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Proceedings Paper

Optimal design of 2D digital filters based on neural networks
Author(s): Xiao-hua Wang; Yi-gang He; Zhe-zhao Zheng; Xu-hong Zhang
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Paper Abstract

Two-dimensional (2-D) digital filters are widely useful in image processing and other 2-D digital signal processing fields,but designing 2-D filters is much more difficult than designing one-dimensional (1-D) ones.In this paper, a new design approach for designing linear-phase 2-D digital filters is described,which is based on a new neural networks algorithm (NNA).By using the symmetry of the given 2-D magnitude specification,a compact express for the magnitude response of a linear-phase 2-D finite impulse response (FIR) filter is derived.Consequently,the optimal problem of designing linear-phase 2-D FIR digital filters is turned to approximate the desired 2-D magnitude response by using the compact express.To solve the problem,a new NNA is presented based on minimizing the mean-squared error,and the convergence theorem is presented and proved to ensure the designed 2-D filter stable.Three design examples are also given to illustrate the effectiveness of the NNA-based design approach.

Paper Details

Date Published: 8 February 2005
PDF: 8 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.567813
Show Author Affiliations
Xiao-hua Wang, Changsha Univ. of Science and Technology (China)
Yi-gang He, Hunan Univ. (China)
Zhe-zhao Zheng, Changsha Univ. of Science and Technology (China)
Xu-hong Zhang, Institute of Electrical Engineering, CAS (China)


Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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