Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Jin Hyeok Yoo"'
Publikováno v:
IEEE Transactions on Signal Processing. 68:4135-4147
In this paper, we address the problem of tracking time-varying support of a sparse signal given a sequence of observation vectors. We model the dynamic variation of the support set using the discrete-state Markov process and employ the Rao-Blackwelli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf24fb61a757470e64d002546b6da37a
https://doi.org/10.1109/tsp.2020.3007962
https://doi.org/10.1109/tsp.2020.3007962
Autor:
Jin Hyeok Yoo, Boyeal Kim, Hyuk-Jae Lee, Sang-Hyun Lee, Ik Joon Chang, Dohun Kwon, Hyun Kim, Minh-Son Le, Duy-Thanh Nguyen, Jun Won Choi
Publikováno v:
DATE
Deep neural network (DNN) training suffers from the significant energy consumption in memory system, and most existing energy reduction techniques for memory system have focused on introducing low precision that is compatible with computing unit (e.g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::497f2ff2776e758322f6897967ccaf50
https://doi.org/10.23919/date48585.2020.9116530
https://doi.org/10.23919/date48585.2020.9116530
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585822
ECCV (27)
ECCV (27)
In this paper, we propose a new deep architecture for fusing camera and LiDAR sensors for 3D object detection. Because the camera and LiDAR sensor signals have different characteristics and distributions, fusing these two modalities is expected to im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49f49f2cf0b3529776cf6557518434c4
https://doi.org/10.1007/978-3-030-58583-9_43
https://doi.org/10.1007/978-3-030-58583-9_43
Publikováno v:
EUSIPCO
In this paper, we propose a new beam training framework to cope with mobility scenarios in millimeter wave communications. When a position of the mobile changes, the basestation needs to perform beam training frequently to track the time-varying chan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::356dcd0f2c2c3e50042227668b60f5e2
https://doi.org/10.23919/eusipco.2018.8553578
https://doi.org/10.23919/eusipco.2018.8553578
Publikováno v:
EUSIPCO
In this paper, we propose a low-complexity greedy recovery algorithm which can recover sparse signals with time-varying support. We consider the scenario where the support of the signal (i.e., the indices of nonzero elements) varies smoothly with cer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e1d2e16165703340ab4f245d3209f2e
https://doi.org/10.23919/eusipco.2018.8553450
https://doi.org/10.23919/eusipco.2018.8553450
Publikováno v:
ICC
In this paper, we propose a new recursive sparse channel recovery algorithm which can track time-varying support of angular domain channel response vector in mobility scenario for millimeter wave-band communications. We model the angle of departure (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab81bfc1b0e328a684ee88fab056caec
https://doi.org/10.1109/icc.2017.7996518
https://doi.org/10.1109/icc.2017.7996518
Publikováno v:
ICCS
In this paper, we investigate a problem of estimating time-varying sparse channel impulse response for wireless communications. We are primarily interested in the scenario where the support of channels (i.e., the location of nonzero elements in chann
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adfa1869adadfb324b137823891a40c7
https://doi.org/10.1109/iccs.2016.7833599
https://doi.org/10.1109/iccs.2016.7833599
Publikováno v:
2015 Fourth International Conference on Information Science and Industrial Applications (ISI).
In this paper, the LQ-servo controller using a reduced order observer is proposed. Since the reduced order observer estimates only the immeasurable states, it does not need to realize the full order estimator or install many sensors. The design metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b60f96ca2a9721cfc0870346dbd86a9
https://doi.org/10.1109/isi.2015.19
https://doi.org/10.1109/isi.2015.19