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dc.contributor.authorSima, Jiri
dc.date.accessioned2019-06-26T10:18:09Z
dc.date.available2019-06-26T10:18:09Z
dc.date.issued2017-06-01cs
dc.identifier.citationMendel. 2017 vol. 23, č. 1, s. 103-110. ISSN 1803-3814cs
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/179205
dc.description.abstractWe briefly survey the basic concepts and results concerning the computational power of neural net-orks which basically depends on the information content of eight parameters. In particular, recurrent neural networks with integer, rational, and arbitrary real weights are classi ed within the Chomsky and finer complexity hierarchies. Then we re ne the analysis between integer and rational weights by investigating an intermediate model of integer-weight neural networks with an extra analog rational-weight neuron (1ANN). We show a representation theorem which characterizes the classification problems solvable by 1ANNs, by using so-called cut languages. Our analysis reveals an interesting link to an active research field on non-standard positional numeral systems with non-integer bases. Within this framework, we introduce a new concept of quasi-periodic numbers which is used to classify the computational power of 1ANNs within the Chomsky hierarchy.en
dc.formattextcs
dc.format.extent103-110cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/59cs
dc.subjectneural networken
dc.subjectChomsky hierarchyen
dc.subjectβ-expansionen
dc.subjectcut languageen
dc.titleThe Computational Power of Neural Networks and Representations of Numbers in Non-Integer Basesen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
dc.coverage.issue1cs
dc.coverage.volume23cs
dc.identifier.doi10.13164/mendel.2017.1.103en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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