[1] Bai L, Roy S.Compressive spectrum sensing using a bandpass sampling architecture[J].IEEE J Emerg Sel Top Circuits Syst, 2012, 2(3):433-442.
[2] Sun H, Chiu W, Jiang J, et al.Wideband spectrum sensing with sub-Nyquist sampling in cognitive radios[J].IEEE Trans Signal Process, 2012, 60(11):6068-6073.
[3] Fu W, Yang X.Communication signal blind reconnaissance technology based on probability density estimation blind sources separation[J].Journal of Huazhong University of Science and Technology (Nature Science Edition), 2006, 34(10):24-27.
[4] 石光明, 刘丹华, 高大化, 等.压缩感知理论及其研究进展[J].电子学报, 2009, 37(5):1070-1081. Shi Guang-ming, Liu Dan-hua, Gao Da-hua, et al.Advances in theory and application of compressed sensing[J].Acta Electronica Sinica, 2009, 37(5):1070-1081.(in Chinese)
[5] Donoho D L.Compressed sensing[J].IEEE Trans Inf Theory, 2006, 52(4):1289-1306.
[6] Baraniuk R.More is less:Signal processing and the data deluge[J].Science, 2011, 331(11):717-719.
[7] 付宁, 曹离然, 彭喜元.基于子空间的块稀疏信号压缩感知重构算法[J].电子学报, 2011, 39(10):2338-2342. Fu Ning, Cao Li-ran, Peng Xi-yuan.Compressed sensing of block-sparse signals recovery based on subspace[J].Acta Electronica Sinica, 2011, 39(10):2338-2342.(in Chinese)
[8] Kirolos S, Laska J, Wakin M.Analog-to-information conversion via random demodulation[A].Proceedings of the IEEE Dallas Circuits and Systems Workshop (DCAS)[C].Dallas, Texas:IEEE, 2006.71-74.
[9] Laska J, Kirolos S.Random sampling for analog-to-Information conversion of wideband signals[A].Proceedings of the IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software[C] Richardson, TX:IEEE, 2006.119-122.
[10] Mishali M, Eldar Y C.From theory to practice:sub-Nyquist sampling of sparse wideband analog signals[J].IEEE J Sel Top Sign Proces, 2010, 4(2):375-39.
[11] Mishali M, Eldar Y C, Dounaevsky O, et al.Xampling:Analog to digital at sub-Nyquist rates[J].IET Circuits Devices Syst, 2011, 5(1):8-20.
[12] Lexa M A, Davies M E, Thompson J S.Reconciling compressive sampling systems for spectrally sparse continuous-time signals[J].IEEE Trans Signal Process, 2012, 60(1):155-171.
[13] Chen J, Huo X M.Theoretical results on sparse representations of multiple-measurement vectors[J].IEEE Trans Signal Process, 2006, 54(12):4634-4643.[LL]
[14] Majumdar A, Ward R K, Aboulnasr T.Algorithms to approximately solve NP hard row-sparse MMV recovery problem:Application to compressive color imaging[J].IEEE J Emerg Sel Top Circuits Syst, 2012, 2(3):362-369.
[15] Cotter F S, Rao D B, Engan K, et al.Sparse solutions to linear inverse problems with multiple measurement vectors[J].IEEE Trans Signal Process, 2005, 53(7):2477-2488.
[16] Mishali M, Eldar Y C.Reduce and boost:recovering arbitrary sets of jointly sparse vectors[J].IEEE Trans Signal Process, 2008, 56(10):4692-4702.
[17] Billingsley P.Probability and Measure[M].3rd ed.New York:Wiley, 1995.158-198. |