研究领域

信号与信息处理；小波理论；时频分析；计算与应用调和分析；非线性分析的理论与方法

论文与著作

代表性期刊论文   (“*”为通信作者)

[1] Li Wenting, François Auger, Zhuosheng Zhang*, Zhu Xiangxiang, Newton time-extractin  wavelet transform: an  effective tool for characterizing interferingsignals with fast varying group delay and theoretical analysis, Signal Processing, 2023, 209:109017, 1-18.  

[2] Li Wenting, Zhuosheng Zhang*, François Auger, Zhu Xiangxiang, Time-extracting wavelet transform forcharacterizing impulsive-like signals and theoretical analysis, Circuits, Systems, and Signal Processing, 2023, 42(1):1-29.

[3] Li Wenting, Zhuosheng Zhang*, François Auger, Zhu Xiangxiang, Theoretical analysis of time-reassigned synchrosqueezingwavelet transform, Applied Mathematics Letters, 2022, 132:108141, 1-7. 

[4] Li Wenting, François Auger, Zhuosheng Zhang*, Zhu Xiangxiang, Self-matched extracting wavelet transform and signal reconstruction, Digital Signal Processing, 2022, 128:103602, 1-23.  

[5] Li Bei, Zhuosheng Zhang*, Zhu Xiangxiang, Multitaper adaptive short-time Fourier transform with chirpmodulatedGaussian window and multitaper extracting transform,  Digital Signal Processing, 2022, 126:103472,1-17.  

[6] Xiangxiang Zhu, Zhuosheng Zhang*, Jinghuai Gao,Three-dimension extracting transform, Signal Processing, 2021, 179:107830, 1-15. 

[7]Bei Li, Zhuosheng Zhang*, Xiangxiang Zhu, AdaptiveS-transform with chirp-modulated window and its synchroextracting transform, Circuits Systems, and Signal Process, 2021, 40(11): 56545681, 1-29. 

[8]Xiangxiang Zhu, Haizhao Yang, Zhuosheng Zhang*,Jinghuai Gaoc, NaihaoLiu, Frequency-chirpratereassignment, Digital Signal Processing, 2020, 104:102783,1-11. 

[9] Xiangxiang Zhu, Zhuosheng Zhang*, Hanqiu Zhang, Jinghuai Gao,Bei Li, Generalized ridge reconstruction approaches toward more accurate signal estimate, Circuits, Systems, and Signal Processing, 2020, 39:2574-2599. 

[10] Xiangxiang Zhu, Zhuosheng Zhang*, Jinghuai Gao, Wenting Li, Two robust approaches tomulticomponent signal reconstruction from STFT ridges, Mechanical Systems and Signal Processing, 2019，115: 720-735. 

[11] Xiangxiang Zhu, Zhuosheng Zhang*, Zhen Li, Jinghuai Gao, Xin Huang, Guangrui Wen, Multiplesqueezes from adaptive chirplet transform, Signal Processing, 2019, 163: 26-40.  

[12] Xiangxiang Zhu, Zhuosheng Zhang*, Jinghuai Gao,Bei Li, Zhen Li, Xin Huang, Guangrui Wen, Synchroextractingchirplet transform for accurate IF estimate and perfect signal reconstruction, Digital Signal Processing, 2019, 93: 172-186.

[13] Xiangxiang Zhu, Zhuosheng Zhang*, Wenting Li and Bei Li, High-order ridge reconstruction for more accurate signalestimate from time-frequency representations, Electronics Letters, 2019, 55(13): 763-765.

[14] Xiangxiang Zhu, Jicheng Li and Zhuosheng Zhang*, Nonnegative matrix factorization with band constraint, Journal of Computational Mathematics, 2018, 36(6): 761-775.  

[15] Xiangxiang Zhu, Zhuosheng Zhang*, Improvedself-paced learning framework for nonnegative matrix factorization, Pattern Recognition Letters, 2017, 97: 1-7. 

[16] Zhuosheng Zhang*, Yongchao Yu, Shumin Zhao, Iterative hard thresholdingbased on randomized Kaczmarz method, Circuits, Systems, and Signal Processing, 2015, 34(6): 2065-2075.  

[17] Zhuosheng Zhang*, Haixing Lv, Qingbao Zhou, Hanqiu Zhang, Reconstructing sparse signals from dyadicwavelet transform modulus maxima, Circuits, Systems, and Signal Processing, 2014, 33:2667-2674. 

[18] Zhuosheng Zhang*, Cunjie Cui, and Kunpeng Liu, Iterative hard-threshold algorithm with momentum, IET, Electronics Letters, 2011, 47(4): 257~259. 

[19] Zhuosheng Zhang*, Guizhong Liu, and Feng Liu, A new iterative algorithm for reconstructing asignal from its dyadic wavelet transform modulus maxima, Science in China, Series F, 2003, 46(6): 420~430.

[20] Zhuosheng Zhang*, Guizhong Liu, and Feng Liu, Construction of a new adaptive wavelet network and its learning algorithm,Science in China, Series F, 2001, 44 (2): 93~103.

[21] 张茁生*，刘贵忠，刘峰，一种新的信号二进小波变换模极大值重构信号的迭代算法, 中国科学(E辑)，2003, 33 (6):545-553.

[22] 张茁生*，刘贵忠，刘峰，一种新的自适应小波网络的构造及其学习算法，中国科学(E辑)，2001, 31 (2): 172-181.

[23] 张茁生*，刘贵忠，刘峰，基于自适应投影学习算法的径向基函数网络设计及应用，电子学报，2000，28 (9):120-123.

[24] 张茁生*，刘贵忠 ，张宗平，基于小波框架的自适应径向基函数网络，自动化学报，2002，28 (2):229-237.

[25] 徐宗本，张茁生*，空间的另一组特征不等式，数学学报，1994，37 (4):433-439.

[26] 张茁生*，徐宗本，一致平滑Banach 空间的特征不等式，工程数学学报，1989, 6 (3): 97-101.

授权发明专利

[1] 高静怀，王前，张茁生，基于二阶同步挤压小波变换的地震资料时频分析方法，2018-10-30，中国，ZL201710543582.1.

[2] 高静怀，刘乃豪，姜秀娣，张茁生，杨涛，王前，王平，吕奇，基于高分辨率时频分析和一致性度量的非均质性刻画方法，2018-10-30，中国，ZL201710543985.6.

著  作

• 徐宗本，张茁生，信息工程概论，科学出版社，2011. （“十一五”国家级规划教材）

荣誉与奖励

• 徐宗本，蒋耀林，张茁生，Banach空间特征化不等式数量定律及应用，陕西省科学技术进步奖，二等奖，1997.