基于扩散模型的缺陷检测和归因理论与方法，国家重点研发计划. 执行时间：2024.01.01-2028.12.31（主持）
耦合多重先验信息的低秩张量恢复模型、理论与算法研究. 国家自然科学基金面上项目. 执行时间：2021.01-2024.12.（主持）
基于样本的非线性压缩感知理论及其应用. 国家自然科学基金面上项目. 执行时间：2017.01-2020.12.（主持）
低秩矩阵复原的Schatten-q正则化理论与算法研究. 国家自然科学基金面上项目. 执行时间：2013.01-2016.12（主持）
基于L1/2正则化的压缩传感可重构性理论研究. 国家自然科学基金青年项目. 执行时间：2011.01-2013.12（主持）
关于前馈神经网络结构与本质逼近阶研究. 国家自然科学基金青年项目. 执行时间：2008.01-2011.12（主持）
关于神经网络拓扑选择与逼近阶研究. 教育部科学技术重点项目. 执行时间：2008.01-2010.12（主持）
关于神经网络逼近能力与算法研究. 部委级科研项目面上项目. 执行时间：2008.06-2010.06（主持）
关于前向神经网络逼近复杂性与算法研究. 部委级科研项目一般项目. 执行时间：2009.06-2012.06（主持）
基于Lq极小化的压缩传感理论及应用研究. 中央高校基本科研业务费重点项目，执行时间：2010.10-2013.10（主持）
块稀疏信号重构的非凸极小化方法及算法应用研究. 中央高校基本科研业务费重大项目，执行时间：2015.01-2017.12（主持）
网络上的流行病动力系统的研究. 国家自然科学基金青年项目. 执行时间：2008.01-2010.12（主持子课题一项）
Guaranteed tensor recovery fused low-rankness and smoothness
Wang H. L., Peng J. J., Qin W. J., Wang J.J. , Meng D. Y.
IEEE Transactions on Pattern Analysis and Machine Intelligence,2023
[pdf]
An analysis of noise folding for low-rank matrix recovery
Huang J. W., Zhang F., Wang J.J. , Wang H. L., Liu X. L., Jia J. P.
Analysis and Applications,2023
[pdf]
Hyperspectral image denoising via nonlocal spectral sparse subspace representation
Wang H. L., Peng J. J., Cao X. Y., Wang J.J. , Zhao Q., Meng D. Y.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2023
[pdf]
Generalized nonconvex regularization for tensor RPCA and its applications in visual inpainting
Zhang F., Wang H. L., Qin W. J., Zhao X. L., Wang J.J. .
Applied Intelligence,2023
[pdf]
Fluorescence microscopy images denoising via deep convolutional sparse coding
Chen G., Wang J.J. , Wang H. L., Wen J. M., Gao Y., Xu Y. J.
Signal Processing: Image Communication,2023
[pdf]
Randomized sampling techniques based low-tubal-rank plus sparse tensor recovery
Zhang F., Yang L. H., Wang J.J. , Luo X.
Knowledge-Based Systems,2023
[pdf]
The perturbation analysis of nonconvex low-rank matrix robust recovery
Huang J. W., Zhang F, Wang J.J. , Liu X. L., Jia J. P.
IEEE Transactions on Neural Networks and Learning Systems
[pdf]
One-bit compressed sensing via total variation minimization method
Zhong Y. X., Xu C., Zhang B., Hou J. Y., Wang J.J.
Signal Processing, 2023
[pdf]
Tensor compressive sensing fused low-rankness and local-smoothness
Liu X. L., Hou J. Y., Peng J. J., Wang H. L., Meng D. Y., Wang J.J.
Proceedings of the AAAI Conference on Artificial Intelligence,2023
[pdf]
Low-Tubal-Rank tensor recovery with multilayer subspace prior learning
Kong W. C., Zhang F., Qin W. J., Wang J.J.
Pattern Recognition,2023
[pdf]
Deep plug-and-play for tensor robust principal component analysis
Tan H., Wang J.J. , Kong W. C.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2023
[pdf]
Matrix recovery using deep generative priors with low-rank deviations
Yu P. B., Wang J.J. , Xu C.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2023
[pdf]
Robust low-rank matrix recovery fusing local-smoothness
Liu X. L., Hou J. Y., Wang J.J. .
IEEE Signal Processing Letters,2022
[pdf]
Tensor robust principal component analysis from multi-level quantized observations
Wang J.J., Hou.J., Eldar Y.C.
IEEE Transactions on Information Theory,2022
[pdf]
Exact decomposition of joint low rankness and local smoothness plus sparse matrices
Peng J., Wang Y., Zhang H., Wang J.J., Meng D.
IEEE Transactions on Pattern Analysis and Machine Intelligence,2022
[pdf]
low-rank high-order tensor completion with applications in visual data
Qin W., Wang H., Zhang F., Wang J.J. , Luo X., Huang T.
IEEE Transactions on Image Processing,2022
[pdf]
Robust high-order tensor recovery via nonconvex low-rank approximation
Qin W., Wang H., Ma W., Wang J.J.
Proceedings of the IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP),2022
[pdf]
Robust low-rank tensor reconstruction using high-order t-SVD
Qin W., Wang H., Zhang F., Dai M., Wang J.J.
Journal of Electronic Imaging,2021
[pdf]
Robust Low-tubal-rank Tensor Recovery from Binary Measurements
Hou J. , Zhang F., Qiu H., Wang J.J., Wang Y., Meng D.
IEEE Transactions on Pattern Analysis and Machine Intelligence,2021
[pdf]
A novel approach to large-scale dynamically weighted directed network representation
Luo X., Wu H., Wang Z., Wang J.J., Meng D.
IEEE Transactions on Pattern Analysis and Machine Intelligence,2021
[pdf]
Low-tubal-rank plus Sparse Tensor Recovery with Prior Subspace Information
Zhang F., Wang J.J. , Wang W.D.,Xu C.
IEEE Transactions on Pattern Analysis and Machine Intelligence,2021
[pdf]
Low-rank matrix recovery via regularized nuclear norm minimization
Wang W., Zhang F., Wang J.J.
Applied and Computational Harmonic Analysis,2021
[pdf]
Large-scale affine matrix rank minimization with a novel nonconvex regularizer
Wang Z., Liu Y., Luo X., Wang J.J., Gao C., Peng D., Chen W.
IEEE Transactions on Neural Networks and Learning Systems,2021
[pdf]
Generalized non-convex approach for low-tubal-rank tensor recovery
Wang H., Zhang F., Wang J.J., Huang T., Huang J., Liu X.
IEEE Transactions on Neural Networks and Learning Systems,2021
[pdf]
Group sparse recovery in impulsive noise via alternating direction method of multipliers
Wang J.J., Huang J.W., Zhang F, Wang W.D.
Applied and Computational Harmonic Analysis,2021
[pdf]
One-bit tensor completion via transformed tensor singular value decomposition
Hou J., Zhang F., Wang J.J.
Applied Mathematical Modelling,2021
[pdf]
Estimating structural missing values via low-tubal-rank tensor completion
Wang H., Zhang F., Wang J.J., Wang Y.
Proceedings of the 45th International Conference on Acoustics,2021
[pdf]
Low-tubal-rank tensor recovery from one-bit measurements
Hou J., Zhang F., Wang Y., Wang J.J.
Proceedings of the 45th International Conference on Acoustics,2021
[pdf]
Non-convex sparse deviation modeling via generative models
Yang Y., Wang H., Wang J.J.
IEEE International Conference on Acoustics,2021
[pdf]
CMCS-net: image compressed sensing with convolutional measurement via DCNN
Xie Y., Wang H., Wang J.J.
IET Image Processing,2021
[pdf]
A denoising convolutional neural network inspired via multi-layer convolutional sparse coding
Wen Z., Wang H., Wang J.J.
Journal of Electronic Imaging,2021
[pdf]
Uniqueness guarantee of solutions of tensor tubal-rank minimization problem
Zhang F., Hou J., Wang J.J., Wang W.
IEEE Signal Processing Letters,2020
[pdf]
One-bit Compressed sensing via lp minimization method
Hou J.Y., Wang J.J., Zhang F., Huang J.W.
Inverse Problems,2020
[pdf]
RIP-based performance guarantee for low-tubal-rank tensor recovery
Zhang F, Wang W.D., Huang J.W., Wang J.J.,Wang Y.
Journal of Computational and Applied Mathematics,2020
[pdf]
Tensor restricted isometry property analysis for a large class of random measurement ensembles
Zhang F, Wang W.D.,Hou J.Y., Wang J.J., Huang J.W.
Science China .Information Sciences,2021
[pdf]
A nonconvex penalty function with integral convolution approximation for compressed sensing
Wang J.J., Zhang F., Huang J.W., Wang W.D., Yuan C.
Signal Processing,2019
[pdf]
Block-sparse signal recovery based on truncated l1- minimisation in non-Gaussian noise
Feng Q, Wang J.J.,Zhang F.
IET Communications,2019
[pdf]
Image denoising in impulsive noise via weighted Schatten p-norm regularization
Chen G., Wang J.J., Zhang F
Journal of Electronic Imaging,2019
[pdf]
Sharp sufficient condition of block signal recovery via l2/l1-minimization
Huang J.W., Wang J.J., Wang W.D.
IET Signal Processing,2019
[pdf]
Enhanced Block-Sparse Signal Recovery Performance via Truncated ℓ2/ℓ1−2 Minimization
Kong W., Wang J.J., Wang W.D., Zhang F.
Journal of Computational Mathematics,2020
[pdf]
Fast and efficient algorithm for matrix completion via closed-form 2/3-thresholding operator
Wang Z., Wang W., Wang J.J.
Neurocomputing,2019
[pdf]
On asymptotic of extremes from generalized Maxwell distribution
Huang J.W., Wang J.J.
Bull. Korean Math. Soc,2018
[pdf]
Block-sparse signal recovery via l2/l1-2minimisation method
Wang, W,D., Wang J.J., Zhang, Z.L.
IET Signal Processing,2018
[pdf]
Reconstruction Analysis of Block Sparse Signal via Truncated ℓ2/ℓ1-minimization with Redundant Dictionaries
Jia y.L., Wang J.J.,Feng Z.
IET Signal Processing,2018
[pdf]
New Sufficient Conditions of Signal Recovery with Tight Frames via l1-Analysis Approach
Huang J.W., Wang J.J., Zhang F., Wang, W.D.
IEEE Access,2018
[pdf]
Higher order expansion for moments of extreme for generalized Maxwell distribution
Huang J.W., Wang J.J.,Luo G.W.,Pu H.
Communications in Statistics - Theory and Methods,2018
[pdf]
Higher order asymptotic behaviour of partial maxima of random sample from generalized Maxwell distribution under power normalization
Huang J.W., Wang J.J.
Applied Mathematics-A Journal of Chinese Universities,2018
[pdf]
Sparse signal recovery with prior information by iterative reweighted least squares algorithm
Feng N.C., Wang J.J.,Wang W.D.
Journal of Inverse and Ill-posed Problems,2018
[pdf]
Perturbations of Compressed Data Separation With Redundant Tight Frames
Zhang F., Wang J.J, Wang,Y., Huang, J., &Wang W.
IEEE Access,2018
[pdf]
An inertial projection neural network for sparse signal reconstruction via l1− 2 minimization
Zhu L., Wang J.J, He, X., & Zhao Y.
Neurocomputing,2018
[pdf]
Enhancing Matrix Completion Using a Modified Second-Order Total Variation
Wang W.D., Wang J.J.
Discrete Dynamics in Nature and Society,2018
[pdf]
A Novel Thresholding Algorithm for Image Deblurring Beyond Nesterov’s Rule
Wang Z., Wang J.J., Wang W.D.
IEEE Access,2018
[pdf]
Robust Signal Recovery With Highly Coherent Measurement Matrices
Wang W.D., Wang J.J.,Zhang Z.L.
IEEE Signal Processing Letters,2017
[pdf]
Tail properties and approximate distribution and expansion for extreme of lgmd
Huang J.W., Wang J.J, Luo G.W., He J.
Journal of Inequalities & Applications,2017
[pdf]
On the rate of convergence of maxima for the generalized Maxwell distribution
Huang J.W., Wang J.J.,Luo G.W.
Statistics: A Journal of Theoretical and Applied Statistics,2017
[pdf]
Non-convex block-sparse compressed sensing with redundant dictionaries
Liu C.Y., Wang J.J., Wang W.D., Wang, Z.
Iet Signal Processing,2017
[pdf]
Improved RIP Conditions for Compressed Sensing with Coherent Tight Frames
Wang Y., Wang J.J.
Discrete Dynamics in Nature and Society,2017
[pdf]
基于非凸极小化的扰动压缩数据分离[J]
刘春燕,王文东,王建军
电子学报,2017
[pdf]
基于混合l2/l1范数极小化方法的块稀疏信号重构条件[J]
王建军,袁建军,王尧
数学学报,2017
[pdf]
Nonlinear Compressed Sensing Based on Kernel Sparse Representation
Nie F., Wang J.J., Wang Y., & Jing J.
In 2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER),2017
[pdf]
Block-sparse compressed sensing with partially known signal support via non-convex minimisation
He S.Y., Wang Y,Wang J.J Xu Z.B,
Iet Signal Processing,2016
[pdf]
基于相干性理论的非凸块稀疏压缩感知
王文东, 王建军, 王尧, 张自力
中国科学 信息科学,2016
[pdf]
Kernel canonical correlation analysis via gradient descent
Cai J, Tang Y,Wang J.J.
Neurocomputing,2016
[pdf]
A perturbation analysis of block-sparse compressed sensing via mixed l2/l1 minimization
Zhang J.,Wang J.J., Wang W.D.
Neurocomputing,2016
[pdf]
Perona–Malik Model with a New Diffusion Coefficient for Image Denoising[J]
Yuan J., Wang J.J.
International Journal of Image & Graphics,2016
[pdf]
Low rank tensor completion via partial sum minimization of singular values
Zhang F,Wang J.J., Jing J.
International Conference on Automatic Control and Information Engineering,2016
[pdf]
Confirming robustness of fuzzy support vector machine via ξ–α bound
Yang C Y., Wang J.J., Chou J J., et al.
Neurocomputing,2015
[pdf]
A perturbation analysis of nonconvex block-sparse compressed sensing
Wang J.J., Zhang J., Wang W.D., et al.
Communications in Nonlinear Science & Numerical Simulation,2015
[pdf]
基于迭代重赋权最小二乘算法的块稀疏压缩感知
王文东, 王尧, 王建军
电子学报,2015
[pdf]
Restricted p-isometry properties of nonconvex block-sparse compressed sensin
Wang Y., Wang J.J., Xu Z.B.
Signal Processing,2014
[pdf]
Active contours driven by local intensity and local gradient fitting energies
Yuan J.J., Wang J.J.
International Journal of Pattern Recognition and Artificial Intelligence,2014
[pdf]
Recovery of Sparse Signal and Nonconvex Minimization
Jing J., Wang J.J.
Applied Mechanics & Materials,2014
[pdf]
On recovery of block-sparse signals via mixed l2/lq(0
[pdf]
A note on block-sparse signal recovery with coherent tight frames
Wang Y.,Wang J.J.,Xu Z.B.
Discrete Dynamics in Nature and Society,2013
[pdf]
Lp Error estimate for minimal norm SBF interpolation
Wang J.J., Yang C. Y., Gu Z.G.
Journal of Inequalities and Applications 2013,2013
[pdf]
Estimation of Approximation with Jacobi Weights by Multivariate Baskakov Operator
Wang J.J., Guo H.F., Jing J.
Journal of Function Spaces,2013
[pdf]
Derivatives of multivariate Bernstein operators and smoothness with Jacobi weights
Wang J.J., Peng Z.X.,Duan S.K., Jing J.
Journal of Applied Mathematics,2012
[pdf]
Estimation of approximating rate for neural networks in L(w,p)
Wang J.J.,Yang C.Y., Jing J.
Journal of Applied Mathematics,2012
[pdf]
Constructive estimation of approximation for trigonometric neural networks
Wang J.J.,Xu W.H., Zou B.
International Journal of Wavelets, Multiresolution and Information Processing,2012
[pdf]
Approximation of algebraic and trigonometric polynomials by feedforward neural networks
Wang J.J.,Chen B.L. , Yang C.Y.
Neural Computing & Applications,2012
[pdf]
L2-Loss Twin Support Vector Machine for Classification
Gao B.B.,Wang J.J., Huang H.
5th International Conference on BioMedical Engineering and Informatics (BMEI),2012
[pdf]
Estimator for Fuzzy Support Vector Machine
Yang C.Y.,Wang J.J.
Advanced Science Letters,2012
[pdf]
Neural networks and the best Trigonometric approximation
Wang J.J., Xu Z.B.
Journal of Systems Science and Complexity,2011
[pdf]
Sparse signal recovery based on lq(0
[pdf]
Aproximation order for multivariate Durrmeyer operators with Jacobi weights
Wang J.J.,Yang C.Y., Duan S.K.
Abstract & Applied Analysis,2011
[pdf]
Bernstein 型算子线性组合加Jacobi权逼近及高阶导数的等价定理
彭联勇，王建军
应用数学,2011
[pdf]
New study of neural networks: the essential order of approximation
Wang J.J., Xu Z.B.
Neural Networks,2011
[pdf]
Derivatives of Bernstein operators and smoothness with Jacobi weights
Wang J.J., Han G.D., et al.
Taiwanese Journal of Mathematics,2011
[pdf]
稳健Lq(0
[pdf]
Approximation with Jacobi weights by Baskakov operators. Taiwanese Journal of Mathematics
Wang J.J., Xu Z.B.
Taiwanese Journal of Mathematics,2009
[pdf]
Margin calibration in SVM class-imbalanced learning
Yang C.Y., Yang J.S.,Wang J.J.
Neurocomputing,2009
[pdf]
How to measure the essential approximation capability of a FNN
Wang J.J., Zou B., Chen B.L.
2009 Fifth International Conference on Natural Computation, IEEE Computer Society,2009
[pdf]
Estimation of covering number in learning theory
Wang J.J., Huang H. Luo Z.T.,Bai l.C.
Fifth International Conference on Semantics, Knowledge and Grid, IEEE Computer Society,2009
[pdf]
Generalization performance of ERM algorithm with geometrically ergodic markov chain samples
Xu J., Zou B.,Wang J.J.
Fifth International Conference on Natural Computation; IEEE Computer Society,2009
[pdf]
神经网络的加权本质逼近阶
王建军, 徐宗本
数学年刊:中文版,2009
[pdf]
多元多项式函数的三层前向神经网络逼近方法
王建军, 徐宗本
计算机学报:中文版,2009
[pdf]
Baskakov算子线性组合加Jacobi权逼近及高阶导数的正逆定理
王建军, 徐宗本
系统科学与数学,2008
[pdf]
Constructive approximation method of polynomial by neural networks
Wang J.J., Xu Z.B.,Jing J.
International conference on congnitive neurodynamics(2007), Springer Science Business Media B.V,2008
[pdf]
Imbalanced SVM learning with margin compensation. Lecture Notes in Computer Science, Germany
Yang C.Y.,Wang J.J., Yang J.S.,Yu G.D.
Springer-Verlag,2008
[pdf]
Stechkin-marchaud type inequalities with Jacobi weights for Bernstein operators
Wang J.J., Xue Y.C., Li F.J.
Journal of Applied mathematics and computing,2007
[pdf]
近似指数型神经网络的本质逼近阶
王建军,徐宗本
中国科学,2006
[pdf]
Multiple positive radial solutions of elliptic equations in an exterior domain. Monatshefte fur mathematik
Han G.D.,Wang J.J.
Monatshefte fur mathematik,2006
[pdf]
and Meng D.Y., Approximation bound of mixture networks in L(w,p) spaces. Lecture Notes in Computer Science, Germany
Xu Z.B., Wang J.J., and Meng D.Y.
Springer-Verlag 2006,2006
[pdf]
Baskakov算子加Jacobi权逼近及导数的正逆定理
王建军,薛银川
数学年刊,2006
[pdf]
Baskakov型算子加权逼近下的Stechkin-Marchand不等式
王建军,薛银川
数学研究与评论,2004
[pdf]
Approximation bounds by neural networks in L(w, p). Lecture Notes in Computer Science, Germany
Wang J.J., Xu Z.B.,and Xu W.J.
Springer-Verlag,2004
[pdf]
2022.09.15：基于深度卷积神经网络与压缩感知的图像恢复方法