1. Identity statement | |
Reference Type | Book Section |
Site | mtc-m16b.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 6qtX3pFwXQZGivnJUY/NdvGS |
Repository | sid.inpe.br/mtc-m15@80/2006/11.20.12.21 (restricted access) |
Last Update | 2006:11.20.12.21.58 (UTC) simone |
Metadata Repository | sid.inpe.br/mtc-m15@80/2006/11.20.12.21.59 |
Metadata Last Update | 2023:12.29.11.50.53 (UTC) simone |
Secondary Key | INPE-14503-PRE/9534 |
Citation Key | WeigangSzuMarSáCFo:1997:PeCoAm |
Title | Peformance comparison among Non-paramatric probability density estimator, radial basis function and adaptive wavelet transform neural networks |
Year | 1997 |
Access Date | 2024, May 02 |
Secondary Type | PRE LI |
Number of Files | 1 |
Size | 904 KiB |
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2. Context | |
Author | 1 Weigang, Li 2 Szu, Harold H. 3 Marar, João F. 4 Sá, Leonardo Deane Abreu 5 C. Filho, Edson C. B. |
Group | 1 2 3 4 DMA-INPE-MCT-BR |
Affiliation | 1 Department of Meteorological Science 2 Center for Advanced Computer Studies, University of Southwestern Louisiana 3 Department of Computer Science, Universidade Estadual Paulista 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Department of Computer Science, Universidade Federal de Pernambuco |
Author e-Mail Address | 1 wei@met.inpe.br 2 hszu@nswc.navy.mil 3 jfm@di.ufpe.br 4 leo@cptec.inpe.br 5 ecdbcf@di.ufpe.br |
Editor | Szu, H. H. |
e-Mail Address | atus@cptec.inpe.br |
Book Title | The World's knowledge |
Publisher | SPIE- The International Society for Optical Engineering |
Volume | 3078 |
Pages | 128-138 |
History (UTC) | 2007-01-08 15:44:58 :: estagiario -> administrator :: 2008-06-10 21:32:52 :: administrator -> estagiario :: 2010-05-11 16:56:45 :: estagiario -> administrator :: 2023-12-29 11:49:29 :: administrator -> simone :: 1997 2023-12-29 11:50:53 :: simone -> estagiario :: 1997 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Version Type | publisher |
Keywords | artificial neural network adaptive wavelet transform density estimation Paraguay River wavelet shrinkage |
Abstract | Wavelet Shrinkage, Radial Basis Function (RBF) Networks and Adaptive Wavelet Transform Neural Networks (AWTNN) have been studied for signal reconstructions. We first use these methods to approximate four specific functions which represent various spatially nonhomogeneous phenomena. Next, we apply these methods to analyse a time series of Paraguay River levels. From the preliminary experiments, we show that Wavelet Shrinkage was the best estimator. With similar results, secondly came AWTNN and lastly came RBF networks. |
Area | MET |
Arrangement | urlib.net > BDMCI > Fonds > Produção até 2016 > DMA > Peformance comparison among... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
Language | en |
Target File | Li.Performance.pdf |
User Group | administrator estagiario |
Visibility | shown |
Copy Holder | SID/SCD |
Read Permission | deny from all and allow from çã |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/46JKC45 |
Dissemination | NTRSNASA; BNDEPOSITOLEGAL. |
Host Collection | cptec.inpe.br/walmeida/2003/04.25.17.12 |
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6. Notes | |
Empty Fields | archivingpolicy archivist callnumber city copyright creatorhistory descriptionlevel documentstage doi edition format isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor seriestitle session shorttitle sponsor subject tertiarymark tertiarytype translator url |
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7. Description control | |
e-Mail (login) | estagiario |
update | |
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