Comparison between BP and RBF Neural Network Pattern Recognition Process Applied in the Droplet Analyzer

Qing Song; Gao Jie Meng; Lu Yang; Dan Qing Du; Xue Fei Mao

doi:10.4028/www.scientific.net/AMM.543-547.2333

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547Comparison between BP and RBF Neural Network...

Comparison between BP and RBF Neural Network Pattern Recognition Process Applied in the Droplet Analyzer

Abstract:

Among various pattern recognition methods used for liquid identification, the method based on neural network has the advantages of robustness and fault tolerance, which can study and adapt to the uncertain system. The waveform analysis is exploited for feature extraction of the liquid droplet fingerprint (LDF) in this paper, and the liquid identification is carried out by means of BP and RBF neural network. The experimental results proved that the recognition rate is excellent in both of these two methods. In condition that the training data is limited, RBF network is better than BP network in recognition speed and rate.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

2333-2336

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.2333

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Online since:

March 2014

Authors:

Qing Song*, Gao Jie Meng, Lu Yang, Dan Qing Du, Xue Fei Mao

Keywords:

BP Neural Network (BPNN), Liquid Droplet Fingerprint, Pattern Recognition, RBF Neural Network

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* - Corresponding Author

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