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Accelerated Gradient Learning Algorithm for Neural Network Weights Update (CROSBI ID 541770)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Hocenski, Željko ; Antunović, Mladen ; Filko, Damir Accelerated Gradient Learning Algorithm for Neural Network Weights Update // Knowledge-Based Intelligent Information and Engineering Systems / Ignac Lovrek and Robert J. Howlett and Lakhmi C. Jain (ur.). Heidelberg: Springer, 2008. str. 49-56

Podaci o odgovornosti

Hocenski, Željko ; Antunović, Mladen ; Filko, Damir

engleski

Accelerated Gradient Learning Algorithm for Neural Network Weights Update

This work proposes decomposition of gradient learning algorithm for neural network weights update. Decomposition enables parallel execution convenient for implementation on computer grid. Improvements are reflected in accelerated learning rate which may be essential for time critical decision processes. Proposed solution is tested and verified on MLP neural network case study, varying a wide range of parameters, such as number of inputs/outputs, length of input/output data, number of neurons and layers. Experimental results show time savings in multiple thread execution.

time critical processes; algorithm decomposition; neural network; weights update; gradient learning method; parallel processing

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Podaci o prilogu

49-56.

2008.

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objavljeno

978-3-540-85562-0

Podaci o matičnoj publikaciji

Knowledge-Based Intelligent Information and Engineering Systems

Ignac Lovrek and Robert J. Howlett and Lakhmi C. Jain

Heidelberg: Springer

Podaci o skupu

Knowledge-Based Intelligent Information and Engineering Systems, KES 2008

predavanje

03.09.2008-05.09.2008

Zagreb, Hrvatska

Povezanost rada

Računarstvo, Elektrotehnika