代表性论文（全部列表参见Google Scholar）
无限维压缩感知/频谱分析方向：
[1] Z. Yang and L. Xie, "On gridless sparse methods for line spectral estimation from complete and incomplete data," IEEE Transactions on Signal Processing, vol. 63, no. 12, pp. 3139–3153, June 15, 2015. [400+引用，无网稀疏频谱分析代表作]
[2] Z. Yang and L. Xie, "Exact joint sparse frequency recovery via optimization methods," IEEE Transactions on Signal Processing, vol. 64, no. 19, pp. 5145–5157, Oct 1, 2016. [300+引用，多通道频谱分析的原子范数方法]
[3] Z. Yang and L. Xie, "Enhancing sparsity and resolution via reweighted atomic norm minimization," IEEE Transactions on Signal Processing, vol. 64, no. 4, pp. 995–1006, Feb 15, 2016. [300+引用，多通道频谱分析的重加权原子范数方法]
[4] Z. Yang, L. Xie and P. Stoica, "Vandermonde decomposition of multilevel Toeplitz matrices with application to multidimensional super-resolution," IEEE Transactions on Information Theory, vol. 62, no. 6, pp. 3685–3701, June 2016. [300+引用，高维频谱分析的原子范数方法，其中解决了Carathéodory-Fejér定理高维形式公开问题，在数学与信息领域均被评价为“首次”]
[5] Z. Yang, J. Tang, Y. C. Eldar, and L. Xie, "On the sample complexity of multichannel frequency estimation via convex optimization," IEEE Transactions on Information Theory, vol. 65, no. 4, pp. 2302–2315, 2019. [多通道原子范数的平均性能理论]
[6] X. Wu, Z. Yang*, P. Stoica, and Z. Xu, "Maximum likelihood line spectral estimation in the signal domain: a rank-constrained structured matrix recovery approach," IEEE Transactions on Signal Processing, vol. 70, pp. 4156–4169, 2022. [频谱分析的信号域极大似然方法]
[7] X. Wu, Z. Yang*, and Z. Xu, "Multichannel frequency estimation in challenging scenarios via structured matrix embedding and recovery (StruMER)," IEEE Transactions on Signal Processing, vol. 71, 3242–3256, 2023. [多通道频谱分析的信号域极大似然方法]
[8] Z. Yang, Y.-L. Mo, and Z. Xu, "Separation-free spectral super-resolution via convex optimization," Applied and Computational Harmonic Analysis, vol. 71, pp. 101650, 2024. [无分辨率限制的频谱分析凸优化方法]
波达方向估计方向：
[9] Z. Yang, L. Xie, and C. Zhang, "Off-grid direction of arrival estimation using sparse Bayesian inference," IEEE Transactions on Signal Processing, vol. 61, no. 1, pp. 38–43, 2013. [1100+引用，离网波达方向估计代表作]
[10] Z. Yang, L. Xie, and C. Zhang, "A discretization-free sparse and parametric approach for linear array signal processing," IEEE Transactions on Signal Processing, vol. 62, no. 19, pp. 4959–4973, Oct 1, 2014. [200+引用，无网稀疏波达方向估计代表作]
[11] Z. Yang, P. Stoica, and J. Tang, "Source resolvability of spatial-smoothing-based subspace methods: A Hadamard product perspective," IEEE Transactions on Signal Processing, vol. 67, no. 10, pp. 2543–2553, 2019. [空间平滑子空间方法的可辨识理论，其中建立了两奇异半正定矩阵Schur-Hadamard积定理，被数学家Roger Horn写入了本科线性代数教材]
[12] Z. Yang, "Nonasymptotic performance analysis of ESPRIT and spatial-smoothing ESPRIT," IEEE Transactions on Information Theory, vol. 69, no. 1, pp. 666–681, 2023. [经典ESPRIT与空间平滑ESPRIT方法的非渐近性能理论]
[13] X. Wu, Z. Yang*, and Z. Xu, "Multichannel frequency estimation with constant amplitude via convex structured low-rank approximation," SIAM Journal on Matrix Analysis and Applications, vol. 45, no. 3, pp. 1643–1668, 2024. [恒模信源波达方向估计的凸优化方法]
压缩感知方向：
[14] Z. Yang, C. Zhang, and L. Xie, "Robustly stable signal recovery in compressed sensing with structured matrix perturbation,"IEEE Transactions on Signal Processing, vol. 60, no. 9, pp. 4658–4671, 2012. [100+引用，有结构性系统扰动的压缩感知理论]
[15] A. Maleki, L. Anitori, Z. Yang, and R.G. Baraniuk, "Asymptotic analysis of complex LASSO via complex approximate message passing (CAMP)," IEEE Transactions on Information Theory, vol. 59, no. 7, pp. 4290–4308, 2013. [300+引用，复数域压缩感知的相变理论，被压缩感知奠基人Donoho和Candes双双施引并正面评价]
信息论、协方差估计等方向：
[16] T. Jiao, K. Wan, Z. Wei, Y. Geng, Y. Li, Z. Yang*, and G. Caire, "Information-theoretic limits of bistatic integrated sensing and communication," IEEE Transactions on Information Theory, vol. 71, no. 12, pp. 9302–9318, 2025. [双基地通感一体化信息理论极限]
[17] H. Xu and Z. Yang*, "Bit-efficient Toeplitz covariance estimation," IEEE Transactions on Information Theory, 2026. [量化协方差估计]
学生代表性论文（与上面部分重复）：
R. A. Horn, S. Luo, H. Xu, and Z. Yang*, "Positivity of a Hadamard product," arXiv:2604.19602, 2026.
W. Zheng, Z. Yang*, and H. Xu, "Joint calibration and direction-of-arrival estimation with sparse linear arrays: parameter identifiability, array design, and algorithms," 2026.
W. Wang and Z. Yang*, "Sign-aided unlimited sampling for robust line spectral estimation," 2026.
H. Xu, W. Zheng, and Z. Yang*, "Compressive Toeplitz covariance estimation from few-bit quantized measurements with applications to DOA estimation," arXiv:2512.22527, 2025.
W. Wang, W. Huang, and Z. Yang*, "Quotient manifold optimization for spectral compressed sensing," arXiv:2511.19108, 2025.
K. Wang, Z. Yang*, H. Wang, "STELLAR: Spatio-temporal tensor completion via low-rankness and smoothness of difference features for traffic data imputation," IEEE Transactions on Intelligent Transportation Systems, 2026.
T. Jiao, Y. Geng, A. M.-C. So, Y. Chu, and Z. Yang*, "Gaussian Arimoto-Blahut algorithm for capacity region calculation of Gaussian vector broadcast channels," IEEE Transactions on Communications, 2026.
H. Xu and Z. Yang*, "Bit-efficient Toeplitz covariance estimation," IEEE Transactions on Information Theory, 2026.
W. Wang, Z. Yang*, J. Shi, and Z. Wei, "Fast and accurate two-dimentional direction-of-arrival estimation using a modified projected descent algorithm," Signal Processing, 2026.
K. Wang, Z. Yang*, Z. Wei, "FALCON: Fast and accurate spatio-temporal signal recovery based on low-rankness and $\ell_p$ nonlocal variation," Signal Processing, 2026.
W. Chen, Z. Yang*, and Z. Wei, "Direction-of-arrival estimation from a mixture of linear and magnitude-only measurements," IEEE Transactions on Vehicular Technology, vol. 75, no. 2, 3470–3474, 2026.
T. Jiao, K. Wan, Z. Wei, Y. Geng, Y. Li, Z. Yang*, and G. Caire, "Information-theoretic limits of bistatic integrated sensing and communication," IEEE Transactions on Information Theory, vol. 71, no. 12, pp. 9302–9318, 2025.
W. Zheng, Z. Yang*, and X. Wu, "Reweighted atomic norm minimization for line spectral estimation with one-bit samples," IEEE Journal of Selected Topics in Signal Processing, vol. 19, no. 6, pp. 1026–1041, 2025.
Y. Chu, W. Wang, S. Liu, Z. Wei, and Z. Yang*, "Downlink-uplink collaborative channel estimation for TDD massive MIMO communications," IEEE Transactions on Signal Processing, vol. 73, pp. 3614–3628, 2025.
W. Chen, Z. Yang, Z. Wei, D.W.K. Ng, and M. Matthaiou, "RIS-aided MIMO Beamforming: Piece-Wise Near-field Channel Model," IEEE Transactions on Communications, 2025.
Y.-L. Mo, W. Wang, J. Shi, and Z. Yang*, "Multichannel sparse recovery for constant modulus signals via convex optimization," IEEE Transactions on Aerospace and Electronic Systems, 2025.
X. Wu, Z. Yang*, Z. Wei, R. Schober, and Z. Xu, "COFFEE: Covariance fitting and focusing for wideband direction-of-arrival estimation," IEEE Transactions on Signal Processing, vol. 72, pp. 5659-5674, 2024.
Y. Chu, Z. Wei, Z. Yang*, and D. W. K. Ng, "Channel estimation for RIS-aided MIMO systems: A partially decoupled atomic norm minimization approach," IEEE Transactions on Wireless Communications, vol. 23, no. 11, pp. 16048-16061, 2024.
X. Wu, Z. Yang*, and Z. Xu, "Multichannel frequency estimation with constant amplitude via convex structured low-rank approximation," SIAM Journal on Matrix Analysis and Applications, vol. 45, no. 3, pp. 1643–1668, 2024.
X. Wu, Z. Yang*, Z. Wei, and Z. Xu, "Direction-of-arrival estimation for constant modulus signals using a structured matrix recovery technique," IEEE Transactions on Wireless Communications, vol. 23, no. 4, pp. 3117–3130, 2024.
X. Wu, Z. Yang*, and Z. Xu, "Multichannel frequency estimation in challenging scenarios via structured matrix embedding and recovery (StruMER)," IEEE Transactions on Signal Processing, vol. 71, 3242–3256, 2023.
Y. Chu, Z. Wei, and Z. Yang*, "New reweighted atomic norm minimization approach for line spectral estimation," Signal Processing, vol. 206, pp. 108897, May 2023.
X. Wu, Z. Yang*, P. Stoica, and Z. Xu, "Maximum likelihood line spectral estimation in the signal domain: a rank-constrained structured matrix recovery approach," IEEE Transactions on Signal Processing, vol. 70, pp. 4156–4169, 2022.