Please use this identifier to cite or link to this item: doi:10.22028/D291-26466
Title: Complexity issues in discrete neurocomputing
Author(s): Wiedermann, Juraj
Language: English
Year of Publication: 1990
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: An overview of the basic results in complexity theory of discrete neural computations is presented. Especially, the computational power and efficiency of single neurons, neural circuits, symmetric neural networks (Hopfield model), and of Boltzmann machines is investigated and characterized. Corresponding intractability results are mentioned as well. The evidence is presented why discrete neural networks (inclusively Boltzmann machines) are not to be expected to solve intractable problems more efficiently than other conventional models of computing.
Link to this record: urn:nbn:de:bsz:291-scidok-51627
Series name: Technischer Bericht / A / Fachbereich Informatik, Universität des Saarlandes
Series volume: 1990/10
Date of registration: 4-Apr-2013
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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