Zobrazeno 1 - 10
of 1 301
pro vyhledávání: '"Hing Cheung So"'
Autor:
Jiahao Han, Shiyang Tang, Zhanye Chen, Yi Ren, Zhixin Lian, Ping Guo, Yinan Li, Linrang Zhang, Hing Cheung So
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 15148-15165 (2024)
As an important supplement to traditional airborne synthetic aperture radar (SAR), multirotor unmanned aerial vehicle (UAV) SAR has the advantages of low cost, high flexibility, and strong survival ability. However, due to the complex motion and flig
Externí odkaz:
https://doaj.org/article/4758e477e902489db46b5280b1b1f84f
Publikováno v:
IEEE Access, Vol 7, Pp 15634-15640 (2019)
In this paper, the problem of direction-of-arrival (DOA) estimation for a uniform linear array with single-snapshot observations is addressed. Two non-parametric DOA estimators are developed, which can be applied in any azimuth range with one snapsho
Externí odkaz:
https://doaj.org/article/99acdc60cc42414d9339e06b2198fe8e
Publikováno v:
IEEE Access, Vol 7, Pp 55620-55630 (2019)
A fast and accurate non-iterative direction-of-arrival (DOA) estimation algorithm for multiple targets in additive white Gaussian noise is devised in this paper. The proposed estimator makes use of the two highest magnitudes discrete Fourier transfor
Externí odkaz:
https://doaj.org/article/e64be1af7ee345099bc9f063cf84ba1a
Publikováno v:
IEEE Access, Vol 7, Pp 151902-151914 (2019)
There are two important issues in the construction of a radial basis function (RBF) neural network. The first one is to select suitable RBF centers. The second one is that the resultant RBF network should be with good fault tolerance. This paper prop
Externí odkaz:
https://doaj.org/article/76535e78199e4093bc34c979bdbf61f7
One-bit sampling has emerged as a promising technique in multiple-input multiple-output (MIMO) radar systems due to its ability to significantly reduce data volume and processing requirements. Nevertheless, current detection methods have not adequate
Externí odkaz:
http://arxiv.org/abs/2403.06756
Publikováno v:
IEEE Access, Vol 6, Pp 47804-47814 (2018)
The problem of data reconstruction with partly sampled elements under a tensor structure, which is referred to as tensor completion, is addressed in this paper. The properties of the rank-1 tensor train decomposition and the tensor Kronecker decompos
Externí odkaz:
https://doaj.org/article/c56055eae1a747bda72b6615f9c58b0f
Autor:
Xiong, Wenxin, Chen, Yuming, He, Jiajun, Shi, Zhang-Lei, Hu, Keyuan, So, Hing Cheung, Leung, Chi-Sing
This short communication addresses the problem of elliptic localization with outlier measurements. Outliers are prevalent in various location-enabled applications, and can significantly compromise the positioning performance if not adequately handled
Externí odkaz:
http://arxiv.org/abs/2401.15619
With the emerging environment-aware applications, ubiquitous sensing is expected to play a key role in future networks. In this paper, we study a 3-dimensional (3D) multi-target localization system where multiple intelligent reflecting surfaces (IRSs
Externí odkaz:
http://arxiv.org/abs/2310.15574
To alleviate the bias generated by the l1-norm in the low-rank tensor completion problem, nonconvex surrogates/regularizers have been suggested to replace the tensor nuclear norm, although both can achieve sparsity. However, the thresholding function
Externí odkaz:
http://arxiv.org/abs/2310.06233
This paper presents a novel loss function referred to as hybrid ordinary-Welsch (HOW) and a new sparsity-inducing regularizer associated with HOW. We theoretically show that the regularizer is quasiconvex and that the corresponding Moreau envelope is
Externí odkaz:
http://arxiv.org/abs/2310.04762