TY - GEN
T1 - Compressive sampling for signal classification
AU - Haupt, Jarvis
AU - Castro, Rui
AU - Nowak, Robert
AU - Fudge, Gerald
AU - Yeh, Alex
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Compressive Sampling (CS), also called Compressed Sensing, entails making observations of an unknown signal by projecting it onto random vectors. Recent theoretical results show that if the signal is sparse (or nearly sparse) in some basis, then with high probability such observations essentially encode the salient information in the signal. Further, the signal can be reconstructed from these "random projections," even when the number of observations is far less than the ambient signal dimension. The provable success of CS for signal reconstruction motivates the study of its potential in other applications. This paper investigates the utility of CS projection observations for signal classification (more specifically, mary hypothesis testing). Theoretical error bounds are derived and verified with several simulations.
AB - Compressive Sampling (CS), also called Compressed Sensing, entails making observations of an unknown signal by projecting it onto random vectors. Recent theoretical results show that if the signal is sparse (or nearly sparse) in some basis, then with high probability such observations essentially encode the salient information in the signal. Further, the signal can be reconstructed from these "random projections," even when the number of observations is far less than the ambient signal dimension. The provable success of CS for signal reconstruction motivates the study of its potential in other applications. This paper investigates the utility of CS projection observations for signal classification (more specifically, mary hypothesis testing). Theoretical error bounds are derived and verified with several simulations.
UR - http://www.scopus.com/inward/record.url?scp=47049124348&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47049124348&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2006.354994
DO - 10.1109/ACSSC.2006.354994
M3 - Conference contribution
AN - SCOPUS:47049124348
SN - 1424407850
SN - 9781424407859
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1430
EP - 1434
BT - Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
T2 - 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
Y2 - 29 October 2006 through 1 November 2006
ER -