A New Method of Parameters Determined in PCNN

Shui Ming He; Dian Hong Wang

doi:10.4028/www.scientific.net/AMM.548-549.1059

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 548-549A New Method of Parameters Determined in PCNN

A New Method of Parameters Determined in PCNN

Abstract:

The aim of this paper is to research the image recognition system and its applications, which is based on combining the traditional BP neural networks and the third-generation pulse coupled neural network (PCNN).The process is by extracting the image's time and entropy sequences, then through the fast Fourier transform, and finally as inputs of the pattern classification. In order to test the stability of the system, we make some varies by rotating, tension and compressing the original image, meanwhile, combined with the statistics of the entropy information to determine the time delay parameter of the pcnn, the recognition results is satisfactory.

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Periodical:

Applied Mechanics and Materials (Volumes 548-549)

Pages:

1059-1063

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.548-549.1059

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Online since:

April 2014

Authors:

Shui Ming He*, Dian Hong Wang

Keywords:

BP, Euler Sequence, FFT, Neural Network (NN), PCNN

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* - Corresponding Author

References

[1] Yanbin Ning, Shuiming He. Application Of BP Network in Evaluation Of Groundwater Quality[C]DCABES 2009 Proceeding, (2009).

Google Scholar

[2] Raul C. Muresan. Pattern recognition using pulse-coupled neural networks and discrete Fourier transforms. Neurocomputing 51 (2003) 487-493.

DOI: 10.1016/s0925-2312(02)00727-0

Google Scholar

[3] Shuiming He, Dianhong Wang, Yanbin Ning. Application of Pulse coupled neural network in image recognition[C]1 1 1 1 International Conference on Computing, control and Industrial Engineering, (2010).

DOI: 10.1109/ccie.2010.223

Google Scholar

[4] Zhijiang Zhao. A new method of PCNN's parameter's optimization[J]. ACTA Electronic SINICA, May, (2007).

Google Scholar