System Identification - 2016 Spring

Reading Materials

No. 1: Adaptive Sparse System Identification Using Wavelets [PDF]
K. Ho and S. Blunt, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II, 2002

No. 2: 郑贺亮、彭昆福
System Identification Using Binary Sensors [PDF]
L. Wang, J. Zhang, and G. Yin, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2003

No. 3: 陈正勇、侯松
Application of Structured Total Least Squares for System Identification and Model Reduction [PDF]
I. Markovsky, J. Willems, S. Huffel, B. De Moor, and R. Pintelon, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2005

No. 4: 唐律邦、尹志鹏
Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling [PDF]
H. Zhu, G. Leus, and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2011

No. 5: 杨博远、席彦新
Analyzing the Responses of a Thermally Modulated Gas Sensor Using a Linear System Identification Technique for Gas Diagnosis [PDF]
F. Hossein-Babaei and S. Hosseini-Golgoo, IEEE SENSORS JOURNAL, 2008

No. 6: 赵振怡、陈树涛
Distributed LMS for Consensus-Based In-Network Adaptive Processing [PDF]
I. Schizas, G. Mateos, and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009

No. 7: 阳雨杰、袁启锋
Distributed Recursive Least-Squares: Stability and Performance Analysis [PDF]
G. Mateos and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012

No. 8: 石翔熹、郑可成
Online Adaptive Estimation of Sparse Signals: Where RLS Meets the L1-Norm [PDF]
D. Angelosante, J. Bazerque, and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2010

No. 9: 高子轩、熊思齐
Distributed Sparse Linear Regression [PDF]
G. Mateos, J. Bazerque, and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2010

No. 10: 刘元煌、杨威
Power System Nonlinear State Estimation Using Distributed Semidefinite Programming [PDF]
H. Zhu and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014

No. 11: 赵宇斐、李展鹏
A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares [PDF]
G. Raskutti and M. Mahoney, ARXIV MANUSCRIPT, 2014

No. 12: 赵子岳、王鸿展
Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares [PDF]
M. Pilanci and M. Wainwright, ARXIV MANUSCRIPT, 2014

No. 13: 张津诚、韩克宇
Faster Ridge Regression via the Subsampled Randomized Hadamard Transform [PDF]
Y. Lu, P. Dhillon, D. Foster, and L. Ungar, NIPS, 2013

No. 14: 管玺权、李龙龙
Sampling Algorithms for L2 Regression and Applications [PDF]
P. Drineas, M. Mahoney, and S. Muthukrishnan, SODA, 2005

No. 15: 耿洋洋、江金健
Online Censoring for Large-Scale Regressions with Application to Streaming Big Data [PDF]
D. Berberidis, V. Kekatos, and G. Giannakis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2016

Requirements

1. 每位同学的报告时间为8-10分钟。

2. 每份ppt的页数不超过总报告时间(分钟)×1.2。

3. 务必讲清楚:所研究的问题、相关的研究工作、解决问题的思路、算法的效果、未来的研究方向。