Blind equalization in neural networks: theory, algorithms and applications
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
De Gruyter
[2018]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XI, 255 Seiten Illustrationen, Diagramme |
| ISBN: | 9783110449624 |
Internformat
MARC
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| 020 | |a 9783110449624 |c hbk |9 978-3-11-044962-4 | ||
| 035 | |a (OCoLC)1022087739 | ||
| 035 | |a (DE-599)DNB1135497133 | ||
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| 100 | 1 | |a Zhang, Liyi |e Verfasser |0 (DE-588)1014359791 |4 aut | |
| 245 | 1 | 0 | |a Blind equalization in neural networks |b theory, algorithms and applications |c Liyi Zhang, Yunshan Sun, Xiaoqin Zhang, Yu Bai |
| 264 | 1 | |a Berlin |b De Gruyter |c [2018] | |
| 264 | 4 | |c © 2018 | |
| 300 | |a XI, 255 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 0 | 7 | |a Neuronales Netz |0 (DE-588)4226127-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Adaptive Entzerrung |0 (DE-588)4141376-3 |2 gnd |9 rswk-swf |
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| 700 | 1 | |a Sun, Yunshan |e Verfasser |4 aut | |
| 700 | 1 | |a Zhang, Xiaoqin |e Verfasser |4 aut | |
| 700 | 1 | |a Bai, Yu |e Verfasser |4 aut | |
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Datensatz im Suchindex
| _version_ | 1804178226027692032 |
|---|---|
| adam_text | CONTENTS
1 INTRODUCTION* 1
1.1 THE RESEARCH SIGNIFICANCE OF THE BE TECHNOLOGY* 1
1.2 THE APPLICATION OF BE TECHNOLOGY* 3
1.2.1 THE APPLICATION IN DIGITAL TELEVISION * 3
1.2.2 THE APPLICATION IN CATV SYSTEM * 3
1.2.3 THE APPLICATION IN SMART ANTENNA * 4
1.2.4 THE APPLICATION IN SOFTWARE RADIO * 4
1.2.5 THE APPLICATION IN BLIND IMAGE RESTORATION * 5
1.2.6 THE APPLICATION IN RADIOFREQUENCY IDENTIFICATION * 5
1.3 THE RESEARCH PROGRESS OF NEURAL NETWORK BE ALGORITHM *
6
1.3.1 THE FFNN BE ALGORITHM
-----
6
1.3.2 THE BE ALGORITHM BASED ON FBNN * 10
1.3.3 THE FNN BE ALGORITHM * 11
1.3.4 THE ENN BE ALGORITHM
-----
13
1.3.5 BE ALGORITHM BASED ON WNN * 14
1.4 THE RESEARCH BACKGROUND AND STRUCTURE * 14
1.4.1 THE RESEARCH BACKGROUND * 14
1.4.2 THE STRUCTURE OF THE BOOK* 15
2 THE FUNDAMENTAL THEORY OF NEURAL NETWORK BLIND EQUALIZATION
ALGORITHM
-----
17
2.1 THE FUNDAMENTAL PRINCIPLE OF BLIND EQUALIZATION* 17
2.1.1 THE CONCEPT OF BLIND EQUALIZATION* 17
2.1.2 THE STRUCTURE OF BLIND EQUALIZER* 18
2.1.3 THE BASIC ALGORITHM OF BLIND EQUALIZATION * 19
2.1.4 THE EQUALIZATION CRITERIA OF BLIND EQUALIZATION * 22
2.2 THE FUNDAMENTAL THEORY OF NEURAL NETWORK * 27
2.2.1 THE CONCEPT OF ARTIFICIAL NEURAL NETWORK* 27
2.2.2 THE DEVELOPMENT OF ANN
-----
28
2.2.3 THE CHARACTERISTICS OF ANN * 29
2.2.4 STRUCTURE AND CLASSIFICATION OF ANN * 30
2.3 THE FUNDAMENTAL PRINCIPLE OF NEURAL NETWORK BLIND EQUALIZATION
ALGORITHM * 32
2.3.1 THE PRINCIPLE OF BLIND EQUALIZATION ALGORITHM BASED ON NEURAL
NETWORK
FILTE R* 32
2.3.2 THE PRINCIPLE OF BLIND EQUALIZATION ALGORITHM BASED ON NEURAL
NETWORK
CONTROLLER* 32
2.3.3 THE PRINCIPLE OF BLIND EQUALIZATION ALGORITHM BASED ON NEURAL
NETWORK
CONTROLLER CLASSIFIER* 33
2.4 THE LEARNING METHOD OF NEURAL NETWORK BLIND EQUALIZATION
ALGORITHM * 34
2.4.1 THE BP ALGORITHM * 34
2.4.2 THE IMPROVED BP ALGORITHM * 36
2.5 THE EVALUATION INDEX OF THE NEURAL NETWORK BLIND EQUALIZATION
ALGORITHM * 42
2.5.1 CONVERGENCE SPEED * 43
2.5.2 THE COMPUTATIONAL COMPLEXITY
-----
43
2.5.3 THE BIT ERROR CHARACTERISTICS * 43
2.5.4 THE ABILITY OF TRACKING THE TIME-VARYING CHANNEL * 43
2.5.5 THE ABILITY OF ANTI INTERFERENCE * 43
2.5.6 THE CONVEXITY OF THE COST FUNCTION * 44
2.5.7 THE STEADY-STATE RESIDUAL ERROR* 45
2.6 SUMMARY* 50
3 RESEARCH OF BLIND EQUALIZATION ALGORITHMS BASED ON FFNN * 51
3.1 BASIC PRINCIPLES OF FFNN * 51
3.1.1 CONCEPT OF FFNN
-----
51
3.1.2 STRUCTURE OF FFNN * 51
3.1.3 CHARACTERISTICS OF FFNN * 52
3.2 BLIND EQUALIZATION ALGORITHM BASED ON THE THREE-LAYER FFNN * 52
3.2.1 MODEL OF THE THREE-LAYER FFNN
-----
52
3.2.2 REAL BLIND EQUALIZATION ALGORITHM BASED
ON THE THREE-LAYER FFNN * 53
3.2.3 COMPLEX BLIND EQUALIZATION ALGORITHM BASED ON THE THREE-LAYER
FFNN
-----
56
3.3 BLIND EQUALIZATION ALGORITHM BASED ON THE MULTILAYER FFNN * 63
3.3.1 CONCEPT OF THE MULTILAYER FFNN * 63
3.3.2 BLIND EQUALIZATION ALGORITHM BASED ON THE FOUR-LAYER FFNN * 64
3.3.3 BLIND EQUALIZATION ALGORITHM BASED ON THE FIVE-LAYER FFNN * 70
3.4 BLIND EQUALIZATION ALGORITHM BASED ON THE MOMENTUM TERM FFNN * 78
3.4.1 BASIC PRINCIPLES OF ALGORITHM * 78
3.4.2 DERIVATION OF ALGORITHM * 80
3.4.3 COMPUTER SIMULATION RESULTS * 82
3.5 BLIND EQUALIZATION ALGORITHM BASED ON THE TIME-VARYING MOMENTUM TERM
FFNN
-----
84
3.5.1 BASIC PRINCIPLES OF ALGORITHM * 84
3.5.2 DERIVATION OF ALGORITHM * 86
3.5.3 COMPUTER SIMULATION RESULTS * 87
3.6 BLIND EQUALIZATION ALGORITHM BASED ON VARIABLE STEP-SIZE FFNN * 88
3.6.1 BASIC PRINCIPLES OF ALGORITHM * 88
3.6.2 DERIVATION OF ALGORITHM * 90
3.6.3 COMPUTER SIMULATION RESULTS * 91
3.7 SUMMARY* 92
4 RESEARCH OF BLIND EQUALIZATION ALGORITHMS BASED ON THE FBNN * 94
4.1 BASIC PRINCIPLES OF FBNN * 94
4.1.1 CONCEPT OF FBNN
-----
94
4.1.2 STRUCTURE OF FBNN
-----
94
4.1.3 CHARACTERISTICS OF FBNN * 94
4.2 BLIND EQUALIZATION ALGORITHM BASED ON THE BILINEAR RECURRENT NN * 95
4.2.1 BASIC PRINCIPLES OF ALGORITHM * 95
4.2.2 REAL BLIND EQUALIZATION ALGORITHM BASED ON BLRNN * 96
4.2.3 COMPLEX BLIND EQUALIZATION ALGORITHM BASED ON BLRNN * 99
4.3 BLIND EQUALIZATION ALGORITHM BASED ON THE DIAGONAL RECURRENT NN *
103
4.3.1 MODEL OF DIAGONAL RECURRENT NN * 103
4.3.2 DERIVATION OF ALGORITHM * 105
4.3.3 COMPUTER SIMULATION RESULTS * 106
4.4 BLIND EQUALIZATION ALGORITHM BASED ON THE QUASI-DRNN * 107
4.4.1 MODEL OF QUASI-DRNN
-----
107
4.4.2 DERIVATION OF ALGORITHM * 110
4.4.3 COMPUTER SIMULATION RESULTS * 112
4.5 BLIND EQUALIZATION ALGORITHM BASED ON THE VARIABLE STEP-SIZE
DRNN
-----
115
4.5.1 BASIC PRINCIPLES OF ALGORITHM * 115
4.5.2 DERIVATION OF ALGORITHM * 115
4.5.3 COMPUTER SIMULATION RESULTS * 116
4.6 BLIND EQUALIZATION ALGORITHM BASED ON THE VARIABLE STEP-SIZE
QDRNN * 119
4.6.1 BASIC PRINCIPLES OF ALGORITHM * 119
4.6.2 DERIVATION OF ALGORITHM * 119
4.6.3 COMPUTER SIMULATION RESULTS
-----
120
4.7 SUMMARY* 123
5 RESEARCH OF BLIND EQUALIZATION ALGORITHMS BASED ON FNN * 124
5.1 BASIC PRINCIPLES OF FNN * 124
5.1.1 CONCEPT OF FNN
-----
124
5.1.2 STRUCTURE OF FNN
-----
125
5.1.3 THE CHOICE OF FUZZY MEMBERSHIP FUNCTION* 126
5.1.4 LEARNING ALGORITHM OF FNN * 128
5.1.5 CHARACTERISTICS OF FNN * 128
5.2 BLIND EQUALIZATION ALGORITHM BASED ON THE FNN FILTER* 129
5.2.1 BASIC PRINCIPLES OF ALGORITHM * 129
5.2.2 DERIVATION OF ALGORITHM * 129
5.2.3 COMPUTER SIMULATION RESULTS * 133
5.3 BLIND EQUALIZATION ALGORITHM BASED ON THE FNN CONTROLLER* 134
5.3.1 BASIC PRINCIPLES OF THE ALGORITHM* 134
5.3.2 DERIVATION OF ALGORITHM * 135
5.3.3 COMPUTER SIMULATION RESULTS * 139
5.4 BLIND EQUALIZATION ALGORITHM BASED ON THE FNN CLASSIFIER* 141
5.4.1 BASIC PRINCIPLES OF ALGORITHM * 141
5.4.2 DERIVATION OF ALGORITHM * 141
5.4.3 COMPUTER SIMULATION RESULTS* 146
5.5 SUMMARY* 147
6 BLIND EQUALIZATION ALGORITHM BASED ON EVOLUTIONARY NEURAL NETWORK *
149
6.1 BASIC PRINCIPLES OF EVOLUTIONARY NEURAL NETWORKS * 149
6.1.1 THE CONCEPT OF GA* 149
6.1.2 DEVELOPMENT OF GA* 150
6.1.3 GA PARAMETERS * 151
6.1.4 THE BASIC PROCESS OF GA * 157
6.1.5 CHARACTERISTICS OF GA* 158
6.1.6 THE INTEGRATION MECHANISM OF GA AND NEURAL NETWORK * 158
6.2 BLIND EQUALIZATION ALGORITHM BASED ON NEURAL NETWORK WEIGHTS
OPTIMIZED
BYGA
-----
159
6.2.1 THE BASIC ALGORITHM PRINCIPLE * 159
6.2.2 FEED-FORWARD NEURAL NETWORK WEIGHTS OPTIMIZED BY GA BLIND
EQUALIZATION
ALGORITHM (GA-FFNNW) IN BINARY ENCODING* 160
6.2.3 REAL ENCODING GA-FFNNW BLIND EQUALIZATION ALGORITHM * 167
6.3 GA OPTIMIZATION NEURAL NETWORK STRUCTURE BLIND EQUALIZATION
ALGORITHM
(GA-FFNNS)
-----
172
6.3.1 THE BASIC ALGORITHM PRINCIPLE * 172
6.3.2 ALGORITHM DERIVATION * 173
6.3.3 COMPUTER SIMULATION * 175
6.4 SUMMARY* 179
7 BLIND EQUALIZATION ALGORITHM BASED ON WAVELET NEURAL NETWORK * 180
7.1 BASIC PRINCIPLE OF WAVELET NEURAL NETWORK* 180
7.1.1 THE CONCEPT OF WAVELET NEURAL NETWORK* 180
7.1.2 THE STRUCTURE OF WAVELET NEURAL NETWORK* 181
7.1.3 THE CHARACTERISTICS OF WAVELET NEURAL NETWORK * 182
7.2 BLIND EQUALIZATION ALGORITHM BASED ON FEED-FORWARD WAVELET NEURAL
NETWORK* 182
7.2.1 ALGORITHM PRINCIPLE * 182
7.2.2 BLIND EQUALIZATION ALGORITHM BASED ON FEED-FORWARD WAVELET NEURAL
NETWORK IN REAL NUMBER SYSTEM * 183
7.2.3 BLIND EQUALIZATION ALGORITHM BASED ON FFWNN IN COMPLEX NUMBER
SYSTEM * 187
7.3 BLIND EQUALIZATION ALGORITHM BASED ON RECURRENT WAVELET NEURAL
NETWORK* 194
7.3.1 PRINCIPLE OF ALGORITHM * 194
7.3.2 BLIND EQUALIZATION ALGORITHM BASED ON BLRWNN IN REAL NUMBER
SYSTEM * 194
7.3.3 BLIND EQUALIZATION ALGORITHM BASED ON BLRWNN IN COMPLEX
SYSTEM * 198
7.4 SUMMARY* 204
8 APPLICATION OF NEURAL NETWORK BLIND EQUALIZATION ALGORITHM IN MEDICAL
IMAGE
PROCESSING * 205
8.1 CONCEPT OF IMAGE BLIND EQUALIZATION * 205
8.1.1 IMAGING MECHANISM AND DEGRADATION PROCESS OF MEDICAL
CT IMAGE * 205
8.1.2 THE BASIC PRINCIPLE OF MEDICAL CT IMAGES BLIND EQUALIZATION * 207
8.1.3 QUANTITATIVE MEASUREMENTS * 208
8.2 MEDICAL CT IMAGE NEURAL NETWORK BLIND EQUALIZATION ALGORITHM BASED
ON
ZIGZAG* 209
8.2.1 BASIC PRINCIPLE OF ALGORITHM * 209
8.2.2 ITERATIVE FORMULA DERIVATION * 211
8.2.3 ANALYSIS OF ALGORITHM CONVERGENCE PERFORMANCE * 213
8.2.4 EXPERIMENTAL SIMULATION * 215
8.3 MEDICAL CT IMAGE NEURAL NETWORK BLIND EQUALIZATION ALGORITHM BASED
ON DOUBLE ZIGZAG ENCODING* 219
8.3.1 THE BASIC PRINCIPLE OF ALGORITHM * 219
8.3.2 FORMULA DERIVATION OF ITERATIVE ALGORITHM * 220
8.3.3 EXPERIMENTAL SIMULATION * 224
8.4 SUMMARY* 226
APPENDIX A: DERIVATION OF THE HIDDEN LAYER WEIGHT ITERATIVE FORMULA IN
THE
BLIND EQUALIZATION ALGORITHM BASED ON THE COMPLEX
THREE-LAYER FFNN * 229
APPENDIX B: ITERATIVE FORMULAS DERIVATION OF COMPLEX BLIND EQUALIZATION
ALGORITHM BASED ON BRNN * 231
APPENDIX C: TYPES OF FUZZY MEMBERSHIP FUNCTION * 235
APPENDIX D: ITERATIVE FORMULA DERIVATION OF BLIND EQUALIZATION ALGORITHM
BASED ON DRFNN
-----
239
REFERENCES* 243
INDEX* 251
|
| any_adam_object | 1 |
| author | Zhang, Liyi Sun, Yunshan Zhang, Xiaoqin Bai, Yu |
| author_GND | (DE-588)1014359791 |
| author_facet | Zhang, Liyi Sun, Yunshan Zhang, Xiaoqin Bai, Yu |
| author_role | aut aut aut aut |
| author_sort | Zhang, Liyi |
| author_variant | l z lz y s ys x z xz y b yb |
| building | Verbundindex |
| bvnumber | BV044730462 |
| classification_rvk | ST 301 |
| ctrlnum | (OCoLC)1022087739 (DE-599)DNB1135497133 |
| dewey-full | 621.3 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
| dewey-raw | 621.3 |
| dewey-search | 621.3 |
| dewey-sort | 3621.3 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik Elektrotechnik / Elektronik / Nachrichtentechnik |
| format | Book |
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| id | DE-604.BV044730462 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:00:36Z |
| institution | BVB |
| isbn | 9783110449624 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030126541 |
| oclc_num | 1022087739 |
| open_access_boolean | |
| owner | DE-92 DE-11 DE-29T DE-634 |
| owner_facet | DE-92 DE-11 DE-29T DE-634 |
| physical | XI, 255 Seiten Illustrationen, Diagramme |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | De Gruyter |
| record_format | marc |
| spelling | Zhang, Liyi Verfasser (DE-588)1014359791 aut Blind equalization in neural networks theory, algorithms and applications Liyi Zhang, Yunshan Sun, Xiaoqin Zhang, Yu Bai Berlin De Gruyter [2018] © 2018 XI, 255 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Adaptive Entzerrung (DE-588)4141376-3 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s DE-604 Adaptive Entzerrung (DE-588)4141376-3 s 1\p DE-604 Sun, Yunshan Verfasser aut Zhang, Xiaoqin Verfasser aut Bai, Yu Verfasser aut Erscheint auch als 978-3-11-045030-9 Set (hbk & ebook) Erscheint auch als Online-Ausgabe, PDF 978-3-11-045029-3 Erscheint auch als Online-Ausgabe, EPUB 978-3-11-044967-9 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030126541&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Zhang, Liyi Sun, Yunshan Zhang, Xiaoqin Bai, Yu Blind equalization in neural networks theory, algorithms and applications Neuronales Netz (DE-588)4226127-2 gnd Adaptive Entzerrung (DE-588)4141376-3 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4141376-3 |
| title | Blind equalization in neural networks theory, algorithms and applications |
| title_auth | Blind equalization in neural networks theory, algorithms and applications |
| title_exact_search | Blind equalization in neural networks theory, algorithms and applications |
| title_full | Blind equalization in neural networks theory, algorithms and applications Liyi Zhang, Yunshan Sun, Xiaoqin Zhang, Yu Bai |
| title_fullStr | Blind equalization in neural networks theory, algorithms and applications Liyi Zhang, Yunshan Sun, Xiaoqin Zhang, Yu Bai |
| title_full_unstemmed | Blind equalization in neural networks theory, algorithms and applications Liyi Zhang, Yunshan Sun, Xiaoqin Zhang, Yu Bai |
| title_short | Blind equalization in neural networks |
| title_sort | blind equalization in neural networks theory algorithms and applications |
| title_sub | theory, algorithms and applications |
| topic | Neuronales Netz (DE-588)4226127-2 gnd Adaptive Entzerrung (DE-588)4141376-3 gnd |
| topic_facet | Neuronales Netz Adaptive Entzerrung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030126541&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT zhangliyi blindequalizationinneuralnetworkstheoryalgorithmsandapplications AT sunyunshan blindequalizationinneuralnetworkstheoryalgorithmsandapplications AT zhangxiaoqin blindequalizationinneuralnetworkstheoryalgorithmsandapplications AT baiyu blindequalizationinneuralnetworkstheoryalgorithmsandapplications |