Neural PCA and maximum likelihood hebbian learning on the GPU

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F12%3A86084952" target="_blank" >RIV/61989100:27740/12:86084952 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-642-33266-1_17" target="_blank" >http://dx.doi.org/10.1007/978-3-642-33266-1_17</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-33266-1_17" target="_blank" >10.1007/978-3-642-33266-1_17</a>

Result language

angličtina

Original language name

Neural PCA and maximum likelihood hebbian learning on the GPU

Original language description

This study introduces a novel fine-grained parallel implementation of a neural principal component analysis (neural PCA) variant and the maximum Likelihood Hebbian Learning (MLHL) network designed for modern many-core graphics processing units (GPUs). The parallel implementation as well as the computational experiments conducted in order to evaluate the speedup achieved by the GPU are presented and discussed. The evaluation was done on a well-known artificial data set, the 2D bars data set.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2012

Confidentiality

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

Article name in the collection

Lecture Notes in Computer Science. Volume 7553

ISBN

978-3-642-33265-4

ISSN

0302-9743

e-ISSN

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Number of pages

8

Pages from-to

132-139

Publisher name

Springer

Place of publication

Berlin

Event location

Lausanne

Event date

Sep 11, 2012

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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