Neurální sítě

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F08%3A00310912" target="_blank" >RIV/67985556:_____/08:00310912 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Neural networks

Popis výsledku v původním jazyce

The method of selective coloring of neurons discovered in 1875 enabled the structure of neural tissue to be shown as a complex network of specific cells?neurons. Neurons occur in a wide variety of shapes and sizes, have a large number of inputs (synapses) at their receptive zones (dendrites), and a single output line (axon) branched into multiple synaptic endings. The microelectrode was the starting point of ideas that led to the binary threshold model of a neuron?s electrical activity. In 1949 a physiological rule was proposed for synaptic plasticity as a basic adaptive principle of neural assemblies. However, despite the extensive and detailed knowledge accumulated in the last century, the learning principles of biological neural assemblies still continue to be a strong motivation for the further search for suitable neural network models.

Název v anglickém jazyce

Neural networks

Popis výsledku anglicky

The method of selective coloring of neurons discovered in 1875 enabled the structure of neural tissue to be shown as a complex network of specific cells?neurons. Neurons occur in a wide variety of shapes and sizes, have a large number of inputs (synapses) at their receptive zones (dendrites), and a single output line (axon) branched into multiple synaptic endings. The microelectrode was the starting point of ideas that led to the binary threshold model of a neuron?s electrical activity. In 1949 a physiological rule was proposed for synaptic plasticity as a basic adaptive principle of neural assemblies. However, despite the extensive and detailed knowledge accumulated in the last century, the learning principles of biological neural assemblies still continue to be a strong motivation for the further search for suitable neural network models.

Druh

C - Kapitola v odborné knize

CEP obor

BD - Teorie informace

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F07%2F1594" target="_blank" >GA102/07/1594: Rekurentní pravděpodobnostní neuronové sítě</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2008

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Systems Science and Cybernetics

ISBN

978-1-84826-654-4

Počet stran výsledku

22

Strana od-do

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Počet stran knihy

250

Název nakladatele

Eolss Publishers-UNESCO

Místo vydání

Oxford

Kód UT WoS kapitoly

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