Concepts for neural networks: a survey
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
London [u.a.]
Springer
1998
|
| Schriftenreihe: | Perspectives in neural computing
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XV, 307 S. Ill., graph. Darst. |
| ISBN: | 3540761632 |
Internformat
MARC
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| 245 | 1 | 0 | |a Concepts for neural networks |b a survey |c L. J. Landau ... (eds.) |
| 264 | 1 | |a London [u.a.] |b Springer |c 1998 | |
| 300 | |a XV, 307 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Perspectives in neural computing | |
| 650 | 4 | |a Neural networks (Computer science) | |
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Datensatz im Suchindex
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| adam_text |
CONTENTS
CHAPTER
SUMMARIES
XI
1
NEURAL
NETWORKS:
AN
OVERVIEW
1
1.1
INTRODUCTION
.
1
1.2
WHAT
IS
A
NEURAL
NETWORK?
.
3
1.3
NEURAL
NETWORK
DYNAMICS
.
5
1.4
TRAINING
A
NEURAL
NETWORK
.
6
1.5
PROBLEMS
FOR
ARTIFICIAL
NEURAL
NETWORKS
.
10
1.6
PROBLEMS
FOR
NEUROBIOLOGICALLY
REALISTIC
NEURAL
NETWORKS
.
10
1.7
CONCLUSIONS
.
11
1.8
FURTHER
READING
.
11
1.9
BIBLIOGRAPHY
.
11
2
A
BEGINNER
'
S
GUIDE
TO
THE
MATHEMATICS
OF
NEURAL
NETWORKS
13
2.1
INTRODUCTION:
NEURAL
INFORMATION
PROCESSING
.
13
2.2
FROM
BIOLOGY
TO
MATHEMATICAL
MODELS
.
16
2.2.1
FROM
BIOLOGICAL
NEURONS
TO
MODEL
NEURONS
.
16
2.2.2
UNIVERSALITY
OF
MODEL
NEURONS
.
20
2.2.3
DIRECTIONS
AND
STRATEGIES
.
22
2.3
NEURAL
NETWORKS
AS
ASSOCIATIVE
MEMORIES
.
24
2.3.1
RECIPES
FOR
STORING
PATTERNS
AND
PATTERN
SEQUENCES
.
.
25
2.3.2
SYMMETRIC
NETWORKS:
THE
ENERGY
PICTURE
.
30
2.3.3
SOLVING
MODELS
OF
NOISY
ATTRACTOR
NETWORKS
.
31
2.4
CREATING
MAPS
OF
THE
OUTSIDE
WORLD
.
35
2.4.1
MAP
FORMATION
THROUGH
COMPETITIVE
LEARNING
.
36
2.4.2
SOLVING
MODELS
OF
MAP
FORMATION
.
39
2.5
LEARNING
A
RULE
FROM
AN
EXPERT
.
44
2.5.1
PERCEPTRONS
.
45
2.5.2
MULTI-LAYER
NETWORKS
.
48
2.5.3
CALCULATING
WHAT
IS
ACHIEVABLE
.
53
2.5.4
SOLVING
THE
DYNAMICS
OF
LEARNING
FOR
PERCEPTRONS
.
57
2.6
PUZZLING
MATHEMATICS
.
61
2.6.1
COMPLEXITY
DUE
TO
FRUSTRATION,
DISORDER
AND
PLASTICITY
61
2.6.2
THE
WORLD
OF
REPLICA
THEORY
.
64
VIII
CONTENTS
2.7
FURTHER
READING
.
68
2.8
BIBLIOGRAPHY
.
69
3
NEUROBIOLOGICAL
MODELLING
71
3.1
INTRODUCTION
.
71
3.2
THE
SINGLE
NERVE
CELL
.
72
3.3
RETINAL
PROCESSING
.
77
3.4
THE
CORTICAL
STREAMS
.
81
3.5
THE
VENTRAL
STREAM
.
84
3.6
THE
DORSAL
STREAM
.
87
3.7
OBJECT
CONSTRUCTION
.
88
3.8
MODELLING
THE
PROCESSING
STREAMS
.
91
3.9
CONCLUSIONS
.
91
3.10
BIBLIOGRAPHY
.
92
4
NEURAL
NETWORK
CONTROL
OF
A
SIMPLE
MOBILE
ROBOT
95
4.1
INTRODUCTION
.
95
4.2
THE
ROBOT
'
INSECTS
'
.
96
4.3
NEURAL
NETWORK
FOR
OBSTACLE
AVOIDANCE
.
98
4.3.1
LEARNING
STRATEGY
.
98
4.3.2
RESULTS
.
100
4.4
A
COMPOUND
EYE
.
101
4.4.1
THE
FIRST
COMPOUND
EYE
.
101
4.4.2
ESTIMATING
ROBOT
POSITION
.
101
4.4.3
WEIGHTLESS
NETWORKS
.
102
4.4.4
MULTI
DISCRIMINATOR
NETWORK
.
103
4.4.5
PROCESSING
GREY
LEVEL
DATA
.
103
4.4.6
WEIGHTLESS
NETWORKS
AND
THE
FIRST
EYE
.
103
4.4.7
RESULTS
.
104
4.4.8
THE
SECOND
EYE
.
104
4.5
NAVIGATION
.
106
4.6
DISCUSSION
.
106
4.7
BIBLIOGRAPHY
.
106
5
A
CONNECTIONIST
APPROACH
TO
SPATIAL
MEMORY
AND
PLANNING
109
5.1
OVERVIEW
.
109
5.2
INTRODUCTION
.
110
5.3
BIOLOGICAL
SPATIAL
MEMORY
.
113
5.3.1
STIMULUS-RESPONSE
THEORY
.
113
5.3.2
COGNITIVE
MAPS
.
114
5.3.3
TOPOLOGICAL
NETWORK-MAPS
.
116
5.3.4
PLANNING
.
118
5.3.5
SUMMARY
.
118
5.4
CONNECTIONIST
IMPLEMENTATION
.
119
5.4.1
PRINCIPLES
OF
A
NETWORK-MAP
BASED
ARTIFICIAL
SPATIAL
MEM
ORY
.
119
CONTENTS
IX
5.4.2
SPARSE
VERSUS
DISTRIBUTED
REPRESENTATION
OF
VIEWS
.
.
.
120
5.4.3
IMPLEMENTATION
OF
A
SPARSE
MODEL
.
124
5.4.4
A
CONSTRUCTIVE
LEARNING
PROCEDURE
FOR
STATES
AND
ACTIONSL26
5.4.5
PLANNING
AND
SEARCH
PROCEDURE
.
127
5.5
AN
EXPERIMENT
WITH
A
ROBOT
.
128
5.5.1
TASK
AND
EXPERIMENTAL
SET-UP
.
128
5.5.2
LEARNING
AND
PLANNING
TEST
.
129
5.6
DISCUSSION
.
131
5.7
CONCLUSION
.
135
5.8
APPENDIX:
VISION
SYSTEM
FOR
LETTER
DETECTION
AND
RECOGNITION
.
136
5.9
APPENDIX:
VISION
SYSTEM
FOR
STATE
RECOGNITION
.
137
5.10
APPENDIX:
NOTES
ON
A
BIOLOGICALLY
PLAUSIBLE
IMPLEMENTATION
.
.
137
5.11
BIBLIOGRAPHY
.
138
6
TURING
'
S
PHILOSOPHICAL
ERROR?
147
6.1
TURING
'
S
MACHINE
.
147
6.2
DIGITAL
PROBLEMS
.
148
6.3
TURING
'
S
THESIS
.
150
6.4
HOW
TURING
BUILT
HIS
UNIVERSAL
MACHINE
.
152
6.5
GODEL
'
S
ATTEMPT
TO
BREAK
TURING
'
S
THESIS
.
154
6.6
YES-OR-NO
QUESTIONS
.
155
6.7
MATERIAL
AND
FORMAL
PROOFS
.
156
6.8
THE
DIALECTICA
LECTURE
.
160
6.9
A
CALCULUS
OF
CONCEPTS?
.
163
6.10
TURING
'
S
ERROR
.
165
6.11
FURTHER
READING
.
168
6.12
BIBLIOGRAPHY
.
169
7
PENROSE
'
S
PHILOSOPHICAL
ERROR
171
7.1
CAN
COMPUTERS
THINK?
.
171
7.2
SOLVING
PROBLEMS
IN
ARITHMETIC
.
179
7.3
THE
BARBER
PARADOX
.
187
7.4
GODEL
'
S
THEOREM
.
192
7.5
PENROSE
.
196
7.6
A
COMPUTATIONAL
MODEL
FOR
THOUGHT?
.
201
7.7
CAN
COMPUTERS
THINK?
.
208
7.8
APPENDIX:
FILLING
IN
SOME
DETAILS
.
213
7.9
BIBLIOGRAPHY
.
222
8
ATTENTIONAL
MODULATION
IN
VISUAL
PATHWAYS
225
8.1
INTRODUCTION
.
225
8.2
STRUCTURAL
EQUATION
MODELLING
.
227
8.3
DESIGN
AND
IMAGE
ACQUISITION
.
231
8.4
IMAGE
ANALYSIS
AND
CATEGORICAL
COMPARISONS
.
232
8.5
MODELLING
OF
THE
POSTERIOR
VISUAL
PATHWAY
.
233
8.6
MODELLING
MODULATION
BY
INTERACTION
TERMS
.
233
X
CONTENTS
8.7
INTERACTION
EFFECTS
DEMONSTRATED
WITH
REGRESSION
ANALYSIS
.
.
235
8.8
REGIONAL
SPECIFICITY
.
235
8.9
CONCLUSION
.
238
8.10
BIBLIOGRAPHY
.
238
9
NEURAL
NETWORKS
AND
THE
MIND
243
9.1
INTRODUCTION
.
243
9.2
THE
RELATIONAL
MIND
.
244
9.3
EXPLORING
THE
RELATIONAL
MIND
MODEL
.
246
9.4
MEMORY
IN
THE
RELATIONAL
MIND
MODEL
.
246
9.5
A
NEURAL
CANDIDATE
FOR
GLOBAL
CONTROL
.
249
9.6
CONSCIOUSNESS
AND
SITES
OF
WORKING
MEMORY
.
251
9.6.1
PSYCHOLOGICAL
BASES
FOR
WORKING
MEMORY
.
251
9.6.2
PET
STUDIES
OF
WORKING
MEMORY
.
255
9.7
AWARENESS
OF
WORDS
.
256
9.8
ACTIVITY
'
BUBBLES
'
IN
CORTEX
.
258
9.8.1
GENERAL
DISCUSSION
.
258
9.8.2
TECHNICAL
RESULTS
.
259
9.9
THE
EMERGENCE
OF
QUALIA
.
261
9.10
DISCUSSION
.
263
9.11
BIBLIOGRAPHY
.
264
10
CONFUSIONS
ABOUT
CONSCIOUSNESS
269
10.1
CONSCIOUSNESS
STUDIES
.
269
10.2
BIBLIOGRAPHY
.
273
11
ROUND
TABLE
DISCUSSION
275
11.1
PRESENTATIONS
.
275
11.2
AUDIENCE
PARTICIPATION
.
284
INDEX
303 |
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| institution | BVB |
| isbn | 3540761632 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007744318 |
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| spelling | Concepts for neural networks a survey L. J. Landau ... (eds.) London [u.a.] Springer 1998 XV, 307 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Perspectives in neural computing Neural networks (Computer science) Neuronales Netz (DE-588)4226127-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Neuronales Netz (DE-588)4226127-2 s DE-604 Landau, Lawrence J. 1942- Sonstige (DE-588)115432396 oth DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007744318&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Concepts for neural networks a survey Neural networks (Computer science) Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4143413-4 |
| title | Concepts for neural networks a survey |
| title_auth | Concepts for neural networks a survey |
| title_exact_search | Concepts for neural networks a survey |
| title_full | Concepts for neural networks a survey L. J. Landau ... (eds.) |
| title_fullStr | Concepts for neural networks a survey L. J. Landau ... (eds.) |
| title_full_unstemmed | Concepts for neural networks a survey L. J. Landau ... (eds.) |
| title_short | Concepts for neural networks |
| title_sort | concepts for neural networks a survey |
| title_sub | a survey |
| topic | Neural networks (Computer science) Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Neural networks (Computer science) Neuronales Netz Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007744318&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT landaulawrencej conceptsforneuralnetworksasurvey |