Fixed-Order optimal deconvolution filter with irregular missing data

uTaipei > College of Science > Department of Computer Science > Periodical Articles > Item 987654321/15782

Please use this identifier to cite or link to this item: http://utaipeir.lib.utaipei.edu.tw/dspace/handle/987654321/15782

Title:	Fixed-Order optimal deconvolution filter with irregular missing data
Authors:	Hung, Jui-Chung;洪瑞鍾
Contributors:	臺北市立教育大學資訊科學系
Keywords:	deconvolution filter;genetic algorithm;irregular missing data
Date:	2010-06-16
Issue Date:	2017-07-24 11:28:06 (UTC+8)
Abstract:	In general, the reconstruction performance of the conventional deconvolution filter is deteriorated by the missing data. In this paper, a fixed-order deconvolution filter design method is proposed for the signal reconstruction from received signal with irregular missing data. The missing data model is based on a probabilistic structure. The probability of occurrence of missing data is unknown a prior. In this situation, the deconvolution filter design problem becomes a complicated nonlinear estimation problem. In this study, a design method based on genetic algorithms is proposed to treat the signal reconstruction design problem with irregular missing data. Finally, two examples are given to illustrate the simulation results of the proposed deconvolution filter. The results show that the reconstruction performance is improved significantly if the missing probability is considered in the deconvolution filter design procedure
Relation:	International Journal of Adaptive Control and Signal Processing，p311-321
Appears in Collections:	[Department of Computer Science] Periodical Articles

Files in This Item:

There are no files associated with this item.