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2016.03.31 学术报告: Noise Enhanced Signal Processing: theory and applications

时间:2016-03-29  来源:文本大小:【 |  | 】  【打印

  报告题目: Noise Enhanced Signal Processing: theory and applications

  报告人:陈豪

  报告时间:2016年03月31日 上午9点30分

  地点:3号楼3楼光学影像分析与学习中心(OPTIMAL)会议室

  报告人简介:

  Dr. Hao Chen received the B.S. and M.S. Degree in electrical engineering from University of Science and Technology of China in 1999 and 2002, respectively, and Ph.D. degree in electrical engineering from Syracuse University, Syracuse, NY, USA in 2007.

  He is currently an assistant Professor with the Department of Electrical and Computer Engineering, Boise State University, Boise, ID, USA. His research interests include statistical signal and image processing, and communications.

  报告摘要:

  Noise enhanced signal processing (NESP) is a phenomenon in which the performance of some nonlinear signal systems can be enhanced by addition of suitable noise under certain conditions. This counter-intuitive phenomenon has been observed in many fields such as physics, biology and some neuronal systems. The basic idea of performance enhancement by adding noise has been practiced in signal processing for some time, e.g., dithering in quantization and some numerical optimization algorithms such as genetic algorithms and simulated annealing.

  From an engineering point of view, the NESP based approaches have some very appealing advantages. In contrast to the traditional approaches where the existing systems are often replaced with new systems to improve system performance, the NESP based approaches keep the existing systems and improve their performance by changing the inputs either randomly or deterministically. Thus, the NESP based approaches are more cost efficient, i.e., instead of putting in a new system, one may only need to insert a noise generator into the existing systems. NESP based approaches are more flexible: the optimal noise distribution can be tuned easily as the conditions change. It also provides a unique way to improve many fixed and irreplaceable systems such as physiological systems and human sensory systems.

  This talk will introduce the phenomenon of NESP, present some recent results and applications with a discussion on potential new research directions.