24小时热门版块排行榜

返回列表

xixixihehehe

新虫 (初入文坛)

应助: 0 (幼儿园)
金币: 10.5
帖子: 2
在线: 1.8小时
虫号: 1118364
注册: 2010-10-10

[交流] [2011-7-7 @ 成都] IEEE信号处理杰出学人讲座 & 国外博士后、研究生招收

IEEE信号处理杰出学人讲座

SIGNAL PROCESSING DISTINGUISHED LECTURE

地点: 电子科技大学清水河校区，科研楼C-216 （本帖末附有交通信息，供校外同学参考）
讲座人: Rick S. Blum (IEEE Fellow), Lehigh University
日期: 7 月7 日（星期四）

讲座 1
时间: 上午10:30
题目: 传感器网络信号检测：分布式检测、能量有效性、MIMO 雷达
Sensor Networking for Detection: From Distributed Detection to Energy Savings and MIMO Radar

ABSTRACT: The focus of the talk is on sensor networking for signal detection. We give a brief review of distributed signal detection which describes some very early work on sensor networking for signal detection. We discuss the important result that sensor likelihood ratio tests are optimum under independence from sensor to sensor. We discuss the more difficult cases of statistically dependent observations and show that some progress can be made in these cases. Next we describe some new work on energy savings for signal detection that shows traditional approaches can be significantly outperformed by ordering the sensor transmissions to send the most informative data first. Finally we discuss a new paradigm called MIMO radar where widely separated multiple transmitters and receivers are employed using either coherent or noncoherent processing. The noncoherent processing allows diversity gains similar to those obtained in communications. The coherent processing allows very high resolution estimation of the position and velocity of objects of interest.

讲座 2
时间: 下午2:30
题目: 非高斯环境和非正交信号情况下的MIMO 雷达N-P 检测分集增益
MIMO Radar Diversity with Neyman-Pearson Signal Detection: NonGaussian Reflections, Clutter and NonOrthogonal Waveforms

ABSTRACT: The diversity gain of a multiple‐input multiple‐output (MIMO) system adopting the Neyman‐Pearson (NP) criterion is derived for a signal‐present versus signal‐absent scalar hypothesis test statistic and for a vector signalpresent versus signal‐absent hypothesis testing problem. The results are applied to a MIMO radar system with M transmit and N receive antennas, used to detect a target composed of Q random scatterers with possibly non‐Gaussian reflection coefficients in the presence of possibly non‐Gaussian clutter‐plus‐noise. It is found that the diversity gain for the MIMO radar system is dependent on the cumulative distribution function (cdf) of the reflection coefficients while invariant to the cdf of the clutter‐plus‐noise under some reasonable conditions. If the noise‐free received waveforms at each receiver span a space of dimension M’ ≤ M, the largest possible diversity gain is controlled by min (NM’,Q) and the cdf of the magnitude square of a linear transformed version of the reflection coefficient vector. It is shown that properly chosen nonorthogonal waveforms can achieve the same diversity gain as orthogonal waveforms.

BIO: Rick S. Blum received a B.S. in Electrical Engineering from the Pennsylvania State University in 1984 and his M.S. and Ph.D in Electrical Engineering from the University of Pennsylvania in 1987 and 1991.
From 1984 to 1991 he was a member of technical staff at General Electric Aerospace in Valley Forge, Pennsylvania and he graduated from GE’s Advanced Course in Engineering. Since 1991, he has been with the Electrical and Computer Engineering Department at Lehigh University in Bethlehem, Pennsylvania where he is currently a Professor and holds the Robert W. Wieseman Chaired Research Professorship in Electrical Engineering. His research interests include signal processing for communications, sensor networking, radar and sensor processing. He is on the editorial board for the Journal of Advances in Information Fusion of the International Society of Information Fusion. He was an associate editor for IEEE Transactions on Signal Processing and for IEEE Communications Letters. He has edited special issues for IEEE Transactions on Signal Processing, IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He is a member of the SAM Technical Committee (TC) of the IEEE Signal Processing Society. He was a member of the Signal Processing for Communications TC of the IEEE Signal Processing Society and is a member of the Communications Theory TC of the IEEE Communication Society. He was on the awards Committee of the IEEE Communication Society.
Dr. Blum is a Fellow of the IEEE, an IEEE Third Millennium Medal winner, a member of Eta Kappa Nu and Sigma Xi, and holds several patents. He was awarded an ONR Young Investigator Award in 1997 and an NSF Research Initiation Award in 1992. His IEEE Fellow Citation “for scientific contributions to detection, data fusion and signal processing with multiple sensors" acknowledges some early contributions to the field of sensor networking.

======================================================

Postdocs and Graduate Students Opportunities at Lehigh University on Signal Processing for Smart Grid

Looking for outstanding researchers with knowledge (classes and hopefully publications) on signal detection, estimation, and related topics in signal processing of random signals as it applies to power systems and smart grid systems. Future emphasis on research related to graph models of power networks, distributed processing and control, relation to financial markets and real‐time pricing information. Current research on detecting malicious attacks and failures (see 2011 ICASSP paper and 2011 CISS paper).

If interested, please talk to me after my presentation at UESTC. I am looking for postdocs and students. Also send cover letter, vita and 3 references to:

Prof. Rick S. Blum
Electrical and Computer Engineering Dept.
Lehigh University
19 Memorial Drive West
Bethlehem PA 18015‐3084

or rblum@lehigh.edu

‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
Rick S. Blum
Robert W. Wieseman Chair in Electrical Engineering
Professor of Electrical and Computer Engineering
Electrical and Computer Engineering Dept.
Lehigh University
19 Memorial Drive West
Bethlehem, PA 18015‐3084
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
Signal Processing and Communications Email: rblum@eecs.lehigh.edu
Research Group in the EECS Dept.
at
Lehigh University (610) 758‐3459 Fax: (610) 758‐6279
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐

================================================

附：

交通 [转自“百度百科”：https://baike.baidu.com/view/1152822.html?fromTaglist]

一、交通路线

　　双流机场：
　　乘124路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。

　　火车北站：
　　1、乘69路或83路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。
　　2、乘36路直达九里堤公交站，转乘116路到电子科大清水河校区。
　　3、乘54路至蜀汉路，转乘96路到电子科大清水河校区。
　　4、乘坐116路至犀浦动车站，转成灌动车到达火车北站（动车运行时间仅仅8分钟~）

　　火车南站：
　　乘111路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。
　　茶店子汽车站：
　　1、步行至成灌立交桥南站，乘405路公交车到金沙汽车站，转乘96路公交车到电子科大清水
　　河站。
　　2、步行至蜀汉西路站，乘96路公交车到电子科大清水河站。

　　昭觉寺汽车站：
　　乘69路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。
　　五桂桥汽车站：
　　乘81路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。
　　城东客运站：
　　乘77路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。

　　旅游客运中心（新南门汽车站）：
　　1、乘110路公交车到金沙汽车站，转乘96路公交车到电子科大清水河站。
　　2、乘48路到九里堤公交站，转乘116路到电子科大清水河校区。

　　沙河校区：
　　1、步行至府青路一环路立交桥站乘7路到黄忠小区站，转乘96路到电子科大清水河站。
　　2、步行至石油路口站，乘46、54路至九里堤公交站，转乘116路到电子科大清水河校区。

二、96路、116路收出车时间：

　　1、96路：（起讫点：金沙公交站—电子科大清水河校区）
　　A、金沙公交站出车时间为6：30，收车时间为21：00
　　B、电子科大（清水河）校区出车时间为7：00，收车时间为22：00
　　C、低峰发车间距：19：00钟以后为半小时一班

　　2、116路：（起讫点：九里堤公交站--电子科大清水河校区）
　　A、九里堤公交站出车时间为7：00，收车时间为21：00
　　B、电子科大（清水河）校区出车时间为8：00，收车时间为22：00
　　C、低峰发车间距：19：00以后为半小时一班

[ Last edited by liuyunme on 2011-6-30 at 10:18 ]

回复此楼