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Average sampling theorems for shift invariant subspaces

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【作者】 孙文昌； 周性伟；

【Author】 SUN Wenchang & ZHOU XingweiNankal Institute of Mathematics, Nankai University, Tianjin 300071, China Correspondence should be addressed to Sun Wenchang

【机构】 Nankal Institute of Mathematics； Nankai University； Tianjin 300071； China； China；

【摘要】 <正> The sampling theorem is one of the most powerful results in signal analysis. In this paper, we study the average sampling on shift invariant subspaces, e.g. wavelet subspaces. We show that if a subspace satisfies certain conditions, then every function in the subspace is uniquely determined and can be reconstructed by its local averages near certain sampling points. Examples are given.

【Abstract】 The sampling theorem is one of the most powerful results in signal analysis. In this paper, we study the average sampling on shift invariant subspaces, e.g. wavelet subspaces. We show that if a subspace satisfies certain conditions, then every function in the subspace is uniquely determined and can be reconstructed by its local averages near certain sampling points. Examples are given.

【关键词】 sampling theorem； average sampling； shift invariant subspaces； wavelet subspaces.；
【Key words】 sampling theorem； average sampling； shift invariant subspaces； wavelet subspaces.；
  • 【文献出处】 Science in China(Series E:Technological Sciences) ,中国科学(E辑:技术科学)(英文版) , 编辑部邮箱 ,2000年05期
  • 【分类号】O242
  • 【被引频次】6
  • 【下载频次】54
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