The term Compressed Sensing was conceived by David L. Donoho in 2006. With the leverage of extra information in terms of sparsity, the signal can be reconstructed without performing the usual steps of the Nyquist-Shannon reconstruction algorithm. A wide variety of signals including bio-signals, medical images, and radar signals are sparse in one or more domains. Intel humdity and temperature data is used for simulation. Sensing matrix is generated randomly and the signal is sparse in DCT domain.
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The term Compressed Sensing was conceived by David L. Donoho in 2006. With the leverage of extra information in terms of sparsity, the signal can be reconstructed without performing the usual steps of the Nyquist-Shannon reconstruction algorithm. A wide variety of signals including bio-signals, medical images, and radar signals are sparse in one…
piyushkumarhcu/Compressed-Sensing
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The term Compressed Sensing was conceived by David L. Donoho in 2006. With the leverage of extra information in terms of sparsity, the signal can be reconstructed without performing the usual steps of the Nyquist-Shannon reconstruction algorithm. A wide variety of signals including bio-signals, medical images, and radar signals are sparse in one…
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