What Can We See behind Sampling Theorems?

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概要

• 論文の詳細を見る

• This paper shows that there is a fruitful world behind sampling theorems. For this purpose, the sampling problem is reformulated from a functional analytic standpoint, and is consequently revealed that the sampling problem is a kind of inverse problem. The sampling problem covers, for example, signal and image restoration including super resolution, image reconstruction from projections such as CT scanners in hospitals, and supervised learning such as learning in artificial neural networks. An optimal reconstruction operator is also given, providing the best approximation to an individual original signal without our knowing the original signal.

• （社）電子情報通信学会の論文
• 2009-03-01

著者

• Ogawa Hidemitsu

  Tokyo University And Graduate School Of Social Welfare

関連論文

• What Can We See behind Sampling Theorems?

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