[1] Yingchun Jiang and Junjian Zhao. Random sampling and reconstruction of signals with finite rate of innovation. Bulletin of the Korean Mathematical Society, 2022, 59(2): 285-301. (SCI)
[2] Yingchun Jiang and Wan Li. Random sampling in multiply
generated shift-invariant subspaces of mixed Lebesgue spaces, Journal of
Computational and Applied Mathematics, 2021, 386: 113237. (SCI)
[3] Yingchun Jiang and Wan Li. Convolution random sampling in multiply
generated shift-invariant spaces, Annals of Functional Analysis, 2021,
12:10. (SCI)
[4] Yingchun Jiang and Jiao Li. Frame-based average sampling
in multiply generated shift-invariant subspaces of mixed Lebesgue spaces,
Taiwanese Journal of Mathematics, 2021, 25(3): 535-552. (SCI)
[5] Yingchun Jiang and Wenchang Sun. Adaptive sampling of
time-space signals in a reproducing kernel subspace of mixed Lebesgue space,
Banach Journal of Mathematical Analysis, 2020, 14: 821-841. (SCI)
[6] Yingchun Jiang and Junke Kou. Semi-average sampling for
shift-invariant signals in a mixed Lebesgue space, Numerical Functional
Analysis and Optimization, 2020, 41(9): 1045-1064. (SCI)
[7] Cheng Cheng, Yingchun Jiang* and Qiyu Sun, Spatially
distributed sampling and reconstruction, Applied and Computational Harmonic
Analysis, 2019, 47(1): 109-148. (SCI)
[8] Yingchun Jiang. Average sampling and reconstruction of reproducing
kernel signals in mixed Lebesgue spaces, Journal of Mathematical Analysis and
Applications, 2019: 123370. (SCI)
[9] Cheng Cheng, Yingchun Jiang* and Qiyu Sun, Sampling and
Galerkin reconstruction in reproducing kernel spaces, Applied and Computational
Harmonic Analysis, 2016, 41: 838-659. (SCI)
[10] Yingchun Jiang, Time sampling and reconstruction in weighted
reproducing kernel subspaces, Journal of Mathematical Aalysis and Applications,
2016, 444: 1380-1402. (SCI)
[11] Yingchun Jiang and Suping Wang, Sampling and quasi-optimal
approximation for signals in a reproducing kernel space of homogeneous type,
Journal of Computational and Applied Mathematics, 2017, 319: 296-307. (SCI)
[12] Yingchun Jiang, Suping Wang and Meixiang Yang, Average
sampling and reconstruction for reproducing kernel stochastic signals,
Mathematical Methods in the Applied Sciences, 2016, 39: 2930-2938. (SCI)
[13] Yingchun Jiang, Lusong Wei and Guangxi Chen, An adaptive
sampling method for high-dimensional shift-invariant signals, Mathematical
Methods in the Applied Sciences, 2017, 40: 4529-4537. (SCI)
[14] Yingchun Jiang and Ting Li, Local measurement and diffusion
reconstruction for signals on a weighted graph, Mathematical Problems in Engineering,
2018: 3264294. (SCI)
[15] 范筱,蒋英春*,混合范数条件下平移不变信号的非均匀平均采样,数学学报,2018,61(2):
289-300.
[16] 蒋英春,王素萍,加权再生核空间中信号的平均采样与重构,数学学报,2016,
59(2): 233-246.
[17] Yingchun Jiang, Anisotropic curl-free wavelets on the unit
cube, Acta Mathematica Sinica, English Series, 2013, 29(4): 801-814. (SCI)
[18] Yingchun Jiang, Improved error analysis for adaptive wavelet
algorithms, Applied Mathematics and Computation, 2012, 219: 2134-2141. (SCI)
[19] Cheng Cheng, Yingchun Jiang and Qiyu Sun, Spatially
distributed sampling and reconstruction of high-dimensional signals, 2015
International Conference on Sampling Theory and Applications, reported,
453-457, Washington DC, United States, 2015. (EI)