Exponential Sampling: A Gibbs Phenomena Removal Model for Finite Rate of Innovation Sampling Framework

摘要：

We propose an exponential approximating function as a sampling kernel with finite rate of innovation. The performance of reconstruct non-bandlimited signals from its low frequency components would inevitably induce Gibbs phenomenon. This paper establishes the theoretical model on relationship between sampling kernel filter and parametric reconstruction method of non-bandlimited signals, and designs a new window function exponential sampling kernel filter to removal Gibbs Influence. Simulation results show that, compared to Sine sampling kernel filter, the reconstruction ability of exponential filter based finite rate sampling system is improved under the white Gaussian noise environment.

关键词： Sampling theory finite innovation rate Gibbs phenomenon sampling kernel filter Dirac streams.

作者: QianHui YuLun

作者单位: College of Physics and Information Engineering, Fuzhou University, FuZhou, China

会议类型: 国际会议

会议名称: 2011 3nd International Conference on Mechanical and Electronics Engineering(2011年第三届机械与电子工程国际会议 ICMEE2011)

会议地点: 合肥

会议语种:英文

页码: 470-474

在线出版日期: 2011-09-23（万方平台首次上网日期，不代表论文的发表时间）