TY - GEN
T1 - Sampled-Data Filters with Compactly Supported Acquisition Prefilters
AU - Yamamoto, Yutaka
AU - Yamamoto, Kaoru
AU - Nagahara, Masaaki
N1 - Funding Information:
1Professor Emeritus, Kyoto University, Kyoto 606-8510, Japan yy@i.kyoto-u.ac.jp. This work was supported in part by the Japan Society for the Promotion of Science under Grants-in-Aid for Scientific Research No. 15H04021 and 24360163. The author wishes to thank DIGI-TEO and Laboratoire des Signaux et Systemes (L2S, UMR CNRS), CNRS-CentraleSupelec-University Paris-Sud and Inria Saclay for their financial support while part of this research was conducted.
Funding Information:
2Department of Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan k.yamamoto@ieee.org. This work was supported in part by the Swedish Research Council through the LCCC Linnaeus Center.
Funding Information:
3Institute of Environmental Science and Technology, The University of Kitakyushu, Fukuoka 808-0135, Japan. nagahara@ieee.org. This work was supported in part by JSPS KAKENHI grant numbers 15H02668 and 16KK0134, and SCOPE grant number 172310003.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - This paper studies the problem of reconstructing continuous-time signals from discrete-time uniformly sampled data. This signal reconstruction problem has been studied by the authors in various contexts, and led to a new signal processing paradigm. The key idea there is to employ a physically realizable signal generator model, and design an (sub)optimal filter via H^ infty(mathbb C- +) optimal sampled-data control theory. The present paper aims at extending this framework to a more general setting where observed data are acquired through an acquisition device (prefilter) that has compact support. In this way, the framework can capture the properties of processing signals with a localized acquisition filter. We give a general setup as well as approximate solution methods along with their convergence results. A simulation is presented to illustrate some properties of the result.
AB - This paper studies the problem of reconstructing continuous-time signals from discrete-time uniformly sampled data. This signal reconstruction problem has been studied by the authors in various contexts, and led to a new signal processing paradigm. The key idea there is to employ a physically realizable signal generator model, and design an (sub)optimal filter via H^ infty(mathbb C- +) optimal sampled-data control theory. The present paper aims at extending this framework to a more general setting where observed data are acquired through an acquisition device (prefilter) that has compact support. In this way, the framework can capture the properties of processing signals with a localized acquisition filter. We give a general setup as well as approximate solution methods along with their convergence results. A simulation is presented to illustrate some properties of the result.
UR - http://www.scopus.com/inward/record.url?scp=85062174784&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062174784&partnerID=8YFLogxK
U2 - 10.1109/CDC.2018.8619614
DO - 10.1109/CDC.2018.8619614
M3 - Conference contribution
AN - SCOPUS:85062174784
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 6650
EP - 6655
BT - 2018 IEEE Conference on Decision and Control, CDC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 57th IEEE Conference on Decision and Control, CDC 2018
Y2 - 17 December 2018 through 19 December 2018
ER -