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001387534 020__ $$a0262255596$$q(electronic bk.)
001387534 020__ $$a9780262255592$$q(electronic bk.)
001387534 020__ $$z0262011107
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001387534 035__ $$a(OCoLC)827012326
001387534 035__ $$a(OCoLC-P)827012326
001387534 040__ $$aOCoLC-P$$beng$$epn$$cOCoLC-P
001387534 050_4 $$aQA76.5$$b.N426 1989eb
001387534 08204 $$a006.3$$222
001387534 24500 $$aNeural computing architectures :$$bthe design of brain-like machines /$$cedited by Igor Aleksander.
001387534 250__ $$a1st MIT Press ed.
001387534 260__ $$aCambridge, Mass. :$$bMIT Press,$$c1989.
001387534 300__ $$a1 online resource (401 pages) :$$billustrations
001387534 336__ $$atext$$btxt$$2rdacontent
001387534 337__ $$acomputer$$bc$$2rdamedia
001387534 338__ $$aonline resource$$bcr$$2rdacarrier
001387534 506__ $$aAccess limited to authorized users.
001387534 5203_ $$a"McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP.In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor."
001387534 588__ $$aOCLC-licensed vendor bibliographic record.
001387534 650_0 $$aNeural computers.
001387534 650_0 $$aComputer architecture.
001387534 653__ $$aCOMPUTER SCIENCE/Machine Learning & Neural Networks
001387534 655_0 $$aElectronic books
001387534 7001_ $$aAleksander, Igor.
001387534 852__ $$bebk
001387534 85640 $$3MIT Press$$uhttps://univsouthin.idm.oclc.org/login?url=https://doi.org/10.7551/mitpress/4926.001.0001?locatt=mode:legacy$$zOnline Access through The MIT Press Direct
001387534 85642 $$3OCLC metadata license agreement$$uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
001387534 909CO $$ooai:library.usi.edu:1387534$$pGLOBAL_SET
001387534 980__ $$aBIB
001387534 980__ $$aEBOOK
001387534 982__ $$aEbook
001387534 983__ $$aOnline