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Description
  • Tento článek prezentuje novou metodu pro generování Markovova řetězce neuronovou sítí. Neuronová síť byla pojmenována Temporal Information Categorizing and Learning Map. Jedná se o zdokonalenou variantu sítě Categorizing and Learning Module (CALM). Vylepšení zahrnuje záměnu skalárního součinu Euklidovou metrikou. Konstrukce Markovova řetězce je umožněna náhradou vnitřních synapsí s pevnými váhami synapsemi s asociativním učením. Výsledky sítě pracující s jednoduchými umělými daty vykazují slibné výsledky. Dále je představena technika pro vizualizaci Markovových řetězců. (cs)
  • In this paper we introduce technique how a neural network can generate a Hidden Markov Chain. We use neural network called Temporal Information Categorizing and Learning Map. The network is an enhanced version of standard Categorizing and Learning Module (CALM). Our modifications include Euclidean metrics instead of weighted sum formerly used for categorization of the input space. Construction of the Hidden Markov Chain is provided by turning steady weight internal synapses to associative learning synapses. Result obtained from testing on simple artificial data promises applicability in a real problem domain. We present a visualization technique of the obtained Hidden Markov Chain and the method how the results can be validated. Experiments are being performed.
  • In this paper we introduce technique how a neural network can generate a Hidden Markov Chain. We use neural network called Temporal Information Categorizing and Learning Map. The network is an enhanced version of standard Categorizing and Learning Module (CALM). Our modifications include Euclidean metrics instead of weighted sum formerly used for categorization of the input space. Construction of the Hidden Markov Chain is provided by turning steady weight internal synapses to associative learning synapses. Result obtained from testing on simple artificial data promises applicability in a real problem domain. We present a visualization technique of the obtained Hidden Markov Chain and the method how the results can be validated. Experiments are being performed. (en)
Title
  • Neural Network Generating Hidden Markov Chain
  • Neural Network Generating Hidden Markov Chain (en)
  • Neuronová síť generující Markovův řetězec (cs)
skos:prefLabel
  • Neural Network Generating Hidden Markov Chain
  • Neural Network Generating Hidden Markov Chain (en)
  • Neuronová síť generující Markovův řetězec (cs)
skos:notation
  • RIV/68407700:21230/05:03108598!RIV08-MSM-21230___
http://linked.open.../vavai/riv/strany
  • 518;521
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 532550
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/05:03108598
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Categorizing and Learning Module; Hidden Markov Model; neural network; signal processing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6980F20765E5]
http://linked.open...v/mistoKonaniAkce
  • Coimbra
http://linked.open...i/riv/mistoVydani
  • Wien
http://linked.open...i/riv/nazevZdroje
  • Adaptive and Natural Computing Algoritms - Proceedings of the International Conference in Coimbra
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Koutník, Jan
  • Šnorek, Miroslav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 3-211-24934-6
http://localhost/t...ganizacniJednotka
  • 21230
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