@InProceedings{8553268,
  author = {G. Campobello},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Rethinking Compressive Sensing},
  year = {2018},
  pages = {1765-1769},
  abstract = {In this paper we show that Compressive Sensing (CS) can be casted as an impulse response estimation problem. Using this interpretation we re-obtain some theoretical results of CS in a simple manner. Moreover, we prove that in the case of a randomly generated sensing matrix, reconstruction probability depends on the kurtosis of the distribution used for its generation.},
  keywords = {compressed sensing;matrix algebra;probability;transient response;CS;simple manner;randomly generated sensing matrix;impulse response estimation problem;compressive sensing;Signal processing;Reconstruction algorithms;Linear systems;Estimation;Europe;Compressed sensing;Sparse matrices},
  doi = {10.23919/EUSIPCO.2018.8553268},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438975.pdf},
}

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