Knowledge-based neurocomputing: a Fuzzy Logic Approach
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2009
|
| Series: | Studies in Fuzziness and Soft Computing
234 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XV, 100 S. graf. Darst. 235 mm x 155 mm |
| ISBN: | 9783540880769 |
Staff View
MARC
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| 100 | 1 | |a Kolman, Eyal |e Verfasser |4 aut | |
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Record in the Search Index
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|---|---|
| adam_text | Contents
Preface
.........................................................
VII
List of Abbreviations
...........................................
IX
List of Symbols
.................................................
XI
1
Introduction
................................................ 1
1.1
Artificial Neural Networks (ANNs)
......................... 2
1.2
Fuzzy Rule-Bases (FRBs)
................................. 3
1.3
The ANN-FRB Synergy
................................... 4
1.4
Knowledge-Based Neurocomputing
......................... 5
1.4.1
Knowledge Extraction from ANNs
.................... 5
1.4.2
Knowledge-Based Design of ANNs
.................... 9
1.5
The
FARB:
A Neuro-fuzzy Equivalence
..................... 11
2
The
FARB
.................................................. 13
2.1
Definition
............................................... 15
2.2
Input-Output Mapping
.................................... 18
3
The FARB-ANN Equivalence
.............................. 21
3.1
The
FARB
and Feedforward ANNs
......................... 21
3.1.1
Example
1:
Knowledge Extraction from a
Feedforward ANN
.................................. 22
3.1.2
Example
2:
Knowledge-Based Design of a
Feedforward ANN
.................................. 24
3.2
The
FARB
and First-Order RNNs
.......................... 26
3.2.1
First Approach
..................................... 26
3.2.2
Example
3:
Knowledge Extraction from a
Simple RNN
....................................... 27
3.2.3
Second Approach
................................... 28
XIV Contents
3.2.4
Third Approach
.................................... 29
3.2.5
Example
4:
Knowledge Extraction from an RNN
....... 30
3.2.6
Example
5:
Knowledge-Based Design of an RNN
....... 32
3.3
The
FARB
and Second-Order RNNs
........................ 33
3.4
Summary
................................................ 35
4
Rule Simplification
......................................... 37
4.1
Sensitivity Analysis
....................................... 37
4.2
A Procedure for Simplifying
a FARB
........................ 39
5
Knowledge Extraction Using the
FARB
..................... 41
5.1
The Iris Classification Problem
............................. 41
5.2
The LED Display Recognition Problem
..................... 44
5.2.1
Knowledge Extraction Using the
FARB
............... 46
5.2.2
FARB
Simplification
................................ 46
5.2.3
Analysis of the FRB
................................ 48
5.3
The La Language Recognition Problem
...................... 50
5.3.1
Formal Languages
.................................. 50
5.3.2
Formal Languages and RNNs
........................ 51
5.3.3
The Trained RNN
.................................. 51
5.3.4
Knowledge Extraction Using the
FARB
............... 53
6
Knowledge-Based Design of ANNs
.......................... 59
6.1
The Direct Approach
..................................... 60
6.1.1
KBD of an ANN Recognizing L4
..................... 60
6.2
The Modular Approach
................................... 63
6.2.1
The Counter Module
................................ 63
6.2.2
The Sequence-Counter Module
....................... 66
6.2.3
The String-Comparator Module
...................... 66
6.2.4
The String-to-Num Converter Module
................. 67
6.2.5
The Num-to-String Converter Module
................. 68
6.2.6
The Soft Threshold Module
.......................... 68
6.2.7
KBD of an RNN for Recognizing the Extended
L4 Language
....................................... 69
6.2.8
KBD of an RNN for Recognizing the
AB
Language
..... 71
6.2.9
KBD of an RNN for Recognizing the Balanced
Parentheses Language
............................... 72
6.2.10
KBD of an RNN for Recognizing the 0nln Language
.... 74
7
Conclusions and Future Research
........................... 77
7.1
Future Research
.......................................... 77
7.1.1
Regularization of Network Training
................... 78
7.1.2
Extracting Knowledge during the Learning Process
..... 79
7.1.3
Knowledge Extraction from Support Vector Machines
... 79
7.1.4
Knowledge Extraction from Trained Networks
.......... 80
Contents
XV
A Proofs
...................................................... 83
В
Details of the LED Recognition Network
................... 87
References
...................................................... 89
Index
........................................................... 99
|
| any_adam_object | 1 |
| author | Kolman, Eyal Margaliot, Michael |
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| author_sort | Kolman, Eyal |
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| callnumber-subject | QA - Mathematics |
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| ctrlnum | (OCoLC)269435337 (DE-599)DNB990118088 |
| dewey-full | 006.32 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.32 |
| dewey-search | 006.32 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Mathematik |
| format | Book |
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| id | DE-604.BV035475221 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T21:36:06Z |
| institution | BVB |
| isbn | 9783540880769 |
| language | English |
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| physical | XV, 100 S. graf. Darst. 235 mm x 155 mm |
| publishDate | 2009 |
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| series | Studies in Fuzziness and Soft Computing |
| series2 | Studies in Fuzziness and Soft Computing |
| spelling | Kolman, Eyal Verfasser aut Knowledge-based neurocomputing a Fuzzy Logic Approach Eyal Kolman and Michael Margaliot Berlin [u.a.] Springer 2009 XV, 100 S. graf. Darst. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Studies in Fuzziness and Soft Computing 234 Fuzzy logic Neural networks (Computer science) Fuzzy-Regelsystem (DE-588)4728095-5 gnd rswk-swf Wissensrepräsentation (DE-588)4049534-6 gnd rswk-swf Wissensextraktion (DE-588)4546354-2 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s Fuzzy-Regelsystem (DE-588)4728095-5 s Wissensextraktion (DE-588)4546354-2 s Wissensrepräsentation (DE-588)4049534-6 s DE-604 Margaliot, Michael Verfasser aut Studies in Fuzziness and Soft Computing 234 (DE-604)BV021858135 234 Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017394853&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kolman, Eyal Margaliot, Michael Knowledge-based neurocomputing a Fuzzy Logic Approach Studies in Fuzziness and Soft Computing Fuzzy logic Neural networks (Computer science) Fuzzy-Regelsystem (DE-588)4728095-5 gnd Wissensrepräsentation (DE-588)4049534-6 gnd Wissensextraktion (DE-588)4546354-2 gnd Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4728095-5 (DE-588)4049534-6 (DE-588)4546354-2 (DE-588)4226127-2 |
| title | Knowledge-based neurocomputing a Fuzzy Logic Approach |
| title_auth | Knowledge-based neurocomputing a Fuzzy Logic Approach |
| title_exact_search | Knowledge-based neurocomputing a Fuzzy Logic Approach |
| title_full | Knowledge-based neurocomputing a Fuzzy Logic Approach Eyal Kolman and Michael Margaliot |
| title_fullStr | Knowledge-based neurocomputing a Fuzzy Logic Approach Eyal Kolman and Michael Margaliot |
| title_full_unstemmed | Knowledge-based neurocomputing a Fuzzy Logic Approach Eyal Kolman and Michael Margaliot |
| title_short | Knowledge-based neurocomputing |
| title_sort | knowledge based neurocomputing a fuzzy logic approach |
| title_sub | a Fuzzy Logic Approach |
| topic | Fuzzy logic Neural networks (Computer science) Fuzzy-Regelsystem (DE-588)4728095-5 gnd Wissensrepräsentation (DE-588)4049534-6 gnd Wissensextraktion (DE-588)4546354-2 gnd Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Fuzzy logic Neural networks (Computer science) Fuzzy-Regelsystem Wissensrepräsentation Wissensextraktion Neuronales Netz |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017394853&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV021858135 |
| work_keys_str_mv | AT kolmaneyal knowledgebasedneurocomputingafuzzylogicapproach AT margaliotmichael knowledgebasedneurocomputingafuzzylogicapproach |