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Description
| - This paper presents a new approach in spatio-temporal data classification. Due to easy transformation of time dimension of spatio-temporal data into the phase of complex number, the presented approach uses complex numbers. The classification is based on a complex-valued neural network with multilayer topology. The paper proposes an extension of complexvalued backpropagation algorithm, which uses activation function applying nonlinearity on the amplitude only (preserving the phase). In order to transform the input data into complex numbers, a new coding technique is presented. Output coding is developed allowing the classification from complex numbers. It is solved with introduction of one-of-N coding extension into complex numbers, which is used as network's output coding. This approach is verified in application of hand-written character recognition, using the data collected during the writing process. The simulation results of this application are presented in the paper.
- This paper presents a new approach in spatio-temporal data classification. Due to easy transformation of time dimension of spatio-temporal data into the phase of complex number, the presented approach uses complex numbers. The classification is based on a complex-valued neural network with multilayer topology. The paper proposes an extension of complexvalued backpropagation algorithm, which uses activation function applying nonlinearity on the amplitude only (preserving the phase). In order to transform the input data into complex numbers, a new coding technique is presented. Output coding is developed allowing the classification from complex numbers. It is solved with introduction of one-of-N coding extension into complex numbers, which is used as network's output coding. This approach is verified in application of hand-written character recognition, using the data collected during the writing process. The simulation results of this application are presented in the paper. (en)
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Title
| - Classification of Spatio-Temporal Data
- Classification of Spatio-Temporal Data (en)
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skos:prefLabel
| - Classification of Spatio-Temporal Data
- Classification of Spatio-Temporal Data (en)
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skos:notation
| - RIV/68407700:21240/10:00171587!RIV11-MSM-21240___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/68407700:21240/10:00171587
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - complex-valued; neural network; spatio-temporal; backpropagation (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - Proceedings of the 7th EUROSIM Congress on Modelling and Simulation, Vol. 2: Full Papers
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Skrbek, Miroslav
- Zahradník, Jakub
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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http://linked.open...n/vavai/riv/zamer
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Department of Computer Science and Engineering, FEE, CTU in Prague
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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is http://linked.open...avai/riv/vysledek
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