叶文彬

yewenbin@szu.edu.cn (+86) 15019415279

教育背景:

新加坡南洋理工大学, 新加坡，博士研究生，电路与系统  2009 .08–2014.07

四川大学, 四川, 成都，学士，微电子学 2005.09–2009.06

工作经历:

我校，副教授 2015.7–至今

研究方向：

•数字 FIR 滤波器设计与VLSI硬件实现；

•低功耗低复杂度的人工智能芯片设计与优化

•基于深度神经网络的雷达人体活动识别以及相应的硬件实现

南洋理工大学博士后2014.7–2015.7

•非均匀采样信号的处理, 主要负责基于非均匀采样信号的系统设计和优化

近几年主持的科研项目

• 深圳市孔雀人才创新创业项目，批准号：KQJSCX20180328093500762。2018.03-2021.03，80万元，低功耗的数字有限冲击响应滤波芯片研制

• 国家自然科学基金项目，批准号：61601301，2016.01-2019.12，20万元，基于子项共享技术的低功耗FIR滤波器设计与实现研究

• 广东省教育厅青年计划项目，批准号：2015KQNCX142，2016.01-2016.12，5万元，低功耗FIR滤波器设计

• 深圳市基础研究项目，批准号：JCYJ20160308094919279，2016.06-2018.06，29万元，基于子项共享技术的低功耗FIR滤波器设计理论与方法研究

• 我校启动项目，批准号：2016020，2016.06-2018.06，6万元，基于全加器级的低复杂度数字FIR滤波器设计研究

• 我校高端人才经费，2017.01-2019.12，300万元，低功耗数字FIR滤波器设计与集成电路实现

代表论文

•Ye Wen Bin*, H. Chen, Human Activity Classification Based on Micro-Doppler Signatures by Multiscale and Multitask Fourier Convolutional Neural Network, IEEE Sensors Journal ,2020,20 (10), 5473-5479.

•J Zhu, H Chen,Ye Wen Bin* A Hybrid CNN–LSTM Network for the Classification of Human Activities Based on Micro-Doppler Radar, IEEE Access,2020, 8, 24713-24720.

•W Chen, M Huang,Ye Wen Bin*, X Lou, Cascaded Form Sparse FIR Filter Design, IEEE Transactions on Circuits and Systems I: Regular Papers 67 (5), 1692-1703.

•H. Chen,Ye Wen Bin*,“Classification of Human Activity based on Radar signal Using One Dimensional Convolutional Neural Network”, IEEE GeoScience and Remote Sensing Letters, 2019, vol 17, pp. 1-10.

•Ye Wen Bin，H. Chen, B. Li,“Using an End-to-End Convolutional network On Radar Signal for human Activity Classification”, IEEE Sensors Journal, 2019, Vol 19(24) pp. 12244-12245.

•X. Zeng, Y. Luo, X. Zhao,Ye Wen Bin*,“An end-to-end fully convolutional neural network for division of focal plane sensors to reconstruct S0, DoLP and AoP”, Optics express, 2019, 27(6),8566-8577.

•Ye Wen Bin，S. Li, X. J. Zhao, A. Abubakar, A. Bermak,“A K times singular value decomposition based image denoising algorithm for DoFP polarization image sensors with Gaussian noise”, IEEE Sensors Journal, 2018, Vol 18(15) pp. 6138-6144.

•P. Peng, X. J. Zhao, X. F., Pan，Ye Wen Bin*,“Gas Classification Using Deep Convolutional Neural Net-works,”Sensors, 2018, pp. 1-11.

•X. Lou,P.Meher, Y. Yu,Ye Wen Bin*, ”Novel Structure for Area-Efficient Implementation of FIR Filter,” IEEE Transactions on Circuits and Systems II: Express Briefs , 2016, vol.PP, no.99, pp.1-1.

•Ye Wen Bin，Yu, Ya Jun，Two-step optimization approach for the design of multiplierless linear-phase FIR filters，IEEE Transactions on Circuits and Systems I: Regular Papers，2015，62（5）：1279-1287.

•Ye Wen Bin，Yu, Ya Jun，Bit-level multiplierless FIR filter optimization incorporating sparse filter tech-nique，IEEE Transactions on C ircuits and Systems I: Regular Papers，2014，61（11）：3206-3215.

•Ye Wen Bin，Ya Jun Yu，Greedy Algorithm for the Design of Linear-Phase FIR Filters with Sparse Co-efficients，Circuits, Systems, and Signal Processing, 2016.

•Ye Wen Bin，Yu, Ya Jun，Single-Stage and Cascade Design of High Order Multiplierless Linear Phase FIR Filters Using Genetic Algorithm，IEEE Transactions on Circuits and Systems I-Regular Papers，2013，60（11）：2987-2997.

•Ye Wen Bin，Yu, Ya Jun，An efficient FIR filtering technique for processing non-uniformly sampled signal，IEEE International Conference on Digital Signal Processing, DSP 2015，182-185.

•Ye Wen Bin，Lou, Xin，Yu, Ya Jun，Design of high-speed multiplierless linear-phase FIR filters，IEEE International Symposium on Circuits and Systems, ISCAS 2015，2964-2967.