NDLI: Functional Network and Tunable Activation Function Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Yongquan Zhou Daozhu Lin Yindong Yang
Copyright Year	2006
Description	Author affiliation: Coll. of Comput. & Inf. Sci., Guangxi Univ. for Nationalities, Nanning (Yongquan Zhou)
Abstract	Functional network is a recently introduced extension of neural networks. Unlike neural networks, it deals with general functional models instead of sigmoid-like ones. And in these networks there are no weights associated with the links connecting neurons. In this paper, firstly, the architecture of functional network is deformed, compares the structure of networks and learning model algorithm, and approximates performance with tunable function neural network. It is pointed out that people study of with tunable function neural network is only special case, and functional network is more generally model. Numerical analyses results show that better convergence performance of functional network algorithm over tunable function neural network
Starting Page	2757
Ending Page	2762
File Size	239732
Page Count	6
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1712866
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Neurons Educational institutions Computer networks Information science Electronic mail Electrons Joining processes Computer architecture Deformable models learning algorithm Functional neuron TAF neuron functional network neural network
Content Type	Text
Resource Type	Article

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