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杨成竹
,创建页面,内容为“{| class="wikitable" style="float:right; margin: -10px 0px 10px 20px; text-align:left" |<center>''' 杨成竹 '''<br><img src=" https://sie.bit.edu.cn/images/2022-0…”
{| class="wikitable" style="float:right; margin: -10px 0px 10px 20px; text-align:left"
|<center>''' 杨成竹 '''<br><img src=" https://sie.bit.edu.cn/images/2022-03/7e67e6f718714e81bb85722c26d24f2e.jpeg " width="180"></center><small>[https://www.bit.edu.cn/ 北京理工大学]
</small>
|}
'''杨成竹''',男, 北京理工大学教授。
==人物简历==
2021.09 至今:任职于 北京理工大学 信息与电子学院
2016.09-2021.06:就读于 清华大学 信息与通信工程专业 博士
2013.09-2016.06:就读于 四川大学 电路与系统专业 硕士
2009.09-2013.06:就读于 四川大学 电子信息工程专业 本科
==研究方向==
[[水声探测]]、[[压缩感知]]、深度学习、[[非凸优化]]
==学术成果==
1. Chengzhu Yang, X. Shen, H. Ma, Y. Gu, and H. C. So, Sparse Recovery Conditions and Performance Bounds for lp-Minimization. IEEE Transactions on Signal Processing, vol. 66, pp. 5014-5028, 2018.
2. Chengzhu Yang, X. Shen, H. Ma, B. Chen, Y. Gu and H. C. So, Weakly Convex Regularized Robust Sparse Recovery Methods with Theoretical Guarantees, IEEE Transactions on Signal Processing, vol. 67, pp. 5046-5061, 2019.
3. Chengzhu Yang, Y. Gu, B. Chen, H. Ma and H. C. So, Learning Proximal Operator Methods for Nonconvex Sparse Recovery with Theoretical Guarantee, IEEE Transactions on Signal Processing, vol. 68, pp. 5244-5259, 2020.
4. Chengzhu Yang, Y. Gu, B. Chen, H. Ma and H. C. So, Two-Dimensional Learned Proximal Gradient Algorithm for Fast Sparse Matrix Recovery, IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 68, pp. 1492-1496, 2021.
5. Q. Liu, Chengzhu Yang, Y. Gu and H. C. So, Robust Sparse Recovery via Weakly Convex Optimization in Impulsive Noise, Signal Processing, vol. 152, pp. 84-89, 2018.
==学术兼职==
IEEE Signal Processing Society会员,IEEE Transactions on Signal Processing、Signal Processing、SCIENCE CHINA Information Sciences审稿人 <ref>[https://www.bit.edu.cn/ 北京理工大学]</ref>
==参考资料==
{{reflist}}
[[Category:教授]]
|<center>''' 杨成竹 '''<br><img src=" https://sie.bit.edu.cn/images/2022-03/7e67e6f718714e81bb85722c26d24f2e.jpeg " width="180"></center><small>[https://www.bit.edu.cn/ 北京理工大学]
</small>
|}
'''杨成竹''',男, 北京理工大学教授。
==人物简历==
2021.09 至今:任职于 北京理工大学 信息与电子学院
2016.09-2021.06:就读于 清华大学 信息与通信工程专业 博士
2013.09-2016.06:就读于 四川大学 电路与系统专业 硕士
2009.09-2013.06:就读于 四川大学 电子信息工程专业 本科
==研究方向==
[[水声探测]]、[[压缩感知]]、深度学习、[[非凸优化]]
==学术成果==
1. Chengzhu Yang, X. Shen, H. Ma, Y. Gu, and H. C. So, Sparse Recovery Conditions and Performance Bounds for lp-Minimization. IEEE Transactions on Signal Processing, vol. 66, pp. 5014-5028, 2018.
2. Chengzhu Yang, X. Shen, H. Ma, B. Chen, Y. Gu and H. C. So, Weakly Convex Regularized Robust Sparse Recovery Methods with Theoretical Guarantees, IEEE Transactions on Signal Processing, vol. 67, pp. 5046-5061, 2019.
3. Chengzhu Yang, Y. Gu, B. Chen, H. Ma and H. C. So, Learning Proximal Operator Methods for Nonconvex Sparse Recovery with Theoretical Guarantee, IEEE Transactions on Signal Processing, vol. 68, pp. 5244-5259, 2020.
4. Chengzhu Yang, Y. Gu, B. Chen, H. Ma and H. C. So, Two-Dimensional Learned Proximal Gradient Algorithm for Fast Sparse Matrix Recovery, IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 68, pp. 1492-1496, 2021.
5. Q. Liu, Chengzhu Yang, Y. Gu and H. C. So, Robust Sparse Recovery via Weakly Convex Optimization in Impulsive Noise, Signal Processing, vol. 152, pp. 84-89, 2018.
==学术兼职==
IEEE Signal Processing Society会员,IEEE Transactions on Signal Processing、Signal Processing、SCIENCE CHINA Information Sciences审稿人 <ref>[https://www.bit.edu.cn/ 北京理工大学]</ref>
==参考资料==
{{reflist}}
[[Category:教授]]