DocumentCode :
1937595
Title :
Queral Networks: Toward an Approach for Engineering Large Artificial Neural Networks
Author :
Hoffman, Travis A. ; Rozenblit, Jerzy W. ; Akoglu, Ali ; Suantak, Liana
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Arizona, Tucson, AZ, USA
fYear :
2011
fDate :
27-29 April 2011
Firstpage :
81
Lastpage :
88
Abstract :
A generalization of an artificial neuron is introduced in this paper. Called the queron, this abstraction is the basic computational node of Queral Networks (QN). QNs are introduced as a parallel architecture expected to be an improvement upon Artificial Neural Networks (ANN). The fundamental properties of QNs are presented here: reusability, complexity management and human-readability. It is expected that this proposed architecture will allow the engineering of large, highly parallel computer systems with the computational benefits of ANNs while overcoming the challenge of developing ANNs. A brief case study is given to illustrate the QN concept.
Keywords :
neural nets; parallel architectures; artificial neuron generalization; computational benefits; computational node; human readability; large artificial neural network engineering; parallel architecture; parallel computer systems; queral networks; Artificial neural networks; Complexity theory; Contracts; Libraries; Meteorology; Neurons; Runtime; Artificial Neural Networks; Automatic Programming; Computation Theory; Evolutionary Computation; Parallel Architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering of Computer Based Systems (ECBS), 2011 18th IEEE International Conference and Workshops on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4577-0065-1
Electronic_ISBN :
978-0-7695-4379-6
Type :
conf
DOI :
10.1109/ECBS.2011.27
Filename :
5934807
Link To Document :
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