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Proceedings Paper

Phase unwrapping by a random artificial neural network
Author(s): Zhengdong Wang; Dapeng Yan; Feng Liu; Anzhi He
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Paper Abstract

There are may phase unwrapping algorithms have been developed in the recent years. Some of them work well in no or less noisy situations. But when encountering noisy data which is the most occurring situation these algorithms may exhibit insufficiency and diversity and usually cause the result unusable. Artificial neural networks have some features in tackling these problems. Especially random artificial neural network is more powerful and robust in solving combinatorial optimization problems. A random artificial neural network model has been used in demodulation of 'wrapped phase' in one and two dimensions of noisy interference pattern.

Paper Details

Date Published: 21 November 1997
PDF: 4 pages
Proc. SPIE 3172, Optical Technology in Fluid, Thermal, and Combustion Flow III, (21 November 1997); doi: 10.1117/12.279744
Show Author Affiliations
Zhengdong Wang, Nanjing Univ. of Science and Technology (China)
Dapeng Yan, Nanjing Univ. of Science and Technology (China)
Feng Liu, Nanjing Univ. of Science and Technology (China)
Anzhi He, Nanjing Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 3172:
Optical Technology in Fluid, Thermal, and Combustion Flow III
Soyoung Stephen Cha; James D. Trolinger; Masaaki Kawahashi, Editor(s)

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