职称:教授,博士生导师 | ||||||
办公室:江宁无线谷A5-402室 | ||||||
办公电话:025-84980409 | ||||||
Email:yili_xia@seu.edu.cn | ||||||
学习经历: | ||||||
2002年9月-2006年6月 学士 2006年9月-2007年8月英国帝国理工学院电气与电子工程系硕士 2007年9月-2011年6月英国帝国理工学院电气与电子工程系博士 | ||||||
工作经历: | ||||||
2011年9月-2012年12月英国帝国理工学院电气与电子工程系博士后 2013年1月-2019年4月 副教授 2019年5月-至今 教授 | ||||||
教授课程: | ||||||
盲信号处理导论(研讨)-- 本科三年级 | ||||||
研究方向: | ||||||
统计信号处理、多维信号处理、自适应信号处理、人工智能、大数据分析、信号处理在无线通信及电力中的应用 | ||||||
获奖情况: | ||||||
1、2019年IEEE信号处理年会(ICASSP’19)教育创新奖 2、2018年东南大学至善青年学者 3、2014年江苏省双创人才 4、2010年国际神经网络研讨会(ISNN’10) 最优论文奖 | ||||||
论文著作: | ||||||
已发表学术论文80余篇。担任国际权威SCI期刊IEEE Transactions on Signal Processing Associate Editor副编辑。 SCI期刊论文: [1] Y. Xia, B. Zhang, W. Pei, and D. P. Mandic, “Bidimensional multivariate empirical mode decomposition with applications in multi-scale image fusion,” IEEE ACCESS, vol.7, pp. 114261-114270, 2019. [2] M. Xiang, Y. Xia, and D. P. Mandic, “ Complementary cost functions for complex and quaternion widely linear estimation,” IEEE Signal Processing Letters, vol. 26, no. 11, 2019. [3] Y. Xia, S. Tao, Z. Li, M. Xiang, W. Pei, and D. P. Mandic, “Full mean square performance bounds on quaternion estimators for improper data,” IEEE Transactions on Signal Processing, vol. 67, no. 15, pp. 4093-4106, 2019. [4] X. Zhang, Y. Xia, C. Li, L. Yang, and D. P. Mandic, “Analysis of the unconstrained frequency-domain block LMS for second-order noncircular inputs” IEEE Transactions on Signal Processing, vol. 67, no. 15, pp. 3970-3984, 2019. [5] S. Kanna, A. Moniri, Y. Xia, A. G. Constantinides, and D. P. Mandic, “A data analytics perspective of power grid analysis-Part 2: Teaching old power systems new tricks,” IEEE Signal Processing Magazine, vol. 36, no. 3, pp. 110-117, 2019. [6] D. P. Mandic, S. Kanna, Y. Xia, A. Moniri, A. Junyent-Ferre, and A. G. Constantinides, “A data analytics perspective of power grid analysis-Part 1: The Clarke and related transforms,” IEEE Signal Processing Magazine, vol. 36, no. 2, pp. 110-116, 2019. [7] H. Cheng, Y. Xia, Y. Huang, L. Yang, and D. P. Mandic, “Joint channel estimation and Tx/Rx I/Q imbalance compensation for GFDM systems,” IEEE Transactions on Wireless Communications, vol. 18, no. 2, pp. 1304-1317, 2019. [8] W. Deng, Z. Li, Y. Xia, K. Wang, and W. Pei, “A widely linear MMSE anti-collision method for multi-antenna RFID readers,” IEEE Communications Letters, vol. 23, no. 4, pp. 644-647, 2019. [9] D. Pei and Y. Xia, “Robust power system frequency estimation based on a sliding window approach,” Mathematical Problems in Engineering, vol. 2019, pp. 1-10, 2019. [10] Z. Li, Y. Xia, W. Pei, and D. P. Mandic, “A cost-effective nonlinear self-interference canceller in full-duplex direct-conversion transceivers,” Signal Processing, vol. 158, pp. 4-14, 2019. [11] Z. Li, Y. Xia, Q. Wang, W. Pei and J. Hao, “A novel four-point model based unit-norm constrained least squares methods for single-tone frequency estimation,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E102-A, no. 2, pp. 404-414, 2019. [12] G. L. Nefabas, H. Zhao, and Y. Xia, “ Robust frequency estimation of unbalanced power system using a phase angle error based least mean kurtosis algorithm,” International Journal of Electrical Power and Energy Systems, vol. 110, pp. 795-808, 2019. [13] Y. Xia and D. P. Mandic, “ Augmented performance bounds on strictly linear and widely linear estimators with complex data,” IEEE Transactions on Signal Processing, vol. 66, no. 2, 2018. [14] Z. Li, Y. Xia, W. Pei, K. Wang, and D. P. Mandic, “An augmented nonlinear LMS for digital self-interference cancellation in full-duplex direct conversion transceivers,” IEEE Transactions on Signal Processing, vol. 66, no. 15, pp. 4065-4078, 2018. [15] H. Cheng, Y. Xia, Y. Huang, L. Yang, and D. P. Mandic, “A normalized complex LMS based blind I/Q imbalance compensator for GFDM receivers and its full second-order performance analysis,” IEEE Transactions on Signal Processing, vol. 66, no. 17, pp. 4701-4712, 2018. [16] Y. Xia, S. Kanna, and D. P. Mandic, “Maximum likelihood parameter estimation of unbalanced three-phase power signals,” IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 3, pp. 569-581, 2018. [17] Y. Xia, S. C. Douglas, and D. P. Mandic, “ Performance analysis of the deficient length augmented CLMS algorithm for second order noncircular complex signals,” Signal Processing, vol. 144, pp. 214-225, 2018. [18] Y. Xia, S. C. Douglas, and D. P. Mandic, “A perspective on CLMS as a deficient length augmented CLMS: Dealing with second-order noncircularity,” Signal Processing, vol. 149, pp. 236-245, 2018. [19] M. Xiang, S. Enshaeifar, A. E. Stott, C. Cheong-Took, Y. Xia, S. Kanna, and D. P. Mandic, “Simultaneous diagonalization of the covariance and complementary covariance matrices in quaternion widely linear signal processing,” Signal Processing, vol. 148, pp. 193-204, 2018. [20] K. Wang, J. Ding, Y. Xia, X. Liu, J. Hao and W. Pei, “Two high accuracy frequency estimation algorithms based on new autocorrelation-like function for noncircular/sinusoid signal,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E101-A, no. 7, pp. 1065-1073, 2018. [21] Y. Xia and D. P. Mandic, “A full mean square analysis of CLMS for second order noncircular inputs,” IEEE Transactions on Signal Processing, vol. 65, no. 21, pp. 5578-5590, 2017. [22] Y. Xia and D. P. Mandic, “Complementary mean square analysis of augmented CLMS for second-order noncircular Gaussian signals,” IEEE Signal Processing Letters, vol. 24, no. 9, pp. 1413-1417, 2017. [23] Y. Xia, Y. He, K. Wang, W. Pei, Z. Blazic, and D. P. Mandic, “A complex least squares enhanced smart DFT technique for power system frequency estimation,” IEEE Transactions on Power Delivery, vol. 32, no. 3, pp. 1270-1278, 2017. [24] Z. Li, Y. Xia, W. Pei, Y. Huang, and D. P. Mandic, “Noncircular measurement and mitigation of I/Q imbalance for OFDM-based WLAN transmitters,” IEEE Transactions on Instrumentation and Measurement, vol. 66, no. 3, pp. 383-393, 2017. [25] D. Xu, Y. Xia, and D. P. Mandic, “Optimization in quaternion dynamic systems: Gradient, Hessian, and learning algorithms,” IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 2, pp. 249-261, 2016. [26] J. Hao, W. Pei, K. Wang, Y. Xia, and C. Pu, “Iterative optimal design for fast filter bank with low complexity,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E99-A, no. 2, pp. 638-642, 2016. [27] J. Hao, K. Wang, W. Pei, and Y. Xia, “Baseband signal processing of digital phosphor technology with high accuracy,” IEICE Electronics Express, vol. 13, no. 2, pp. 1-7, 2016. [28] J. Hao, W. Pei, K. Wang, and Y. Xia, “ Two-stage iterative design for fast filter bank with low complexity,” Electronics Letters, vol. 52, no. 4, pp. 287-289, 2016. [29] Y. Xia, C. Jahanchahi, and D. P. Mandic, “Quaternion-valued echo state networks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 4, pp. 663-673, 2015. [30] S. Kanna, D. H. Dini, Y. Xia, S. Y. Hui, and D. P. Mandic, “Distributed widely linear Kalman filtering for frequency estimation in power networks,” IEEE Transactions on Signal and Information Processing over Networks, vol. 1, no. 1, pp. 45-57, 2015. [31] Y. Xia, Z. Blazic, and D. P. Mandic, “Complex-valued least squares frequency estimation for unbalanced power systems,” IEEE Transactions on Instrumentation and Measurement, vol. 64, no. 3, pp. 638-648, 2015. [32] Y. Xia, C. Jahanchahi, T. Nitta, and D. P. Mandic, “Performance bounds of quaternion estimators,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 12, pp. 3287-3292, 2015. [33] J. Hao, W. Pei, Y. Xia, and K. Wang, “Adaptive pulse signal shaping of tag response signal for RFID tag test system,” Electronics Letters, vol. 50, no. 17, pp. 1182-1184, 2014. [34] Y. Xia and D. P. Mandic, “A widely linear least mean phase algorithm for adaptive frequency estimation of unbalanced power systems,” International Journal of Electrical Power and Energy Systems, vol. 54, pp. 367-375, 2014. [35] Y. Xia and D. P. Mandic, “Augmented MVDR spectrum-based frequency estimation for unbalanced power systems,” IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 7, pp. 1917-1926, 2013. [36] Y. Xia, S. C. Douglas, and D. P. Mandic, “Adaptive frequency estimation in smart grid applications: Exploiting noncircularity and widely linear adaptive estimators,” IEEE Signal Processing Magazine, vol. 29, no. 5, pp. 44-54, 2012. [37] L. Li, Y. Xia, B. Jelfs, J. Cao, and D. P. Mandic, “Modelling of brain consciousness based on collaborative adaptive filters,” Neurocomputing, vol. 76, no. 1, pp. 36-43, 2012. [38] Y. Xia and D. P. Mandic, “Widely linear frequency estimation of unbalanced three-phase power systems,” IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 1, pp. 74-83, 2012. [39] Y. Xia, D. P. Mandic, and A. H. Sayed, “An adaptive diffusion augmented CLMS algorithm for distributed filtering of noncircular complex signals,” IEEE Signal Processing Letters, vol. 18, no. 11, pp. 659-662, 2011. [40] Y. Xia, B. Jelfs, M. M. Van Hull, J. C. Principe, and D. P. Mandic, “An augmented echo state network for nonlinear adaptive filtering of complex noncircular signals,” IEEE Transactions on Neural Networks, vol. 22, no. 1, pp. 74-83, 2011. [41] Y. Xia, C. Cheong-Took, and D. P. Mandic, “An augmented affine projection algorithm for the filtering of complex noncircular signals,” Signal Processing, vol. 90, no. 6, pp. 1788-1799, 2010.
图书专著: [1] Adaptive Learning Methods for Nonlinear System Modelling. Chapter 12-Echo State Networks for Multidimensional Data: Exploiting Noncircularity and Widely Linear Models, Y. Xia, M. Xiang, Z. Li, and D. P. Mandic, Elsevier, 2018. [2] Cooperative and Graph Signal Processing. Chapter 28-Smart Grids: Diffusion Augmented Extended Kalman Filtering for Adaptive Frequency Estimation in Distributed Power Systems, Y. Xia, S. Kanna, and D. P. Mandic, Elsevier, 2018.
| ||||||
科研项目: | ||||||
项目名称 | 项目类别 | 项目时间 | 工作类别 | 项目金额 | ||
复数域自适应估计算法的完备性能分析方法及其在宽带多载波I/Q不平衡补偿中的应用 | 东南大学优秀教师科学研究资助 | 2019.01-2021.12 | 应用研究 | 20万 | ||
基于非圆复数的自适应滤波算法完备均方性能分析 | 国家自然科学基金项目 | 2018.01-2021.12 | 基础研究 | 60万 | ||
基于电压离散傅立叶联合功率谱的非平衡电力系统频率估计技术研究 | 国家自然科学基金项目 | 2015.01-2017.12 | 基础研究 | 25万 | ||
基于电压联合周期图最大化的非平衡电力系统频率估计技术研究 | 江苏省自然科学基金项目 | 2014.07-2017.06 | 基础研究 | 20万 | ||
高精度频率估计算法研究 | 教育部基金项目 | 2015.07-2017.06 | 基础研究 | 3万 | ||
输变电工程数据管理关键技术研究 | 企事业委托项目 | 2017.01-2019.12 | 应用研究 | 50万 | ||
基于大数据的配电网中短期电压越限预警及优化治理关键技术研究 | 企事业委托项目 | 2017.01-2019.12 | 应用研究 | 30万 | ||
专利: | ||||||
专利号 | 专利名称 | 专利类型 | ||||
ZL201510098640.5 | 一种发射机中IQ不平衡的补偿方法和装置 | 发明专利 | ||||
ZL201610159351.6 | 基于虚拟仪器的RFID标签空中接口协议符合性自动化测试方法 | 发明专利 | ||||
ZL201610227715.X | 基于虚拟仪器的RFID标签一致性测试系统 | 发明专利 | ||||
ZL201610137200.0 | 适用于MIMO-OFDM系统的IQ不平衡和信道联合估计方法 | 发明专利 | ||||
ZL201610145766.8 | OFDM-WLAN射频测试系统的IQ不平衡估计与补偿方法 | 发明专利 | ||||
ZL201610147118.6 | 一种适用于MIMO-OFDM系统的载波频偏估计方法 | 发明专利 | ||||
ZL201611223964.8 | 一种非平衡电力系统频率估计的方法 | 发明专利 | ||||
ZL201610225065.5 | 一种基于802.11ac射频一致性测试系统接收机的检测方法 | 发明专利 | ||||
ZL201610150465.4 | MIMO-OFDM WLAN系统的同步方法及系统 | 发明专利 | ||||
ZL201710279284.6 | 基于改进的SmartDFT算法的非平衡系统频率估计算法 | 发明专利 | ||||
ZL201711326494.2 | 一种零中频全双工收发机的数字自干扰消除方法 | 发明专利 | ||||
ZL201710126644.9 | 一种基于外插脉冲响应法实现的快速滤波器组的非均匀数字信道化方法 | 发明专利 | ||||
US9995774B2 | Frequency estimation | 美国发明专利 |