Neural computing architectures : the design of brain-like machines

McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Aleksander, Igor

Format:	E-Book
Sprache:	Englisch

Erschienen:	Cambridge, Mass: MIT Press ; 1989
Ausgabe:	1st MIT Press ed

Schlagwörter:	Computer architecture Neural computers

Anmerkung:	Bibliography: p. 381-393 Includes index
Umfang:	Online-Ressource (401 p) ; ill

Reproduktion:	Online-Ausg.

Links:	Link aufrufen IEEE Xplore Inhaltsverzeichnis
ISBN:	0-262-25559-6 0-262-01110-7 978-0-262-25559-2 978-0-262-01110-5

Katalog-ID:	816666776

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Indexfelder

matchkey_str	book:9780262255592:1989----
oclc_num	827012326
hierarchy_sort_str	1989
callnumber-subject-code	QA
publishDate	1989
allfields	0262255596 electronic bk. 0-262-25559-6 0262011107 0-262-01110-7 9780262255592 : electronic bk. 978-0-262-25559-2 9780262011105 978-0-262-01110-5 (DE-627)816666776 (DE-576)9816666774 (DE-599)GBV816666776 (OCoLC)827012326 (MITPRESS)6267209 (EBP)055117317 DE-627 ger DE-627 rakwb eng XD-US QA76.5 006.3 22 Neural computing architectures the design of brain-like machines edited by Igor Aleksander 1st MIT Press ed Cambridge, Mass MIT Press 1989 Online-Ressource (401 p) ill Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bibliography: p. 381-393 Includes index McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor. Online-Ausg. Computer architecture Neural computers Neural computers Computer architecture Aleksander, Igor oth 9780262511506 Print version Neural computing architectures (DLC)88038352 https://ieeexplore.ieee.org/book/6267209 X:MITPRESS Verlag IEEE Xplore lizenzpflichtig Volltext http://www.gbv.de/dms/bowker/toc/9780262011105.pdf V:DE-601 X:Bowker pdf/application 2015-03-18 Verlag Inhaltsverzeichnis Inhaltsverzeichnis ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 006.3 22 01 0018 3848469715 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 1521012172 olr-MIT i z 31-01-15 100 01 3100 4472463253 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011216038 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753668 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267209 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267209 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267209 100 01 3100 https://ieeexplore.ieee.org/book/6267209 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267209 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267209 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267209 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 23 01 0830 2015.01.31 370 01 4370 2021.12.01
spelling	0262255596 electronic bk. 0-262-25559-6 0262011107 0-262-01110-7 9780262255592 : electronic bk. 978-0-262-25559-2 9780262011105 978-0-262-01110-5 (DE-627)816666776 (DE-576)9816666774 (DE-599)GBV816666776 (OCoLC)827012326 (MITPRESS)6267209 (EBP)055117317 DE-627 ger DE-627 rakwb eng XD-US QA76.5 006.3 22 Neural computing architectures the design of brain-like machines edited by Igor Aleksander 1st MIT Press ed Cambridge, Mass MIT Press 1989 Online-Ressource (401 p) ill Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Bibliography: p. 381-393 Includes index McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor. Online-Ausg. Computer architecture Neural computers Neural computers Computer architecture Aleksander, Igor oth 9780262511506 Print version Neural computing architectures (DLC)88038352 https://ieeexplore.ieee.org/book/6267209 X:MITPRESS Verlag IEEE Xplore lizenzpflichtig Volltext http://www.gbv.de/dms/bowker/toc/9780262011105.pdf V:DE-601 X:Bowker pdf/application 2015-03-18 Verlag Inhaltsverzeichnis Inhaltsverzeichnis ZDB-37-IEM 2012 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2015 ISIL_DE-93 BO 045F 006.3 22 01 0018 3848469715 olrm-h228-MITIEEE zi22818 03-02-21 23 01 0830 1521012172 olr-MIT i z 31-01-15 100 01 3100 4472463253 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4011216038 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 01-12-21 2015 01 DE-93 3740753668 00 --%%-- --%%-- p --%%-- Campuslizenz l01 18-08-20 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/6267209 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/6267209 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/6267209 100 01 3100 https://ieeexplore.ieee.org/book/6267209 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/6267209 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/6267209 2015 01 DE-93 https://ieeexplore.ieee.org/book/6267209 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 23 01 0830 2015.01.31 370 01 4370 2021.12.01
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abstract	McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor. Bibliography: p. 381-393 Includes index
abstractGer	McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor. Bibliography: p. 381-393 Includes index
abstract_unstemmed	McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor. Bibliography: p. 381-393 Includes index
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title_short	Neural computing architectures
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fulltext	The Classical Perspective Why Neural Computing? A personal view … A theory of neural networks … Speech recognition based on topology-preserving neural maps … Neural map applications … Backpropagation in non-feedforward networks … A PDP learning approach to natural language understanding … Learning capabilities of Boolean networks … The Logical Perspective The logic of connectionist systems … A probabilistic logic neuron network for associative learning … Applications of N-tuple sampling and genetic algorithms to speech recognition … Dynamic Behavior of Boolean networks … Analysis and Interpretation Statistical mechanics and neural networks … Digital neural networks, matched filters and optical implementations … Hetero-associative networks using link-enabling vs. link-disabling local modification rules … Generation of movement trajectories in primates and robots … The PDP Perspective A review of parallel distributed processing … Bibliography … Index …
_version_	1805540683704958976
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