIFICATION 207
APPENDIX F PROGRAM: GMDH NETWORK FOR PREDICTION 217
AUTHOR INDEX 231
SUBJECT INDEX 235
|
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| id | DE-604.BV010332888 |
| illustrated | Illustrated |
| indexdate | 2024-08-01T10:39:09Z |
| institution | BVB |
| isbn | 3540199594 |
| language | German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-006877111 |
| oclc_num | 32236242 |
| open_access_boolean | |
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| physical | XIV, 238 S. zahlr. graph. Darst. |
| publishDate | 1995 |
| publishDateSearch | 1995 |
| publishDateSort | 1995 |
| publisher | Springer |
| record_format | marc |
| spellingShingle | Pham, Duc Truong 1952- Liu, Xing Neural networks for identification, prediction and control Controlesystemen gtt Neurale netwerken gtt Voorspellingen gtt Neural networks (Computer science) Systemidentifikation (DE-588)4121753-6 gnd Neuronales Netz (DE-588)4226127-2 gnd Prädiktive Regelung (DE-588)4271836-3 gnd Identifikation (DE-588)4072712-9 gnd Zukunft (DE-588)4068097-6 gnd Kontrollsystem (DE-588)4126040-5 gnd Regler (DE-588)4140088-4 gnd |
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| title | Neural networks for identification, prediction and control |
| title_auth | Neural networks for identification, prediction and control |
| title_exact_search | Neural networks for identification, prediction and control |
| title_full | Neural networks for identification, prediction and control Duc Truong Pham and Liu Xiang |
| title_fullStr | Neural networks for identification, prediction and control Duc Truong Pham and Liu Xiang |
| title_full_unstemmed | Neural networks for identification, prediction and control Duc Truong Pham and Liu Xiang |
| title_short | Neural networks for identification, prediction and control |
| title_sort | neural networks for identification prediction and control |
| topic | Controlesystemen gtt Neurale netwerken gtt Voorspellingen gtt Neural networks (Computer science) Systemidentifikation (DE-588)4121753-6 gnd Neuronales Netz (DE-588)4226127-2 gnd Prädiktive Regelung (DE-588)4271836-3 gnd Identifikation (DE-588)4072712-9 gnd Zukunft (DE-588)4068097-6 gnd Kontrollsystem (DE-588)4126040-5 gnd Regler (DE-588)4140088-4 gnd |
| topic_facet | Controlesystemen Neurale netwerken Voorspellingen Neural networks (Computer science) Systemidentifikation Neuronales Netz Prädiktive Regelung Identifikation Zukunft Kontrollsystem Regler |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006877111&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT phamductruong neuralnetworksforidentificationpredictionandcontrol AT liuxing neuralnetworksforidentificationpredictionandcontrol |
Inhaltsverzeichnis
THWS Schweinfurt Zentralbibliothek Lesesaal
| Signatur: |
2000 ST 300 P534 |
|---|---|
| Exemplar 1 | ausleihbar Verfügbar Bestellen |