J
Jie Chen
Researcher at Beihang University
Publications - 487
Citations - 12669
Jie Chen is an academic researcher from Beihang University. The author has contributed to research in topics: Synthetic aperture radar & Linear system. The author has an hindex of 44, co-authored 453 publications receiving 10931 citations. Previous affiliations of Jie Chen include South China University of Technology & Northeastern University.
Papers
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Journal ArticleDOI
Prognostic value of cytokine profile on survival in non-small cell lung cancer patients treated with radiotherapy.
TL;DR: This study is to investigate the prognostic value of cytokine profile on cancer development and progression in mice by studying the response of these cytokines to EMT and conventional chemotherapy.
Journal ArticleDOI
Mean-square stabilizability via output feedback for a non-minimum phase networked feedback system
TL;DR: This work studies mean-square stabilizability via output feedback for a networked linear time invariant (LTI) feedback system with a non-minimum phase plant and analytically describes intrinsic constraints among channel packet dropout probabilities and the plant's characteristics, such as unstable poles, non- Minimum phase zeros and Wonham decomposition forms.
Proceedings ArticleDOI
Trade-offs in information-limited feedback systems: MIMO Bode-type integrals and power allocation
Song Fang,Hideaki Ishii,Jie Chen +2 more
TL;DR: Two information-theoretic measures, termed negentropy rate and channel blurredness respectively, are proposed to quantify the effect of the multivariate disturbance and communication channel constraints on the Bode-type integrals.
Proceedings ArticleDOI
Feedback stabilization of MIMO systems in the presence of stochastic network uncertainties and delays
TL;DR: In this article, the mean-square stabilization problem of linear time-invariant systems subject to stochastic multiplicative uncertainties and time delays is studied and a complete, computationally efficient solution is provided in the form of a generalized eigenvalue problem readily solvable by means of linear matrix inequality optimization.
Journal ArticleDOI
Scalloping Suppression for ScanSAR Images Based on Modified Kalman Filter With Preprocessing
TL;DR: In this paper, a modified Kalman filter is proposed to estimate the intensity of scalloping and an innovative preprocessing operation is introduced, involving image segmentation and pixel value filling, which can accommodate the complex scene well.