New advances in intelligent signal processing:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2011
|
| Schriftenreihe: | Studies in computational intelligence
372 |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024519319&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XIII, 254 S. Ill., graph. Darst. |
| ISBN: | 9783642117381 3642117384 |
Internformat
MARC
| LEADER | 00000nam a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV039670148 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | t| | ||
| 008 | 111031s2011 xx ad|| |||| 00||| eng d | ||
| 016 | 7 | |a 1015540031 |2 DE-101 | |
| 020 | |a 9783642117381 |9 978-3-642-11738-1 | ||
| 020 | |a 3642117384 |9 3-642-11738-4 | ||
| 035 | |a (OCoLC)773832171 | ||
| 035 | |a (DE-599)DNB1015540031 | ||
| 040 | |a DE-604 |b ger |e rakddb | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-11 | ||
| 082 | 0 | |a 006.3 |2 22/ger | |
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 084 | |a 004 |2 sdnb | ||
| 084 | |a 621.3 |2 sdnb | ||
| 100 | 1 | |a Ruano, António E. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a New advances in intelligent signal processing |c António E. Ruano ... (eds.) |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2011 | |
| 300 | |a XIII, 254 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Studies in computational intelligence |v 372 | |
| 650 | 0 | 7 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Mustererkennung |0 (DE-588)4040936-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Soft Computing |0 (DE-588)4455833-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Bildverarbeitung |0 (DE-588)4006684-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Signalverarbeitung |0 (DE-588)4054947-1 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)1071861417 |a Konferenzschrift |y 2009 |z Budapest |2 gnd-content | |
| 689 | 0 | 0 | |a Soft Computing |0 (DE-588)4455833-8 |D s |
| 689 | 0 | 1 | |a Mustererkennung |0 (DE-588)4040936-3 |D s |
| 689 | 0 | 2 | |a Signalverarbeitung |0 (DE-588)4054947-1 |D s |
| 689 | 0 | 3 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Soft Computing |0 (DE-588)4455833-8 |D s |
| 689 | 1 | 1 | |a Bildverarbeitung |0 (DE-588)4006684-8 |D s |
| 689 | 1 | |5 DE-604 | |
| 830 | 0 | |a Studies in computational intelligence |v 372 |w (DE-604)BV020822171 |9 372 | |
| 856 | 4 | 2 | |m DNB Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024519319&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-024519319 | |
Datensatz im Suchindex
| _version_ | 1819265425410621440 |
|---|---|
| adam_text | IMAGE 1
CONTENTS
1 FORMULATION OF FUZZY RANDOM REGRESSION MODEL 1
JUNZO WATADA, SHUMING WANG, WITOLD PEDRYCZ 1 INTRODUCTION 2
2 FUZZY RANDOM VARIABLES 4
3 FUZZY RANDOM REGRESSION MODEL 7
4 THE SOLUTION TO THE FRRM 11
4.1 VERTICES METHOD 11
4.2 HEURISTIC METHOD 13
5 AN EXAMPLE 15
6 CONCLUDING REMARKS 17
REFERENCES 18
2 EVOLUTIONARY MULTIOBJECTIVE NEURAL NETWORK MODELS IDENTIFICATION:
EVOLVING TASK-OPTIMISED MODELS 21
PEDRO M. FERREIRA, ANTONIO E. RUANO 1 INTRODUCTION 21
2 METHODOLOGY 23
2.1 PROBLEM DEFINITION 24
2.2 MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS 25
2.3 MODEL DESIGN CYCLE 29
2.4 ANN PARAMETER TRAINING 30
3 EXAMPLE MODEL IDENTIFICATION PROBLEMS 35
3.1 ELECTRICITY CONSUMPTION PREDICTION 35
3.2 CLOUDINESS ESTIMATION 43
4 CONCLUDING REMARKS 50
REFERENCES 50
3 STRUCTURAL LEARNING MODEL OF THE NEURAL NETWORK AND ITS APPLICATION TO
LEDS SIGNAL RETROFIT 55
JUNZO WATADA, SHAMSHUL BAHAR YAAKOB 1 INTRODUCTION 56
2 HOPFIELD AND BOLTZMANN MACHINE 57
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1015540031
DIGITALISIERT DURCH
IMAGE 2
X CONTENTS
3 BOLTZMANN MACHINE APPROACH TO MEAN-VARIANCE ANALYSIS 59 4
DOUBLE-LAYERED BOLTZMANN MACHINE EXAMPLE 62
5 OVERVIEW ON LEDS SIGNAL RETROFIT 64
6 LEDS SIGNAL RETROFIT AND MEAN-VARIANCE PROBLEM 65
7 NUMERICAL EXAMPLE OF LEDS SIGNAL RETROFIT 67
8 CONCLUSIONS 72
REFERENCES 73
4 ROBUSTNESS OF DNA-BASED CLUSTERING 75
ROHANI ABU BAKAR, CHU YU-YI, JUNZO WATADA 1 DNA COMPUTING METHODS FOR
SOLVING CLUSTERING PROBLEMS 75 2 BACKGROUND STUDY OF CLUSTERING PROBLEMS
76
3 ROBUSTNESS OF DNA-BASED CLUSTERING ALGORITHMS 78
4 PROXIMITY DISTANCE APPROACH 80
5 ROBUSTNESS IN CLUSTERING 82
5.1 DATASET AND PARAMETER IMPLEMENTATION 83
5.2 ROBUSTNESS EVALUATION OF DNA-BASED CLUSTERING 83 6 RESULTS AND
DISCUSSION 85
7 CONCLUSIONS 90
REFERENCES 91
5 ADVANCES IN AUTOMATED NEONATAL SEIZURE DETECTION 93
EOIN M. THOMAS, ANDREY TEMKO, GORDON LIGHTBODY, WILLIAM P. MARNANE,
GERALDINE B. BOYLAN 1 INTRODUCTION 93
2 DATA AND EXPERIMENT SETUP 96
3 PROBABILISTIC CLASSIFICATION FRAMEWORK 97
3.1 PREPROCESSING AND FEATURE EXTRACTION 98
3.2 CLASSIFICATION 99
3.3 POSTPROCESSING 102
3.4 METRICS 103
4 RESULTS 104
4.1 RESULTS OVER ALL PATIENTS 104
4.2 RESULTS FOR INDIVIDUAL PATIENTS 107
5 DISCUSSION 109
6 CONCLUSION 112
REFERENCES 112
6 DESIGN OF FUZZY RELATION-BASED IMAGE SHARPENERS 115
FABRIZIO RUSSO 1 INTRODUCTION 115
2 LINEAR UNSHARP MASKING: A BRIEF REVIEW 116
3 NONLINEAR UNSHARP MASKING BASED ON FUZZY RELATIONS 118 4 EFFECTS OF
PARAMETER SETTINGS 120
5 NOISE PREFILTERING USING FUZZY RELATIONS 122
IMAGE 3
CONTENTS XI
6 A COMPLETE FUZZY RELATION-BASED IMAGE ENHANCEMENT SYSTEM 127
7 CONCLUSION 130
REFERENCES 1 30
7 APPLICATION OF FUZZY LOGIC AND LUKASIEWICZ OPERATORS FOR IMAGE
CONTRAST CONTROL 133
ANGEL BARRIGA, NASHAAT MOHAMED HUSSEIN HASSAN 1 INTRODUCTION 133
2 CONTRAST CONTROL TECHNIQUES 135
3 SOFT COMPUTING TECHNIQUES 138
3.1 MINIMIZATION OF IMAGE FUZZINESS 138
3.2 DIRECT METHOD 139
3.3 FUZZY HISTOGRAM HIPERBOLATION 140
3.4 SHARPENING AND NOISE REDUCTION 140
4 HARDWARE REALIZATIONS 141
5 CONTRAST CONTROL BY MEANS OF LUKASIEWICZ OPERATORS 142 6 CONTROL
PARAMETERS BASED ON FUZZY LOGIC 144
7 CONTRAST CONTROLLER ARCHITECTURE 149
8 CONCLUSIONS 152
REFERENCES 153
8 LOW COMPLEXITY SITUATIONAL MODELS IN IMAGE QUALITY IMPROVEMENT 155
ANNAMARIA R. VARKONYI-KOCZY 1 INTRODUCTION 155
2 CORNER DETECTION 156
2.1 OVERVIEW 157
2.2 DETECTION OF CORNER POINTS 159
2.3 EXPERIMENTAL RESULTS 162
3 USEFUL INFORMATION EXTRACTION 163
3.1 OVERVIEW 166
3.2 SURFACE SMOOTHING 169
3.3 EDGE DETECTION 170
3.4 EDGE SEPARATION 171
3.5 ILLUSTRATIVE EXAMPLE 172
4 A POSSIBLE APPLICATION: 3D RECONSTRUCTION OF SCENES 175 5 CONCLUSIONS
176
REFERENCES 176
9 A FLEXIBLE REPRESENTATION AND INVERTIBLE TRANSFORMATIONS FOR IMAGES ON
QUANTUM COMPUTERS 179
PHUC Q. LE, ABDULLAHI M. ILIYASU, FANGYAN DONG, KAONI HIROTA 1
INTRODUCTION 179
2 FLEXIBLE REPRESENTATION OF QUANTUM IMAGES AND ITS POLYNOMIAL
PREPARATION 181
IMAGE 4
XII CONTENTS
3 QUANTUM IMAGE COMPRESSION BASED ON MINIMIZATION OF BOOLEAN EXPRESSIONS
186
4 IMAGE PROCESSING OPERATORS ON QUANTUM IMAGES BASED ON INVERTIBLE
TRANSFORMATIONS 191
5 EXPERIMENTS ON QUANTUM IMAGES 194
5.1 STORAGE AND RETRIEVAL OF QUANTUM IMAGES 194
5.2 ANALYSIS OF QUANTUM IMAGE COMPRESSION RATIOS 196 5.3 SIMPLE
DETECTION OF A LINE IN A QUANTUM IMAGE BASED ON QUANTUM FOURIER
TRANSFORM 198
6 CONCLUSION 199
REFERENCES 202
10 WEAKLY SUPERVISED LEARNING: APPLICATION TO FISH SCHOOL RECOGNITION
203
RIWAL LEFORT, RONAN FABLET, JEAN-MARC BOUCHER 1 INTRODUCTION 203
2 NOTATIONS AND GENERAL FRAMEWORK 205
3 GENERATIVE MODEL 206
4 DISCRIMINATIVE MODEL 209
4.1 LINEAR MODEL 209
4.2 NON LINEAR MODEL 210
5 SOFT DECISION TREES AND SOFT RANDOM FORESTS 211
5.1 SOFT DECISION TREES 211
5.2 SOFT RANDOM FOREST 213
6 CLASSIFIER COMBINATION 214
7 APPLICATION TO FISHERIES ACOUSTICS 215
7.1 SIMULATION METHOD 215
7.2 THE FISH SCHOOL DATASET 216
7.3 RESULTS 217
8 CONCLUSION 221
REFERENCES 221
11 INTELLIGENT SPACES AS ASSISTIVE ENVIRONMENTS: VISUAL FALL DETECTION
USING AN EVOLUTIVE ALGORITHM 225
JOSE MARIA CANAS, SARA MARUGAN, MARTA MARRON, JUAN C. GARCIA 1
INTRODUCTION 225
2 GLOBAL SYSTEM DESCRIPTION 228
3 MULTIMODAL EVOLUTIVE ALGORITHM FOR VISION BASED 3D TRACKING 229
3.1 EXPLORERS AND RACES 231
3.2 FITNESS FUNCTION OBSERVATION MODEL 233
3.3 DETERMINE 3D POSITIONS 236
IMAGE 5
CONTENTS XIII
4 EXPERIMENTS 237
4.1 TYPICAL EXECUTION 239
4.2 TIME PERFORMANCE 241
4.3 SYSTEM ACCURACY 242
5 CONCLUSIONS 245
REFERENCES 246
AUTHOR INDEX 249
SUBJECT INDEX 251
|
| any_adam_object | 1 |
| author | Ruano, António E. |
| author_facet | Ruano, António E. |
| author_role | aut |
| author_sort | Ruano, António E. |
| author_variant | a e r ae aer |
| building | Verbundindex |
| bvnumber | BV039670148 |
| classification_rvk | ST 300 |
| ctrlnum | (OCoLC)773832171 (DE-599)DNB1015540031 |
| dewey-full | 006.3 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
| dewey-sort | 16.3 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Elektrotechnik / Elektronik / Nachrichtentechnik |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02137nam a2200529 cb4500</leader><controlfield tag="001">BV039670148</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">t|</controlfield><controlfield tag="008">111031s2011 xx ad|| |||| 00||| eng d</controlfield><datafield tag="016" ind1="7" ind2=" "><subfield code="a">1015540031</subfield><subfield code="2">DE-101</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783642117381</subfield><subfield code="9">978-3-642-11738-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3642117384</subfield><subfield code="9">3-642-11738-4</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)773832171</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DNB1015540031</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rakddb</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-11</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3</subfield><subfield code="2">22/ger</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">004</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">621.3</subfield><subfield code="2">sdnb</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ruano, António E.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">New advances in intelligent signal processing</subfield><subfield code="c">António E. Ruano ... (eds.)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin [u.a.]</subfield><subfield code="b">Springer</subfield><subfield code="c">2011</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XIII, 254 S.</subfield><subfield code="b">Ill., graph. Darst.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Studies in computational intelligence</subfield><subfield code="v">372</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Mustererkennung</subfield><subfield code="0">(DE-588)4040936-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Soft Computing</subfield><subfield code="0">(DE-588)4455833-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Bildverarbeitung</subfield><subfield code="0">(DE-588)4006684-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Signalverarbeitung</subfield><subfield code="0">(DE-588)4054947-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)1071861417</subfield><subfield code="a">Konferenzschrift</subfield><subfield code="y">2009</subfield><subfield code="z">Budapest</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Soft Computing</subfield><subfield code="0">(DE-588)4455833-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Mustererkennung</subfield><subfield code="0">(DE-588)4040936-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Signalverarbeitung</subfield><subfield code="0">(DE-588)4054947-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Soft Computing</subfield><subfield code="0">(DE-588)4455833-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2="1"><subfield code="a">Bildverarbeitung</subfield><subfield code="0">(DE-588)4006684-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Studies in computational intelligence</subfield><subfield code="v">372</subfield><subfield code="w">(DE-604)BV020822171</subfield><subfield code="9">372</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">DNB Datenaustausch</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024519319&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-024519319</subfield></datafield></record></collection> |
| genre | (DE-588)1071861417 Konferenzschrift 2009 Budapest gnd-content |
| genre_facet | Konferenzschrift 2009 Budapest |
| id | DE-604.BV039670148 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T15:59:50Z |
| institution | BVB |
| isbn | 9783642117381 3642117384 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024519319 |
| oclc_num | 773832171 |
| open_access_boolean | |
| owner | DE-11 |
| owner_facet | DE-11 |
| physical | XIII, 254 S. Ill., graph. Darst. |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Springer |
| record_format | marc |
| series | Studies in computational intelligence |
| series2 | Studies in computational intelligence |
| spellingShingle | Ruano, António E. New advances in intelligent signal processing Studies in computational intelligence Maschinelles Lernen (DE-588)4193754-5 gnd Mustererkennung (DE-588)4040936-3 gnd Soft Computing (DE-588)4455833-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd Signalverarbeitung (DE-588)4054947-1 gnd |
| subject_GND | (DE-588)4193754-5 (DE-588)4040936-3 (DE-588)4455833-8 (DE-588)4006684-8 (DE-588)4054947-1 (DE-588)1071861417 |
| title | New advances in intelligent signal processing |
| title_auth | New advances in intelligent signal processing |
| title_exact_search | New advances in intelligent signal processing |
| title_full | New advances in intelligent signal processing António E. Ruano ... (eds.) |
| title_fullStr | New advances in intelligent signal processing António E. Ruano ... (eds.) |
| title_full_unstemmed | New advances in intelligent signal processing António E. Ruano ... (eds.) |
| title_short | New advances in intelligent signal processing |
| title_sort | new advances in intelligent signal processing |
| topic | Maschinelles Lernen (DE-588)4193754-5 gnd Mustererkennung (DE-588)4040936-3 gnd Soft Computing (DE-588)4455833-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd Signalverarbeitung (DE-588)4054947-1 gnd |
| topic_facet | Maschinelles Lernen Mustererkennung Soft Computing Bildverarbeitung Signalverarbeitung Konferenzschrift 2009 Budapest |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024519319&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV020822171 |
| work_keys_str_mv | AT ruanoantonioe newadvancesinintelligentsignalprocessing |