Matches in SemOpenAlex for { <https://semopenalex.org/work/W2913507916> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W2913507916 abstract "This paper presents a Nonlinear Auto-Regressive (NAR) model design for the generation and prediction of Lorenz chaotic system using different Artificial Neural Network (ANN) architectures. Electroencephalogram (EEG) signals captured from brain activities demonstrate chaotic features. In order to theoretically understand brain functionalities, the dynamic chaotic time series outputs of a chaotic system with known system equations can be used to train ANN. And the ANN based NAR model can be used for the simulation and analysis of the chaotic features of brain activities. The ANN architecture design and optimization of the NAR chaotic system model is part of the preliminary research of a multidisciplinary brain research program. The ANN training results of different ANN architectures with 3 to 16 neurons in the hidden layer and 1 to 4 input delays of the NAR model, using training data generated with different step sizes provide important information for the selection of optimal training configuration to optimize the training performance. The research outcome is beneficial for the study of brain activities using EEG." @default.
- W2913507916 created "2019-02-21" @default.
- W2913507916 creator A5056676522 @default.
- W2913507916 date "2018-08-01" @default.
- W2913507916 modified "2023-09-26" @default.
- W2913507916 title "Time Series Generation Using Nonlinear Autoregressive Model Artificial Neural Network Based Nonlinear Autoregressive Model Design for the Generation and Prediction of Lorenz Chaotic System" @default.
- W2913507916 cites W1987387046 @default.
- W2913507916 cites W2131242650 @default.
- W2913507916 cites W2148138104 @default.
- W2913507916 cites W2155482699 @default.
- W2913507916 cites W2645542328 @default.
- W2913507916 cites W2736748092 @default.
- W2913507916 cites W2786300701 @default.
- W2913507916 doi "https://doi.org/10.1109/mwscas.2018.8623992" @default.
- W2913507916 hasPublicationYear "2018" @default.
- W2913507916 type Work @default.
- W2913507916 sameAs 2913507916 @default.
- W2913507916 citedByCount "1" @default.
- W2913507916 countsByYear W29135079162018 @default.
- W2913507916 crossrefType "proceedings-article" @default.
- W2913507916 hasAuthorship W2913507916A5056676522 @default.
- W2913507916 hasConcept C119857082 @default.
- W2913507916 hasConcept C121332964 @default.
- W2913507916 hasConcept C149782125 @default.
- W2913507916 hasConcept C151406439 @default.
- W2913507916 hasConcept C151510863 @default.
- W2913507916 hasConcept C154945302 @default.
- W2913507916 hasConcept C158622935 @default.
- W2913507916 hasConcept C159877910 @default.
- W2913507916 hasConcept C2775924081 @default.
- W2913507916 hasConcept C2777052490 @default.
- W2913507916 hasConcept C33923547 @default.
- W2913507916 hasConcept C41008148 @default.
- W2913507916 hasConcept C42536954 @default.
- W2913507916 hasConcept C47446073 @default.
- W2913507916 hasConcept C50644808 @default.
- W2913507916 hasConcept C62520636 @default.
- W2913507916 hasConceptScore W2913507916C119857082 @default.
- W2913507916 hasConceptScore W2913507916C121332964 @default.
- W2913507916 hasConceptScore W2913507916C149782125 @default.
- W2913507916 hasConceptScore W2913507916C151406439 @default.
- W2913507916 hasConceptScore W2913507916C151510863 @default.
- W2913507916 hasConceptScore W2913507916C154945302 @default.
- W2913507916 hasConceptScore W2913507916C158622935 @default.
- W2913507916 hasConceptScore W2913507916C159877910 @default.
- W2913507916 hasConceptScore W2913507916C2775924081 @default.
- W2913507916 hasConceptScore W2913507916C2777052490 @default.
- W2913507916 hasConceptScore W2913507916C33923547 @default.
- W2913507916 hasConceptScore W2913507916C41008148 @default.
- W2913507916 hasConceptScore W2913507916C42536954 @default.
- W2913507916 hasConceptScore W2913507916C47446073 @default.
- W2913507916 hasConceptScore W2913507916C50644808 @default.
- W2913507916 hasConceptScore W2913507916C62520636 @default.
- W2913507916 hasLocation W29135079161 @default.
- W2913507916 hasOpenAccess W2913507916 @default.
- W2913507916 hasPrimaryLocation W29135079161 @default.
- W2913507916 hasRelatedWork W1643663407 @default.
- W2913507916 hasRelatedWork W2044331189 @default.
- W2913507916 hasRelatedWork W2101113449 @default.
- W2913507916 hasRelatedWork W2102039114 @default.
- W2913507916 hasRelatedWork W2150746837 @default.
- W2913507916 hasRelatedWork W2336868063 @default.
- W2913507916 hasRelatedWork W2902707689 @default.
- W2913507916 hasRelatedWork W2913507916 @default.
- W2913507916 hasRelatedWork W883676525 @default.
- W2913507916 hasRelatedWork W2181589441 @default.
- W2913507916 isParatext "false" @default.
- W2913507916 isRetracted "false" @default.
- W2913507916 magId "2913507916" @default.
- W2913507916 workType "article" @default.