DocumentCode
1564853
Title
CNN Template Design Method Based on GQA
Author
Meng, Hongling ; Zhao, Jianye
Author_Institution
Dept. of Electron., Peking Univ., Beijing
Volume
2
fYear
2005
Firstpage
941
Lastpage
944
Abstract
In this paper, a new quantum algorithm for cellular neural network (CNN) template design is proposed. The similarities between CNN and Gibbs image model (GIM) are described, so image processing could be regarded as an optimization question, and quantum computing is utilized for seeking global minimum. This approach is valid to many questions that could be processed with GIM, such as restoration. Simulations of an example (image restoration) are shown in order to validate effectiveness of new approach
Keywords
cellular neural nets; genetic algorithms; image restoration; quantum computing; quantum theory; Gibbs image model; cellular neural network; genetic quantum algorithm; image processing; image restoration; quantum computing; template design; Algorithm design and analysis; Cellular networks; Cellular neural networks; Computational modeling; Design methodology; Image processing; Image restoration; Neural networks; Quantum computing; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614774
Filename
1614774
Link To Document