TY - GEN
T1 - Compressive information acquisition with hardware impairments and constraints
T2 - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
AU - Gopalakrishnan, S.
AU - Moy, T.
AU - Madhow, U.
AU - Verma, N.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/16
Y1 - 2017/6/16
N2 - Compressive information acquisition is a natural approach for low-power hardware front ends, since most natural signals are sparse in some basis. Key design questions include the impact of hardware impairments (e.g., nonlinearities) and constraints (e.g., spatially localized computations) on the fidelity of information acquisition. Our goal in this paper is to obtain specific insights into such issues through modeling of a Large Area Electronics (LAE)-based image acquisition system. We show that compressive information acquisition is robust to stochastic nonlinearities, and that appropriately designed spatially localized computations are effective, by evaluating the performance of reconstruction and classification based on the information acquired.
AB - Compressive information acquisition is a natural approach for low-power hardware front ends, since most natural signals are sparse in some basis. Key design questions include the impact of hardware impairments (e.g., nonlinearities) and constraints (e.g., spatially localized computations) on the fidelity of information acquisition. Our goal in this paper is to obtain specific insights into such issues through modeling of a Large Area Electronics (LAE)-based image acquisition system. We show that compressive information acquisition is robust to stochastic nonlinearities, and that appropriately designed spatially localized computations are effective, by evaluating the performance of reconstruction and classification based on the information acquired.
KW - Compressed sensing
KW - hardware impairments
KW - image acquisition
KW - low-power front ends
KW - stochastic nonlinearities
UR - http://www.scopus.com/inward/record.url?scp=85023760342&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85023760342&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2017.7953323
DO - 10.1109/ICASSP.2017.7953323
M3 - Conference contribution
AN - SCOPUS:85023760342
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 6075
EP - 6079
BT - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 March 2017 through 9 March 2017
ER -