Neural networks as cybernetic systems:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | German |
| Published: |
Stuttgart [u.a.]
Thieme
1996
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | VIII, 167 S. Ill., graph. Darst., Kt. |
| ISBN: | 3131021810 0865776725 |
Staff View
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| 245 | 1 | 0 | |a Neural networks as cybernetic systems |c Holk Cruse |
| 264 | 1 | |a Stuttgart [u.a.] |b Thieme |c 1996 | |
| 300 | |a VIII, 167 S. |b Ill., graph. Darst., Kt. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Cybernetics | |
| 650 | 4 | |a Nerve Net | |
| 650 | 4 | |a Neural Networks (Computer) | |
| 650 | 4 | |a Neural networks (Computer science) | |
| 650 | 4 | |a Neural networks (Neurobiology) | |
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Record in the Search Index
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|---|---|
| adam_text |
CONTENTS
43
1
INTRODUCTION
.
1
7
THE
STUDY
OF
NONLINEAR
SYSTEMS
.
.
45
1.1
SYMBOLS
.
2
BOX
2
AN
EXAMPLE:
THE
OPTOMOTER
1.2
LINEAR
SYSTEMS
.
.
3
RESPONSE
.
.
47
1.3
THE
TASKS
OF
SYSTEMS
THEORY
INVESTIGATIONS
.
.
4
8
FEEDBACK
SYSTEMS
.
.
49
8.1
OPEN
LOOP
CONTROL-CLOSED
LOOP
2
THE
MOST
IMPORTANT
INPUT
CONTROL
.
.
49
FUNCTIONS
.
.
5
8.2
THE
MOST
IMPORTANT
TERMS
.
.
49
2.1
THE
STEP
FUNCTION
.
.
5
8.3
A
SIMPLE
FEEDBACK
SYSTEM
.
.
51
2.2
THE
IMPULSE
FUNCTION
.
.
5
8.4
THE
STUDY
OF
A
FEEDBACK
SYSTEM
.
.
53
2.3
THE
SINE
FUNCTION
.
.
7
8.5
FEEDBACK
CONTROL
SYSTEMS
WITH
2.4
THE
STATISTICAL
FUNCTION
.
9
DYNAMIC
PROPERTIES
.
.
55
2.5
THE
RAMP
FUNCTION
.
.
10
8.6
THE
STABILITY
OF
FEEDBACK
SYSTEMS
.
.
59
BOX
3
THE
PUPIL
FEEDBACK
SYSTEM
.
.
62
3
THE
FOURIER
ANALYSIS
.
.
11
8.7
FURTHER
TYPES
OF
FEEDBACK
CONTROL
SYSTEMS
.
.
64
4
THE
PROPERTIES
OF
THE
MOST
8.8
AN
EXAMPLE
.
.
65
IMPORTANT
FILTERS
.
.
13
8.9
REAFFERENCE
PRINCIPLE
.
.
68
4.1
FIRST
ORDER
LOW-PASS
FILTER
.
.
13
8.10
THE
DYNAMIC
PROPERTIES
OF
A
4.2
FIRST
ORDER
HIGH-PASS
FILTER
.
.
15
SIMPLIFIED
NEURON
.
.
69
4.3
N-TH
ORDER
LOW-PASS
FILTER
.
.
18
4.4
N-TH
ORDER
HIGH-PASS
FILTERS
.
.
19
9
MASSIVELY
PARALLEL
SYSTEMS
.
.
71
4.5
BAND-PASS
FILTER
.
.
20
4.6
LEAD-LAG
SYSTEM
.
.
22
10
FEEDFORWARD
NETWORKS
.
.
76
4.7
PURE
TIME
DELAY
.
.
25
10.1
SPATIAL
LOW-PASS
FILTER
.
.
76
BOX
1
AN
ASYMMETRICAL
BAND-PASS
FILTER
.
.
26
10.2
SPATIAL
HIGH-PASS
FILTER
.
.
78
4.8
INTEGRATOR
AND
DIFFERENTIATOR
.
.
27
10.3
SPATIAL
BAND-PASS
FILTER
.
.
79
4.9
OSCILLATING
SYSTEMS
.
.
28
BOX
4
SPATIAL
FILTERS
IN
THE
MAMMALIAN
4.10
COMBINATION
OF
DIFFERENT
FILTERS
.
.
30
VISUAL
SYSTEM
.
.
80
10.4
A
WINNER-TAKE-ALL
NETWORK
.
.
82
5
THE
CHARACTERISTICS
.
.
33
10.5
LEARNING
MATRIX
.
82
5.1
GENERAL
REMARKS
.
.
33
10.6
PERCEPTRON
.
84
5.2
THE
STATIC
CHARACTERISTIC
.
.
33
10.7
MULTILAYERED
FEEDFORWARD
NETS
.
85
5.3
THE
DYNAMIC
CHARACTERISTIC
.
.
40
11
RECURRENT
NETWORKS
.
90
6
COMBINATION
OF
LINEAR
AND
11.1
PATTERN
GENERATION
.
92
NONLINEAR
ELEMENTS
.
42
BOX
5
DIFFUSION
ALGORITHMS
.
93
6.1
THE
SEQUENCE
LINEAR
11.2
RECURRENT
WINNER-TAKE-ALL
NETWORK
96
ELEMENT-NONLINEAR
ELEMENT
.
42
11.3
OPTIMIZATION
.
97
6.2
THE
SEQUENCE
NONLINEAR
11.4
ASSOCIATIVE
STORAGE
.
98
ELEMENT-LINEAR
ELEMENT
.
42
11.5
DYNAMIC
NETWORKS
.
99
63
UNIDIRECTIONAL
RATE
SENSITIVE
(URS)
ELEMENT
.
BOX
6
SPATIAL
INTEGRATOR
.
103
12
LEARNING
.
12.1
HEBB'S
RULE
.
12.2
DELTA
RULE
.
12.3
GENERALIZED
DELTA
RULE
.
12.4
REINFORCEMENT
LEARNING
.
12.5
GENETIC
ALGORITHMS
.
12.6
COMPETITIVE
LEARNING
.
13
FEATURE
MAPS
.
BOX
7
HISTORICAL
NOTE
.
14
SOME
SPECIAL
RECURRENT
NETWORKS
.
15
ANIMATS
.
105
105
106
108
110
114
115
119
122
124
131
16
DEVELOPMENT
OF
COMPLEXITY
IN
ANIMATS
.
139
BOX
8
ACTIVE
PERCEPTION
.
140
17
EMERGENT
PROPERTIES
.
146
18
THE
INTERNAL
ASPECT
-
MIGHT
MACHINES
HAVE
FEELINGS?
.
148
APPENDIX!
.
153
APPENDIX
II
.
156
REFERENCES
.
157
INDEX
.
161 |
| any_adam_object | 1 |
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| classification_rvk | ST 300 ST 301 WW 4120 |
| classification_tum | DAT 717f |
| ctrlnum | (OCoLC)34675893 (DE-599)BVBBV010755572 |
| dewey-full | 612.8 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 612 - Human physiology |
| dewey-raw | 612.8 |
| dewey-search | 612.8 |
| dewey-sort | 3612.8 |
| dewey-tens | 610 - Medicine and health |
| discipline | Biologie Informatik Medizin |
| format | Book |
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| illustrated | Illustrated |
| indexdate | 2024-08-18T00:41:18Z |
| institution | BVB |
| isbn | 3131021810 0865776725 |
| language | German |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007183597 |
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| physical | VIII, 167 S. Ill., graph. Darst., Kt. |
| publishDate | 1996 |
| publishDateSearch | 1996 |
| publishDateSort | 1996 |
| publisher | Thieme |
| record_format | marc |
| spelling | Cruse, Holk 1942- Verfasser (DE-588)108283704 aut Neural networks as cybernetic systems Holk Cruse Stuttgart [u.a.] Thieme 1996 VIII, 167 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Cybernetics Nerve Net Neural Networks (Computer) Neural networks (Computer science) Neural networks (Neurobiology) Nervennetz (DE-588)4041638-0 gnd rswk-swf Neurokybernetik (DE-588)4041883-2 gnd rswk-swf Modell (DE-588)4039798-1 gnd rswk-swf Nervennetz (DE-588)4041638-0 s Modell (DE-588)4039798-1 s Neurokybernetik (DE-588)4041883-2 s DE-604 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007183597&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Cruse, Holk 1942- Neural networks as cybernetic systems Cybernetics Nerve Net Neural Networks (Computer) Neural networks (Computer science) Neural networks (Neurobiology) Nervennetz (DE-588)4041638-0 gnd Neurokybernetik (DE-588)4041883-2 gnd Modell (DE-588)4039798-1 gnd |
| subject_GND | (DE-588)4041638-0 (DE-588)4041883-2 (DE-588)4039798-1 |
| title | Neural networks as cybernetic systems |
| title_auth | Neural networks as cybernetic systems |
| title_exact_search | Neural networks as cybernetic systems |
| title_full | Neural networks as cybernetic systems Holk Cruse |
| title_fullStr | Neural networks as cybernetic systems Holk Cruse |
| title_full_unstemmed | Neural networks as cybernetic systems Holk Cruse |
| title_short | Neural networks as cybernetic systems |
| title_sort | neural networks as cybernetic systems |
| topic | Cybernetics Nerve Net Neural Networks (Computer) Neural networks (Computer science) Neural networks (Neurobiology) Nervennetz (DE-588)4041638-0 gnd Neurokybernetik (DE-588)4041883-2 gnd Modell (DE-588)4039798-1 gnd |
| topic_facet | Cybernetics Nerve Net Neural Networks (Computer) Neural networks (Computer science) Neural networks (Neurobiology) Nervennetz Neurokybernetik Modell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007183597&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT cruseholk neuralnetworksascyberneticsystems |