Spatio-Temporal Data Classification using CVNNs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F13%3A00203405" target="_blank" >RIV/68407700:21240/13:00203405 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S1569190X12001347" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1569190X12001347</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.simpat.2012.10.001" target="_blank" >10.1016/j.simpat.2012.10.001</a>
Alternative languages
Result language
angličtina
Original language name
Spatio-Temporal Data Classification using CVNNs
Original language description
This paper presents two new approaches of spatio-temporal data classification using complex-valued neural networks. First approach uses extended complex-valued backpropagation algorithm to train MLP network, whose output?s amplitudes are encoded in one-of-N coding. It makes a classification decision based on accumulated distance between network output and trained pattern. The second approach is inspired in RBF networks with two layer architecture. Neurons from the first layer have fixed position in space and time encoded into theirs weights. This layer is trained by presented extension of neural gas algorithm into complex numbers. The second layer affects which neurons from the first layer belong to specific class. Paper contains details on experimenting with proposed approaches on artificial data of hand-written character recognition and comparison of both methods.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Simulation Modelling Practice and Theory
ISSN
1569-190X
e-ISSN
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Volume of the periodical
33
Issue of the periodical within the volume
33
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
8
Pages from-to
81-88
UT code for WoS article
000317253700007
EID of the result in the Scopus database
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