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In our previous discussion, we saw that imposing bandlimited-ness on our class of signals permits point-wise sampling of our signal and then later perfect reconstruction. It turns out that by imposing sparsity we can also obtain perfect reconstruction irrespective of whether or not we have satsified the sampling rate limits imposed by Shannon's sampling theorem. This has extremely important in pra
Microsoft PowerPoint - ランダムプãƒã‚¸ã‚§ã‚¯ã‚·ãƒ§ãƒ³ã¨ã‚¹ãƒ‘ースãƒã‚¹.pptm
ランダムプãƒã‚¸ã‚§ã‚¯ã‚·ãƒ§ãƒ³ã¨ã‚¹ãƒ‘ースãƒã‚¹ 鈴木 大慈 æ±äº¬å¤§å¦æƒ…å ±ç†å·¥å¦ç³»ç ”究科æ±äº¬å¤§å¦æƒ…å ±ç†å·¥å¦ç³»ç ”究科 æ•°ç†æƒ…å ±å¦å°‚æ”» 2010/7/16→7/26 1 • Compressed Sensing (CS) - encoding – ランダムプãƒã‚¸ã‚§ã‚¯ã‚·ãƒ§ãƒ³ – Johnson–Lindenstrauss Lemma– Johnson–Lindenstrauss Lemma • Lasso & Dantzig Selector – decoding [Candes, Romberg, and Tao: Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Trans. on Information Theory, 52(2)
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Learning Compressed Sensing
3000th post. Wow !
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Compressive Imaging: A New Single-Pixel Camera | Rice DSP
Caltech UGCS
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