Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 19, NO. 5, MAY 2008 883 Blur Identification by Multilayer Neural Network
 

Summary: IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 19, NO. 5, MAY 2008 883
Blur Identification by Multilayer Neural Network
Based on Multivalued Neurons
Igor Aizenberg, Senior Member, IEEE, Dmitriy V. Paliy, Jacek M. Zurada, Fellow, IEEE, and
Jaakko T. Astola, Fellow, IEEE
Abstract--A multilayer neural network based on multivalued
neurons (MLMVN) is a neural network with a traditional feedfor-
ward architecture. At the same time, this network has a number of
specific different features. Its backpropagation learning algorithm
is derivative-free. The functionality of MLMVN is superior to that
of the traditional feedforward neural networks and of a variety
kernel-based networks. Its higher flexibility and faster adaptation
to the target mapping enables to model complex problems using
simpler networks. In this paper, the MLMVN is used to identify
both type and parameters of the point spread function, whose pre-
cise identification is of crucial importance for the image deblur-
ring. The simulation results show the high efficiency of the pro-
posed approach. It is confirmed that the MLMVN is a powerful
tool for solving classification problems, especially multiclass ones.
Index Terms--Blind deconvolution, complex-valued neuron,

  

Source: Aizenberg, Igor - College of Science, Technology, Engineering, and Mathematics, Texas A&M University at Texarkana

 

Collections: Computer Technologies and Information Sciences