Self-organization and associative memory:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
1989
|
| Ausgabe: | 3. ed. |
| Schriftenreihe: | Springer series in information sciences
8 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XV, 312 S. graph. Darst. |
| ISBN: | 3540513876 0387513876 |
Internformat
MARC
| LEADER | 00000nam a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV022007756 | ||
| 003 | DE-604 | ||
| 005 | 20040301000000.0 | ||
| 007 | t | ||
| 008 | 900221s1989 d||| |||| 00||| eng d | ||
| 020 | |a 3540513876 |9 3-540-51387-6 | ||
| 020 | |a 0387513876 |9 0-387-51387-6 | ||
| 035 | |a (OCoLC)20015322 | ||
| 035 | |a (DE-599)BVBBV022007756 | ||
| 040 | |a DE-604 |b ger | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-706 | ||
| 050 | 0 | |a Q325 | |
| 082 | 0 | |a 003/.7 |2 20 | |
| 084 | |a CP 5000 |0 (DE-625)18991: |2 rvk | ||
| 084 | |a SK 880 |0 (DE-625)143266: |2 rvk | ||
| 084 | |a ST 285 |0 (DE-625)143648: |2 rvk | ||
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 100 | 1 | |a Kohonen, Teuvo |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Self-organization and associative memory |
| 250 | |a 3. ed. | ||
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 1989 | |
| 300 | |a XV, 312 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Springer series in information sciences |v 8 | |
| 650 | 4 | |a Associative storage | |
| 650 | 4 | |a Memory | |
| 650 | 4 | |a Self-organizing systems | |
| 650 | 0 | 7 | |a Psychologie |0 (DE-588)4047704-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Assoziativspeicher |0 (DE-588)4124575-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Nervennetz |0 (DE-588)4041638-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Mathematische Psychologie |0 (DE-588)4126558-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Gedächtnis |0 (DE-588)4019614-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Selbsteinstellendes System |0 (DE-588)4054398-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Selbstbestimmung |0 (DE-588)4135889-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Selbst organisierendes System |0 (DE-588)4054424-2 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Modell |0 (DE-588)4039798-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Assoziatives Gedächtnis |0 (DE-588)4290792-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Selbstbestimmung |0 (DE-588)4135889-2 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Assoziatives Gedächtnis |0 (DE-588)4290792-5 |D s |
| 689 | 1 | |5 DE-604 | |
| 689 | 2 | 0 | |a Assoziativspeicher |0 (DE-588)4124575-1 |D s |
| 689 | 2 | 1 | |a Gedächtnis |0 (DE-588)4019614-8 |D s |
| 689 | 2 | |8 1\p |5 DE-604 | |
| 689 | 3 | 0 | |a Gedächtnis |0 (DE-588)4019614-8 |D s |
| 689 | 3 | 1 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |D s |
| 689 | 3 | |8 2\p |5 DE-604 | |
| 689 | 4 | 0 | |a Gedächtnis |0 (DE-588)4019614-8 |D s |
| 689 | 4 | 1 | |a Psychologie |0 (DE-588)4047704-6 |D s |
| 689 | 4 | |8 3\p |5 DE-604 | |
| 689 | 5 | 0 | |a Nervennetz |0 (DE-588)4041638-0 |D s |
| 689 | 5 | 1 | |a Modell |0 (DE-588)4039798-1 |D s |
| 689 | 5 | |8 4\p |5 DE-604 | |
| 689 | 6 | 0 | |a Gedächtnis |0 (DE-588)4019614-8 |D s |
| 689 | 6 | 1 | |a Mathematische Psychologie |0 (DE-588)4126558-0 |D s |
| 689 | 6 | |8 5\p |5 DE-604 | |
| 689 | 7 | 0 | |a Selbsteinstellendes System |0 (DE-588)4054398-5 |D s |
| 689 | 7 | |8 6\p |5 DE-604 | |
| 689 | 8 | 0 | |a Selbst organisierendes System |0 (DE-588)4054424-2 |D s |
| 689 | 8 | |8 7\p |5 DE-604 | |
| 830 | 0 | |a Springer series in information sciences |v 8 |w (DE-604)BV000008063 | |
| 856 | 4 | 2 | |m HEBIS Datenaustausch Darmstadt |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015222388&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-015222388 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 2\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 3\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 4\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 5\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 6\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 7\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
Datensatz im Suchindex
| _version_ | 1804135982604222464 |
|---|---|
| adam_text | CONTENTS 1. VARIOUS ASPECTS OF MEMORY 1 1.1 ON THE PURPOSE AND NATURE OF
BIOLOGICAL MEMORY 1 1.1.1 SOME FUNDAMENTAL CONCEPTS 1 1.1.2 THE
CLASSICAL LAWS OF ASSOCIATION 3 1.1.3 ON DIFFERENT LEVELS OF MODELLING 4
1.2 QUESTIONS CONCERNING THE FUNDAMENTAL MECHANISMS OF MEMORY 4 1.2.1
WHERE DO THE SIGNALS RELATING TO MEMORY ACT UPON? ... 5 1.2.2 WHAT KIND
OF ENCODING IS USED FOR NEURAL SIGNALS? 6 1.2.3 WHAT ARE THE VARIABLE
MEMORY ELEMENTS? 7 1.2.4 HOW ARE NEURAL SIGNALS ADDRESSED IN MEMORY? 8
1.3 ELEMENTARY OPERATIONS IMPLEMENTED BY ASSOCIATIVE MEMORY .. 14 1.3.1
ASSOCIATIVE RECALL 14 1.3.2 PRODUCTION OF SEQUENCES FROM THE ASSOCIATIVE
MEMORY .. 16 1.3.3 ON THE MEANING OF BACKGROUND AND CONTEXT 20 1.4 MORE
ABSTRACT ASPECTS OF MEMORY ,, 21 1.4.1 THE PROBLEM OF INFINITE-STATE
MEMORY 21 1.4.2 INVARIANT REPRESENTATIONS 22 1.4.3 SYMBOLIC
REPRESENTATIONS 24 1.4.4 VIRTUAL IMAGES 25 1.4.5 THE LOGIC OF STORED
KNOWLEDGE 27 2. PATTERN MATHEMATICS 30 2.1 MATHEMATICAL NOTATIONS AND
METHODS 30 2.1.1 VECTOR SPACE CONCEPTS 30 2.1.2 MATRIX NOTATIONS 41
2.1.3 FURTHER PROPERTIES OF MATRICES 44 2.1.4 MATRIX EQUATIONS 48 2.1.5
PROJECTION OPERATORS 54 2.1.6 ON MATRIX DIFFERENTIAL CALCULUS 57 2.2
DISTANCE MEASURES FOR PATTERNS 59 XII CONTENTS 2.2.1 MEASURES OF
SIMILARITY AND DISTANCE IN VECTOR SPACES .... 59 2.2.2 MEASURES OF
SIMILARITY AND DISTANCE BETWEEN SYMBOL STRINGS 63 2.2.3 MORE ACCURATE
DISTANCE MEASURES FOR TEXT 66 3. CLASSICAL LEARNING SYSTEMS 68 3.1 THE
ADAPTIVE LINEAR ELEMENT (ADALINE) 69 3.1.1 DESCRIPTION OF ADAPTATION BY
THE STOCHASTIC APPROXIMATION 71 3.2 THE PERCEPTRON 72 3.3 THE LEARNING
MATRIX 74 3.4 PHYSICAL REALIZATION OF ADAPTIVE WEIGHTS 77 3.4.1
PERCEPTRON AND ADALINE 77 3.4.2 CLASSICAL CONDITIONING 78 3.4.3
CONJUNCTION LEARNING SWITCHES 80 3.4.4 DIGITAL REPRESENTATION OF
ADAPTIVE CIRCUITS 80 3.4.5 BIOLOGICAL COMPONENTS 81 4. A NEW APPROACH TO
ADAPTIVE FILTERS 82 4.1 SURVEY OF SOME NECESSARY FUNCTIONS 82 4.2 ON THE
TRANSFER FUNCTION OF THE NEURON 84 4.3 MODELS FOR BASIC ADAPTIVE UNITS
90 4.3.1 ON THE LINEARIZATION OF THE BASIC UNIT 90 4.3.2 VARIOUS CASES
OF ADAPTATION LAWS 91 4.3.3 TWO LIMIT THEOREMS 98 4.3.4 THE NOVELTY
DETECTOR /. 101 4.4 ADAPTIVE FEEDBACK NETWORKS 104 4.4.1 THE
AUTOCORRELATION MATRIX MEMORY 105 4.4.2 THE NOVELTY FILTER 109 5.
SELF-ORGANIZING FEATURE MAPS 119 5.1 ON THE FEATURE MAPS OF THE BRAIN
119 5.2 FORMATION OF LOCALIZED RESPONSES BY LATERAL FEEDBACK 122 5.3
COMPUTATIONAL SIMPLIFICATION OF THE PROCESS 127 5.3.1 DEFINITION OF THE
TOPOLOGY-PRESERVING MAPPING 127 5.3.2 A SIMPLE TWO-DIMENSIONAL
SELF-ORGANIZING SYSTEM 130 5.4 DEMONSTRATIONS OF SIMPLE
TOPOLOGY-PRESERVING MAPPINGS .... 133 5.4.1 IMAGES OF VARIOUS
DISTRIBUTIONS OF INPUT VECTORS 133 5.4.2 THE MAGIC TV 137 5.4.3
MAPPING BY A FEELER MECHANISM 139 5.5 TONOTOPIC MAP 140 CONTENTS XIII
5.6 FORMATION OF HIERARCHICAL REPRESENTATIONS 141 5.6.1 TAXONOMY EXAMPLE
141 5.6.2 PHONEME MAP 142 5.7 MATHEMATICAL TREATMENT OF
SELF-ORGANIZATION 143 5.7.1 ORDERING OF WEIGHTS 144 5.7.2 CONVERGENCE
PHASE 150 5.8 AUTOMATIC SELECTION OF FEATURE DIMENSIONS 155 6. OPTIMAL
ASSOCIATIVE MAPPINGS 158 6.1 TRANSFER FUNCTION OF AN ASSOCIATIVE NETWORK
159 6.2 AUTOASSOCIATIVE RECALL AS AN ORTHOGONAL PROJECTION 160 6.2.1
ORTHOGONAL PROJECTIONS 160 6.2.2 ERROR-CORRECTING PROPERTIES OF
PROJECTIONS 161 6.3 THE NOVELTY FILTER 163 6.3.1 TWO EXAMPLES OF NOVELTY
FILTER 163 6.3.2 NOVELTY FILTER AS AN AUTOASSOCIATIVE MEMORY 165 6.4
AUTOASSOCIATIVE ENCODING 165 6.4.1 AN EXAMPLE OF AUTOASSOCIATIVE
ENCODING 166 6.5 OPTIMAL ASSOCIATIVE MAPPINGS 167 6.5.1 THE OPTIMAL
LINEAR ASSOCIATIVE MAPPING 168 6.5.2 OPTIMAL NONLINEAR ASSOCIATIVE
MAPPINGS 172 6.6 RELATIONSHIP BETWEEN ASSOCIATIVE MAPPING, LINEAR
REGRESSION, AND LINEAR ESTIMATION 175 6.6.1 RELATIONSHIP OF THE
ASSOCIATIVE MAPPING TO LINEAR REGRESSION 175 6.6.2 RELATIONSHIP OF THE
REGRESSION SOLUTION TO THE LINEAR ESTIMATOR 176 6.7 RECURSIVE
COMPUTATION OF THE OPTIMAL ASSOCIATIVE MAPPING ... 177 6.7.1 LINEAR
CORRECTIVE ALGORITHMS 178 6.7.2 BEST EXACT SOLUTION (GRADIENT
PROJECTION) 179 6.7.3 BEST APPROXIMATE SOLUTION (REGRESSION) 180 6.7.4
RECURSIVE SOLUTION IN THE GENERAL CASE 182 6.8 SPECIAL CASES 183 6.8.1
THE CORRELATION MATRIX MEMORY 183 6.8.2 RELATIONSHIP BETWEEN CONDITIONAL
AVERAGES AND OPTIMAL ESTIMATOR 184 7. PATTERN RECOGNITION 185 7.1
DISCRIMINANT FUNCTIONS 185 7.2 STATISTICAL FORMULATION OF PATTERN
CLASSIFICATION 187 7.3 COMPARISON METHODS 190 XIV CONTENTS 7.4 THE
SUBSPACE METHODS OF CLASSIFICATION 192 7.4.1 THE BASIC SUBSPACE METHOD
192 7.4.2 THE LEARNING SUBSPACE METHOD (LSM) 193 7.5 LEARNING VECTOR
QUANTIZATION 199 7.6 FEATURE EXTRACTION 202 7.7 CLUSTERING 203 7.7.1
SIMPLE CLUSTERING (OPTIMIZATION APPROACH) 204 7.7.2 HIERARCHICAL
CLUSTERING (TAXONOMY APPROACH) 205 7.8 STRUCTURAL PATTERN RECOGNITION
METHODS 206 8. MORE ABOUT BIOLOGICAL MEMORY 210 8.1 PHYSIOLOGICAL
FOUNDATIONS OF MEMORY 210 8.1.1 ON THE MECHANISMS OF MEMORY IN
BIOLOGICAL SYSTEMS ... 210 8.1.2 STRUCTURAL FEATURES OF SOME NEURAL
NETWORKS 213 8.1.3 FUNCTIONAL FEATURES OF NEURONS 218 8.1.4 MODELLING OF
THE SYNAPTIC PLASTICITY 222 8.1.5 CAN THE MEMORY CAPACITY ENSUE FROM
SYNAPTIC CHANGES? 227 8.2 THE UNIFIED CORTICAL MEMORY MODEL 230 8.2.1
THE LAMINAR NETWORK ORGANIZATION 230 8.2.2 ON THE ROLES OF INTERNEURONS
232 8.2.3 REPRESENTATION OF KNOWLEDGE OVER MEMORY FIELDS 233 8.2.4
SELF-CONTROLLED OPERATION OF MEMORY 237 8.3 COLLATERAL READING 239 8.3.1
PHYSIOLOGICAL RESULTS RELEVANT TO MODELLING 239 8.3.2 RELATED MODELLING
240 .7 . / 9. NOTES ON NEURAL COMPUTING 241 9.1 FIRST THEORETICAL VIEWS
OF NEURAL NETWORKS 241 9.2 MOTIVES FOR THE NEURAL COMPUTING RESEARCH 242
9.3 WHAT COULD THE PURPOSE OF THE NEURAL NETWORKS BE? 245 9.4
DEFINITIONS OF ARTIFICIAL NEURAL COMPUTING AND GENERAL NOTES ON NEURAL
MODELLING 249 9.5 ARE THE BIOLOGICAL NEURAL FUNCTIONS LOCALIZED OR
DISTRIBUTED? 253 9.6 IS NOHLINEARITY ESSENTIAL TO NEURAL COMPUTING? 255
9.7 CHARACTERISTIC DIFFERENCES BETWEEN NEURAL AND DIGITAL COMPUTERS 259
9.7.1 THE DEGREE OF PARALLELISM OF THE NEURAL NETWORKS IS STILL HIGHER
THAN THAT OF ANY MASSIVELY PARALLEL DIGITAL COMPUTER 259 9.7.2 WHY THE
NEURAL SIGNALS CANNOT BE APPROXIMATED BY BOOLEAN VARIABLES 261 CONTENTS
XV 9.7.3 THE NEURAL CIRCUITS DO NOT IMPLEMENT FINITE AUTOMATA 261 9.7.4
UNDUE VIEWS OF THE LOGIC EQUIVALENCE OF THE BRAIN AND COMPUTERS ON A
HIGH LEVEL 263 9.8 CONNECTIONIST MODELS 264 9.9 HOW CAN THE NEURAL
COMPUTERS BE PROGRAMMED? 267 10. OPTICAL ASSOCIATIVE MEMORIES 26 9 10.1
NONHOLOGRAPHIC METHODS 269 10.2 GENERAL ASPECTS OF HOLOGRAPHIC MEMORIES
271 10.3 A SIMPLE PRINCIPLE OF HOLOGRAPHIC ASSOCIATIVE MEMORY 273 10.4
ADDRESSING IN HOLOGRAPHIC MEMORIES 275 10.5 RECENT ADVANCES OF OPTICAL
ASSOCIATIVE MEMORIES 280 BIBLIOGRAPHY ON PATTERN RECOGNITION 285
REFERENCES 289 SUBJECT INDEX 301
|
| adam_txt |
CONTENTS 1. VARIOUS ASPECTS OF MEMORY 1 1.1 ON THE PURPOSE AND NATURE OF
BIOLOGICAL MEMORY 1 1.1.1 SOME FUNDAMENTAL CONCEPTS 1 1.1.2 THE
CLASSICAL LAWS OF ASSOCIATION 3 1.1.3 ON DIFFERENT LEVELS OF MODELLING 4
1.2 QUESTIONS CONCERNING THE FUNDAMENTAL MECHANISMS OF MEMORY 4 1.2.1
WHERE DO THE SIGNALS RELATING TO MEMORY ACT UPON? . 5 1.2.2 WHAT KIND
OF ENCODING IS USED FOR NEURAL SIGNALS? 6 1.2.3 WHAT ARE THE VARIABLE
MEMORY ELEMENTS? 7 1.2.4 HOW ARE NEURAL SIGNALS ADDRESSED IN MEMORY? 8
1.3 ELEMENTARY OPERATIONS IMPLEMENTED BY ASSOCIATIVE MEMORY . 14 1.3.1
ASSOCIATIVE RECALL 14 1.3.2 PRODUCTION OF SEQUENCES FROM THE ASSOCIATIVE
MEMORY . 16 1.3.3 ON THE MEANING OF BACKGROUND AND CONTEXT 20 1.4 MORE
ABSTRACT ASPECTS OF MEMORY ,, 21 1.4.1 THE PROBLEM OF INFINITE-STATE
MEMORY 21 1.4.2 INVARIANT REPRESENTATIONS 22 1.4.3 SYMBOLIC
REPRESENTATIONS 24 1.4.4 VIRTUAL IMAGES 25 1.4.5 THE LOGIC OF STORED
KNOWLEDGE 27 2. PATTERN MATHEMATICS 30 2.1 MATHEMATICAL NOTATIONS AND
METHODS 30 2.1.1 VECTOR SPACE CONCEPTS 30 2.1.2 MATRIX NOTATIONS 41
2.1.3 FURTHER PROPERTIES OF MATRICES 44 2.1.4 MATRIX EQUATIONS 48 2.1.5
PROJECTION OPERATORS 54 2.1.6 ON MATRIX DIFFERENTIAL CALCULUS 57 2.2
DISTANCE MEASURES FOR PATTERNS 59 XII CONTENTS 2.2.1 MEASURES OF
SIMILARITY AND DISTANCE IN VECTOR SPACES . 59 2.2.2 MEASURES OF
SIMILARITY AND DISTANCE BETWEEN SYMBOL STRINGS 63 2.2.3 MORE ACCURATE
DISTANCE MEASURES FOR TEXT 66 3. CLASSICAL LEARNING SYSTEMS 68 3.1 THE
ADAPTIVE LINEAR ELEMENT (ADALINE) 69 3.1.1 DESCRIPTION OF ADAPTATION BY
THE STOCHASTIC APPROXIMATION 71 3.2 THE PERCEPTRON 72 3.3 THE LEARNING
MATRIX 74 3.4 PHYSICAL REALIZATION OF ADAPTIVE WEIGHTS 77 3.4.1
PERCEPTRON AND ADALINE 77 3.4.2 CLASSICAL CONDITIONING 78 3.4.3
CONJUNCTION LEARNING SWITCHES 80 3.4.4 DIGITAL REPRESENTATION OF
ADAPTIVE CIRCUITS 80 3.4.5 BIOLOGICAL COMPONENTS 81 4. A NEW APPROACH TO
ADAPTIVE FILTERS 82 4.1 SURVEY OF SOME NECESSARY FUNCTIONS 82 4.2 ON THE
"TRANSFER FUNCTION" OF THE NEURON 84 4.3 MODELS FOR BASIC ADAPTIVE UNITS
90 4.3.1 ON THE LINEARIZATION OF THE BASIC UNIT 90 4.3.2 VARIOUS CASES
OF ADAPTATION LAWS 91 4.3.3 TWO LIMIT THEOREMS 98 4.3.4 THE NOVELTY
DETECTOR /. 101 4.4 ADAPTIVE FEEDBACK NETWORKS 104 4.4.1 THE
AUTOCORRELATION MATRIX MEMORY 105 4.4.2 THE NOVELTY FILTER 109 5.
SELF-ORGANIZING FEATURE MAPS 119 5.1 ON THE FEATURE MAPS OF THE BRAIN
119 5.2 FORMATION OF LOCALIZED RESPONSES BY LATERAL FEEDBACK 122 5.3
COMPUTATIONAL SIMPLIFICATION OF THE PROCESS 127 5.3.1 DEFINITION OF THE
TOPOLOGY-PRESERVING MAPPING 127 5.3.2 A SIMPLE TWO-DIMENSIONAL
SELF-ORGANIZING SYSTEM 130 5.4 DEMONSTRATIONS OF SIMPLE
TOPOLOGY-PRESERVING MAPPINGS . 133 5.4.1 IMAGES OF VARIOUS
DISTRIBUTIONS OF INPUT VECTORS 133 5.4.2 "THE MAGIC TV" 137 5.4.3
MAPPING BY A FEELER MECHANISM 139 5.5 TONOTOPIC MAP 140 CONTENTS XIII
5.6 FORMATION OF HIERARCHICAL REPRESENTATIONS 141 5.6.1 TAXONOMY EXAMPLE
141 5.6.2 PHONEME MAP 142 5.7 MATHEMATICAL TREATMENT OF
SELF-ORGANIZATION 143 5.7.1 ORDERING OF WEIGHTS 144 5.7.2 CONVERGENCE
PHASE 150 5.8 AUTOMATIC SELECTION OF FEATURE DIMENSIONS 155 6. OPTIMAL
ASSOCIATIVE MAPPINGS 158 6.1 TRANSFER FUNCTION OF AN ASSOCIATIVE NETWORK
159 6.2 AUTOASSOCIATIVE RECALL AS AN ORTHOGONAL PROJECTION 160 6.2.1
ORTHOGONAL PROJECTIONS 160 6.2.2 ERROR-CORRECTING PROPERTIES OF
PROJECTIONS 161 6.3 THE NOVELTY FILTER 163 6.3.1 TWO EXAMPLES OF NOVELTY
FILTER 163 6.3.2 NOVELTY FILTER AS AN AUTOASSOCIATIVE MEMORY 165 6.4
AUTOASSOCIATIVE ENCODING 165 6.4.1 AN EXAMPLE OF AUTOASSOCIATIVE
ENCODING 166 6.5 OPTIMAL ASSOCIATIVE MAPPINGS 167 6.5.1 THE OPTIMAL
LINEAR ASSOCIATIVE MAPPING 168 6.5.2 OPTIMAL NONLINEAR ASSOCIATIVE
MAPPINGS 172 6.6 RELATIONSHIP BETWEEN ASSOCIATIVE MAPPING, LINEAR
REGRESSION, AND LINEAR ESTIMATION 175 6.6.1 RELATIONSHIP OF THE
ASSOCIATIVE MAPPING TO LINEAR REGRESSION 175 6.6.2 RELATIONSHIP OF THE
REGRESSION SOLUTION TO THE LINEAR ESTIMATOR 176 6.7 RECURSIVE
COMPUTATION OF THE OPTIMAL ASSOCIATIVE MAPPING . 177 6.7.1 LINEAR
CORRECTIVE ALGORITHMS 178 6.7.2 BEST EXACT SOLUTION (GRADIENT
PROJECTION) 179 6.7.3 BEST APPROXIMATE SOLUTION (REGRESSION) 180 6.7.4
RECURSIVE SOLUTION IN THE GENERAL CASE 182 6.8 SPECIAL CASES 183 6.8.1
THE CORRELATION MATRIX MEMORY 183 6.8.2 RELATIONSHIP BETWEEN CONDITIONAL
AVERAGES AND OPTIMAL ESTIMATOR 184 7. PATTERN RECOGNITION 185 7.1
DISCRIMINANT FUNCTIONS 185 7.2 STATISTICAL FORMULATION OF PATTERN
CLASSIFICATION 187 7.3 COMPARISON METHODS 190 XIV CONTENTS 7.4 THE
SUBSPACE METHODS OF CLASSIFICATION 192 7.4.1 THE BASIC SUBSPACE METHOD
192 7.4.2 THE LEARNING SUBSPACE METHOD (LSM) 193 7.5 LEARNING VECTOR
QUANTIZATION 199 7.6 FEATURE EXTRACTION 202 7.7 CLUSTERING 203 7.7.1
SIMPLE CLUSTERING (OPTIMIZATION APPROACH) 204 7.7.2 HIERARCHICAL
CLUSTERING (TAXONOMY APPROACH) 205 7.8 STRUCTURAL PATTERN RECOGNITION
METHODS 206 8. MORE ABOUT BIOLOGICAL MEMORY 210 8.1 PHYSIOLOGICAL
FOUNDATIONS OF MEMORY 210 8.1.1 ON THE MECHANISMS OF MEMORY IN
BIOLOGICAL SYSTEMS . 210 8.1.2 STRUCTURAL FEATURES OF SOME NEURAL
NETWORKS 213 8.1.3 FUNCTIONAL FEATURES OF NEURONS 218 8.1.4 MODELLING OF
THE SYNAPTIC PLASTICITY 222 8.1.5 CAN THE MEMORY CAPACITY ENSUE FROM
SYNAPTIC CHANGES? 227 8.2 THE UNIFIED CORTICAL MEMORY MODEL 230 8.2.1
THE LAMINAR NETWORK ORGANIZATION 230 8.2.2 ON THE ROLES OF INTERNEURONS
232 8.2.3 REPRESENTATION OF KNOWLEDGE OVER MEMORY FIELDS 233 8.2.4
SELF-CONTROLLED OPERATION OF MEMORY 237 8.3 COLLATERAL READING 239 8.3.1
PHYSIOLOGICAL RESULTS RELEVANT TO MODELLING 239 8.3.2 RELATED MODELLING
240 .7 .'/ 9. NOTES ON NEURAL COMPUTING 241 9.1 FIRST THEORETICAL VIEWS
OF NEURAL NETWORKS 241 9.2 MOTIVES FOR THE NEURAL COMPUTING RESEARCH 242
9.3 WHAT COULD THE PURPOSE OF THE NEURAL NETWORKS BE? 245 9.4
DEFINITIONS OF ARTIFICIAL "NEURAL COMPUTING" AND GENERAL NOTES ON NEURAL
MODELLING 249 9.5 ARE THE BIOLOGICAL NEURAL FUNCTIONS LOCALIZED OR
DISTRIBUTED? 253 9.6 IS NOHLINEARITY ESSENTIAL TO NEURAL COMPUTING? 255
9.7 CHARACTERISTIC DIFFERENCES BETWEEN NEURAL AND DIGITAL COMPUTERS 259
9.7.1 THE DEGREE OF PARALLELISM OF THE NEURAL NETWORKS IS STILL HIGHER
THAN THAT OF ANY "MASSIVELY PARALLEL" DIGITAL COMPUTER 259 9.7.2 WHY THE
NEURAL SIGNALS CANNOT BE APPROXIMATED BY BOOLEAN VARIABLES 261 CONTENTS
XV 9.7.3 THE NEURAL CIRCUITS DO NOT IMPLEMENT FINITE AUTOMATA 261 9.7.4
UNDUE VIEWS OF THE LOGIC EQUIVALENCE OF THE BRAIN AND COMPUTERS ON A
HIGH LEVEL 263 9.8 "CONNECTIONIST MODELS" 264 9.9 HOW CAN THE NEURAL
COMPUTERS BE PROGRAMMED? 267 10. OPTICAL ASSOCIATIVE MEMORIES 26 9 10.1
NONHOLOGRAPHIC METHODS 269 10.2 GENERAL ASPECTS OF HOLOGRAPHIC MEMORIES
271 10.3 A SIMPLE PRINCIPLE OF HOLOGRAPHIC ASSOCIATIVE MEMORY 273 10.4
ADDRESSING IN HOLOGRAPHIC MEMORIES 275 10.5 RECENT ADVANCES OF OPTICAL
ASSOCIATIVE MEMORIES 280 BIBLIOGRAPHY ON PATTERN RECOGNITION 285
REFERENCES 289 SUBJECT INDEX 301 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Kohonen, Teuvo |
| author_facet | Kohonen, Teuvo |
| author_role | aut |
| author_sort | Kohonen, Teuvo |
| author_variant | t k tk |
| building | Verbundindex |
| bvnumber | BV022007756 |
| callnumber-first | Q - Science |
| callnumber-label | Q325 |
| callnumber-raw | Q325 |
| callnumber-search | Q325 |
| callnumber-sort | Q 3325 |
| callnumber-subject | Q - General Science |
| classification_rvk | CP 5000 SK 880 ST 285 ST 300 |
| ctrlnum | (OCoLC)20015322 (DE-599)BVBBV022007756 |
| dewey-full | 003/.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 003 - Systems |
| dewey-raw | 003/.7 |
| dewey-search | 003/.7 |
| dewey-sort | 13 17 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Psychologie Mathematik |
| discipline_str_mv | Informatik Psychologie Mathematik |
| edition | 3. ed. |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03857nam a2200913zcb4500</leader><controlfield tag="001">BV022007756</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20040301000000.0</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">900221s1989 d||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3540513876</subfield><subfield code="9">3-540-51387-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">0387513876</subfield><subfield code="9">0-387-51387-6</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)20015322</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV022007756</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-706</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">Q325</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">003/.7</subfield><subfield code="2">20</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">CP 5000</subfield><subfield code="0">(DE-625)18991:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 880</subfield><subfield code="0">(DE-625)143266:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 285</subfield><subfield code="0">(DE-625)143648:</subfield><subfield code="2">rvk</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="100" ind1="1" ind2=" "><subfield code="a">Kohonen, Teuvo</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Self-organization and associative memory</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">3. ed.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin [u.a.]</subfield><subfield code="b">Springer</subfield><subfield code="c">1989</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XV, 312 S.</subfield><subfield code="b">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">Springer series in information sciences</subfield><subfield code="v">8</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Associative storage</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Memory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Self-organizing systems</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Psychologie</subfield><subfield code="0">(DE-588)4047704-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Assoziativspeicher</subfield><subfield code="0">(DE-588)4124575-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Nervennetz</subfield><subfield code="0">(DE-588)4041638-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Mathematische Psychologie</subfield><subfield code="0">(DE-588)4126558-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Gedächtnis</subfield><subfield code="0">(DE-588)4019614-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Selbsteinstellendes System</subfield><subfield code="0">(DE-588)4054398-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Selbstbestimmung</subfield><subfield code="0">(DE-588)4135889-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Selbst organisierendes System</subfield><subfield code="0">(DE-588)4054424-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Modell</subfield><subfield code="0">(DE-588)4039798-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Assoziatives Gedächtnis</subfield><subfield code="0">(DE-588)4290792-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Selbstbestimmung</subfield><subfield code="0">(DE-588)4135889-2</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">Assoziatives Gedächtnis</subfield><subfield code="0">(DE-588)4290792-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="2" ind2="0"><subfield code="a">Assoziativspeicher</subfield><subfield code="0">(DE-588)4124575-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="2" ind2="1"><subfield code="a">Gedächtnis</subfield><subfield code="0">(DE-588)4019614-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="2" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="3" ind2="0"><subfield code="a">Gedächtnis</subfield><subfield code="0">(DE-588)4019614-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="3" ind2="1"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="3" ind2=" "><subfield code="8">2\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="4" ind2="0"><subfield code="a">Gedächtnis</subfield><subfield code="0">(DE-588)4019614-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="4" ind2="1"><subfield code="a">Psychologie</subfield><subfield code="0">(DE-588)4047704-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="4" ind2=" "><subfield code="8">3\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="5" ind2="0"><subfield code="a">Nervennetz</subfield><subfield code="0">(DE-588)4041638-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="5" ind2="1"><subfield code="a">Modell</subfield><subfield code="0">(DE-588)4039798-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="5" ind2=" "><subfield code="8">4\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="6" ind2="0"><subfield code="a">Gedächtnis</subfield><subfield code="0">(DE-588)4019614-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="6" ind2="1"><subfield code="a">Mathematische Psychologie</subfield><subfield code="0">(DE-588)4126558-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="6" ind2=" "><subfield code="8">5\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="7" ind2="0"><subfield code="a">Selbsteinstellendes System</subfield><subfield code="0">(DE-588)4054398-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="7" ind2=" "><subfield code="8">6\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="8" ind2="0"><subfield code="a">Selbst organisierendes System</subfield><subfield code="0">(DE-588)4054424-2</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="8" ind2=" "><subfield code="8">7\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Springer series in information sciences</subfield><subfield code="v">8</subfield><subfield code="w">(DE-604)BV000008063</subfield><subfield code="9"></subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">HEBIS Datenaustausch Darmstadt</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=015222388&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-015222388</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">2\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">3\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">4\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">5\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">6\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">7\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield></record></collection> |
| id | DE-604.BV022007756 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:11:42Z |
| indexdate | 2024-07-09T20:49:09Z |
| institution | BVB |
| isbn | 3540513876 0387513876 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015222388 |
| oclc_num | 20015322 |
| open_access_boolean | |
| owner | DE-706 |
| owner_facet | DE-706 |
| physical | XV, 312 S. graph. Darst. |
| publishDate | 1989 |
| publishDateSearch | 1989 |
| publishDateSort | 1989 |
| publisher | Springer |
| record_format | marc |
| series | Springer series in information sciences |
| series2 | Springer series in information sciences |
| spelling | Kohonen, Teuvo Verfasser aut Self-organization and associative memory 3. ed. Berlin [u.a.] Springer 1989 XV, 312 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Springer series in information sciences 8 Associative storage Memory Self-organizing systems Psychologie (DE-588)4047704-6 gnd rswk-swf Assoziativspeicher (DE-588)4124575-1 gnd rswk-swf Nervennetz (DE-588)4041638-0 gnd rswk-swf Mathematische Psychologie (DE-588)4126558-0 gnd rswk-swf Gedächtnis (DE-588)4019614-8 gnd rswk-swf Selbsteinstellendes System (DE-588)4054398-5 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Selbstbestimmung (DE-588)4135889-2 gnd rswk-swf Selbst organisierendes System (DE-588)4054424-2 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Assoziatives Gedächtnis (DE-588)4290792-5 gnd rswk-swf Selbstbestimmung (DE-588)4135889-2 s DE-604 Assoziatives Gedächtnis (DE-588)4290792-5 s Assoziativspeicher (DE-588)4124575-1 s Gedächtnis (DE-588)4019614-8 s 1\p DE-604 Künstliche Intelligenz (DE-588)4033447-8 s 2\p DE-604 Psychologie (DE-588)4047704-6 s 3\p DE-604 Nervennetz (DE-588)4041638-0 s Modell (DE-588)4039798-1 s 4\p DE-604 Mathematische Psychologie (DE-588)4126558-0 s 5\p DE-604 Selbsteinstellendes System (DE-588)4054398-5 s 6\p DE-604 Selbst organisierendes System (DE-588)4054424-2 s 7\p DE-604 Springer series in information sciences 8 (DE-604)BV000008063 HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015222388&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 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 5\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 6\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 7\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kohonen, Teuvo Self-organization and associative memory Springer series in information sciences Associative storage Memory Self-organizing systems Psychologie (DE-588)4047704-6 gnd Assoziativspeicher (DE-588)4124575-1 gnd Nervennetz (DE-588)4041638-0 gnd Mathematische Psychologie (DE-588)4126558-0 gnd Gedächtnis (DE-588)4019614-8 gnd Selbsteinstellendes System (DE-588)4054398-5 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Selbstbestimmung (DE-588)4135889-2 gnd Selbst organisierendes System (DE-588)4054424-2 gnd Modell (DE-588)4039798-1 gnd Assoziatives Gedächtnis (DE-588)4290792-5 gnd |
| subject_GND | (DE-588)4047704-6 (DE-588)4124575-1 (DE-588)4041638-0 (DE-588)4126558-0 (DE-588)4019614-8 (DE-588)4054398-5 (DE-588)4033447-8 (DE-588)4135889-2 (DE-588)4054424-2 (DE-588)4039798-1 (DE-588)4290792-5 |
| title | Self-organization and associative memory |
| title_auth | Self-organization and associative memory |
| title_exact_search | Self-organization and associative memory |
| title_exact_search_txtP | Self-organization and associative memory |
| title_full | Self-organization and associative memory |
| title_fullStr | Self-organization and associative memory |
| title_full_unstemmed | Self-organization and associative memory |
| title_short | Self-organization and associative memory |
| title_sort | self organization and associative memory |
| topic | Associative storage Memory Self-organizing systems Psychologie (DE-588)4047704-6 gnd Assoziativspeicher (DE-588)4124575-1 gnd Nervennetz (DE-588)4041638-0 gnd Mathematische Psychologie (DE-588)4126558-0 gnd Gedächtnis (DE-588)4019614-8 gnd Selbsteinstellendes System (DE-588)4054398-5 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Selbstbestimmung (DE-588)4135889-2 gnd Selbst organisierendes System (DE-588)4054424-2 gnd Modell (DE-588)4039798-1 gnd Assoziatives Gedächtnis (DE-588)4290792-5 gnd |
| topic_facet | Associative storage Memory Self-organizing systems Psychologie Assoziativspeicher Nervennetz Mathematische Psychologie Gedächtnis Selbsteinstellendes System Künstliche Intelligenz Selbstbestimmung Selbst organisierendes System Modell Assoziatives Gedächtnis |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015222388&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000008063 |
| work_keys_str_mv | AT kohonenteuvo selforganizationandassociativememory |