Quick Search:

uzh logo
Browse by:

Zurich Open Repository and Archive

Maintenance: Tuesday, 5.7.2016, 07:00-08:00

Maintenance work on ZORA and JDB on Tuesday, 5th July, 07h00-08h00. During this time there will be a brief unavailability for about 1 hour. Please be patient.

Uwate, Y; Nishio, Y; Stoop, R (2009). Durability of affordable neural networks against damaging neurons. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E92.A(2):585-593.

Full text not available from this repository.

View at publisher


Durability describes the ability of a device to operate properly in imperfect conditions. We have recently proposed a novel neural network structure called an “Affordable Neural Network” (AfNN), in which affordable neurons of the hidden layer are considered as the elements responsible for the robustness property as is observed in human brain function. Whereas earlier we have shown that AfNNs can still generalize and learn, here we show that these networks are robust against damages occurring after the learning process has terminated. The results support the view that AfNNs embody the important feature of durability. In our contribution, we investigate the durability of the AfNN when some of the neurons in the hidden layer are damaged after the learning process.


2 citations in Web of Science®
2 citations in Scopus®
Google Scholar™


Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Date:February 2009
Deposited On:08 Mar 2010 18:40
Last Modified:05 Apr 2016 14:00
Publisher:Denshi Jouhou Tsuushin Gakkai
Publisher DOI:10.1587/transfun.E92.A.585
Related URLs:http://www.ini.uzh.ch/node/19263 (Organisation)

Users (please log in): suggest update or correction for this item

Repository Staff Only: item control page