EconPapers    
Economics at your fingertips  
 

Complex functional networks

Chunguang Li, Xiaofeng Liao, Zhongfu Wu and Juebang Yu

Mathematics and Computers in Simulation (MATCOM), 2001, vol. 57, issue 6, 355-365

Abstract: Functional networks are a recently introduced extension of neural networks, which deal with general functional models instead of sigmoidal-like ones. In this paper, we propose complex functional networks, whose inputs, outputs, neural functions and arguments are all complex-valued. The general learning algorithm for this kind of complex functional networks is derived. And the performance of the proposed complex functional networks is demonstrated with application in the identification of complex-valued communication channels.

Keywords: Communication channel; Functional networks; Real time recurrent learning (search for similar items in EconPapers)
Date: 2001
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475401002968
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:57:y:2001:i:6:p:355-365

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:matcom:v:57:y:2001:i:6:p:355-365