DocumentCode :
1949840
Title :
An Improved Fuzzy Neuron Network Scheme Using the Modified Genetic Algorithm and Structure
Author :
Zhou, Lixiang ; Shen, Minfen ; Cai, Binghuang
Author_Institution :
Coll. of Eng., Shantou Univ., Guangdong
Volume :
4
fYear :
2006
fDate :
16-20 2006
Abstract :
In the process of image filtering, it is a difficult problem to get rid of the distorted points and to keep the detail of the image at same time. So we use the fuzzy neuron network (FNN) to fuse the result of filter of the multilevel FIR-median hybrid (MFMHF) and the result of the median filter with a 5*5 window. It is not easy to set the appropriate parameters for the FNN. Thus, an improved FNN based on genetic algorithm (GA) is introduced to solve the problems of setting parameters of the FNN. Simulation results indicate that after the parameters of the FNN being optimized with GA, the performance of the FNN on image fusion is better than the performance of the common FNN
Keywords :
FIR filters; fuzzy neural nets; genetic algorithms; image fusion; median filters; fuzzy neuron network scheme; genetic algorithm; image filtering; image fusion; modified genetic algorithm; multilevel FIR-median hybrid filter; Backpropagation; Educational institutions; Filters; Fuses; Fuzzy neural networks; Genetic algorithms; Genetic engineering; Image fusion; Neurons; Nonlinear systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
Type :
conf
DOI :
10.1109/ICOSP.2006.346135
Filename :
4129827
Link To Document :
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