Matches in SemOpenAlex for { <https://semopenalex.org/work/W2069778874> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W2069778874 endingPage "S756" @default.
- W2069778874 startingPage "S751" @default.
- W2069778874 abstract "Artificial Neural Networks (ANNs) can be used for grey-box or black-box modeling of continuous-time systems by placing them in a framework based on numerical integration techniques. When an implicit integration scheme is used as a template, it imposes a recurrent structure on the overall network. Here we present three algorithms suitable for the training of such “network-plus-integrator” assemblies and compare their relative computational efficiencies. Pineda's Recurrent Back-Propagation (RBP) training method is recast to exploit the structure of the assembly. The second approach is RBP modified to evaluate partial derivatives of network outputs with respect to parameters exactly, while the third is a Newton-Raphson based algorithm in which outputs of the network and partial derivatives are computed at each step instead of approximated. We compare the methods via an illustrative example and discuss aspects of training in a parallel computing environment." @default.
- W2069778874 created "2016-06-24" @default.
- W2069778874 creator A5062644187 @default.
- W2069778874 creator A5063855248 @default.
- W2069778874 creator A5069647922 @default.
- W2069778874 date "1996-01-01" @default.
- W2069778874 modified "2023-09-23" @default.
- W2069778874 title "A comparison of recurrent training algorithms for time series analysis and system identification" @default.
- W2069778874 cites W1966860445 @default.
- W2069778874 cites W1976068300 @default.
- W2069778874 cites W2007431958 @default.
- W2069778874 cites W2034183452 @default.
- W2069778874 cites W2155022747 @default.
- W2069778874 doi "https://doi.org/10.1016/0098-1354(96)00133-0" @default.
- W2069778874 hasPublicationYear "1996" @default.
- W2069778874 type Work @default.
- W2069778874 sameAs 2069778874 @default.
- W2069778874 citedByCount "21" @default.
- W2069778874 countsByYear W20697788742013 @default.
- W2069778874 countsByYear W20697788742015 @default.
- W2069778874 countsByYear W20697788742018 @default.
- W2069778874 countsByYear W20697788742019 @default.
- W2069778874 countsByYear W20697788742020 @default.
- W2069778874 countsByYear W20697788742021 @default.
- W2069778874 countsByYear W20697788742022 @default.
- W2069778874 countsByYear W20697788742023 @default.
- W2069778874 crossrefType "journal-article" @default.
- W2069778874 hasAuthorship W2069778874A5062644187 @default.
- W2069778874 hasAuthorship W2069778874A5063855248 @default.
- W2069778874 hasAuthorship W2069778874A5069647922 @default.
- W2069778874 hasConcept C11413529 @default.
- W2069778874 hasConcept C116834253 @default.
- W2069778874 hasConcept C134306372 @default.
- W2069778874 hasConcept C143724316 @default.
- W2069778874 hasConcept C147168706 @default.
- W2069778874 hasConcept C151730666 @default.
- W2069778874 hasConcept C154945302 @default.
- W2069778874 hasConcept C155032097 @default.
- W2069778874 hasConcept C165696696 @default.
- W2069778874 hasConcept C2776257435 @default.
- W2069778874 hasConcept C31258907 @default.
- W2069778874 hasConcept C33923547 @default.
- W2069778874 hasConcept C38652104 @default.
- W2069778874 hasConcept C41008148 @default.
- W2069778874 hasConcept C50644808 @default.
- W2069778874 hasConcept C59822182 @default.
- W2069778874 hasConcept C77618280 @default.
- W2069778874 hasConcept C79518650 @default.
- W2069778874 hasConcept C86803240 @default.
- W2069778874 hasConcept C94966114 @default.
- W2069778874 hasConceptScore W2069778874C11413529 @default.
- W2069778874 hasConceptScore W2069778874C116834253 @default.
- W2069778874 hasConceptScore W2069778874C134306372 @default.
- W2069778874 hasConceptScore W2069778874C143724316 @default.
- W2069778874 hasConceptScore W2069778874C147168706 @default.
- W2069778874 hasConceptScore W2069778874C151730666 @default.
- W2069778874 hasConceptScore W2069778874C154945302 @default.
- W2069778874 hasConceptScore W2069778874C155032097 @default.
- W2069778874 hasConceptScore W2069778874C165696696 @default.
- W2069778874 hasConceptScore W2069778874C2776257435 @default.
- W2069778874 hasConceptScore W2069778874C31258907 @default.
- W2069778874 hasConceptScore W2069778874C33923547 @default.
- W2069778874 hasConceptScore W2069778874C38652104 @default.
- W2069778874 hasConceptScore W2069778874C41008148 @default.
- W2069778874 hasConceptScore W2069778874C50644808 @default.
- W2069778874 hasConceptScore W2069778874C59822182 @default.
- W2069778874 hasConceptScore W2069778874C77618280 @default.
- W2069778874 hasConceptScore W2069778874C79518650 @default.
- W2069778874 hasConceptScore W2069778874C86803240 @default.
- W2069778874 hasConceptScore W2069778874C94966114 @default.
- W2069778874 hasLocation W20697788741 @default.
- W2069778874 hasOpenAccess W2069778874 @default.
- W2069778874 hasPrimaryLocation W20697788741 @default.
- W2069778874 hasRelatedWork W1596397513 @default.
- W2069778874 hasRelatedWork W1604061580 @default.
- W2069778874 hasRelatedWork W1814702984 @default.
- W2069778874 hasRelatedWork W2086999410 @default.
- W2069778874 hasRelatedWork W2092534630 @default.
- W2069778874 hasRelatedWork W2362189222 @default.
- W2069778874 hasRelatedWork W2391384657 @default.
- W2069778874 hasRelatedWork W2566625450 @default.
- W2069778874 hasRelatedWork W2182757990 @default.
- W2069778874 hasRelatedWork W2516580779 @default.
- W2069778874 hasVolume "20" @default.
- W2069778874 isParatext "false" @default.
- W2069778874 isRetracted "false" @default.
- W2069778874 magId "2069778874" @default.
- W2069778874 workType "article" @default.