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Distinguished Talk PowerPoint Presentation
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Distinguished Talk

Distinguished Talk

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Distinguished Talk

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  1. Distinguished Talk On January 26, 2011 National Taiwan University of Science and Technology Professor Wai Ho MOW received his BSc (Electronics) in 1989, MPhil and PhD (Information Engineering) in 1991 and 1993 respectively, all from the Chinese University of Hong Kong (CUHK). In 1994, he was a visiting assistant professor at the Department of Information Engineering, CUHK. He was a visiting scholar at the University of Waterloo, the Munich University of Technology (TUM), the Kyoto University, and the University of California at San Diego in 1995, 1996, 2000, and 2010, respectively. From 1997 to 1999, he was an assistant professor at the Nanyang Technological University, Singapore. He joined the Department of Electrical and Electronic Engineering, Hong Kong University of Science and Technology, in March 2000. He has been an Adjunct Professor of the Southwest Jiaotong University, Chengdu, China from 2003 to 2008. In spite of the relatively short PhD study period, he received the Best PhD Thesis in Engineering Award and the Young Scholar Dissertation Award. He was also the recipient of the Croucher Research Fellowship (HK), the Humboldt Research Fellowship (Germany), the Telecommunications Advancement Research Fellowship (Japan), the Tan Chin Tuan Academic Exchange Fellowship (Singapore), the Wong Kuan Cheng Education Foundation Academic Exchange Award (China), the Foreign Expert Bureau Fellowship (China) and the Royal Academy of Engineering Award for Short Research Exchanges with China and India (UK). His research includes: wireless communications, coding and information theory. Dr. Mow was a past chair of the Hong Kong Chapter of the IEEE Information Theory Society and has been a Senior Member of IEEE since 1999. Prof. Wai Ho Mow, Senior Member of IEEE Dept. of ECE,HKUST Speech: 11:00~12:00 (IB-201) Robust Decoding for Unknown Impulsive Noise Channels In many real-world communication and storage systems, the extent of non-Gaussian impulsive noise (IN) rather than Gaussian noise poses practical limits on the achievable system performance. The decoding of IN-corrupted signals is complicated by the fact that accurate IN statistics are typically unavailable at the receiver. Without exploiting the probability distribution of the impulsive noise, the conventional method is to mark the IN corrupted symbol as erasures before performing an error-and-erasure decoding. The main contribution of this work is to propose a joint erasure marking and decoding approach to the design of a high performance decoding algorithm for signals corrupted by impulsive noise as well as Gaussian noise. In this presentation, a novel decoding metric for a joint erasure marker and decoder (JED) is introduced. Some simple modulation schemes are investigated in detail to demonstrate the sophistication in characterizing the decision regions and analyzing the performance of JED. Next, the optimal joint erasure marking and Viterbi decoder (JEVA) is derived for a convolutionally coded scheme. Our simulation results showed that JEVA performs only marginally worse than the maximum likelihood decoder although unlike the latter, it does not exploit the knowledge of the impulsive noise statistics at all. Finally, a sub-optimal variant of JEVA is devised to allow different complexity-performance tradeoff. Contact information : dtseng@mail.ntust.edu.tw02-27376513 Prof. Der-Feng Tseng