BROWSE

AUTHOR PROFILE

Browsing by Author Xiao, L.

Jump to: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
or enter first few letters:  
Showing results 1 to 2 of 2
  • BB

  • Impulsive Noise Recovery and Elimination: A Sparse Machine Learning Based Approach

    • Authors: Liu, S.;  Advisor: -;  Participants: Xiao, L.; Huang, L.; Wang, X. (2019)

  • The performance of orthogonal frequency division multiplexing (OFDM) based wireless vehicular communication systems is faced with the great challenge of impulsive noise (IN), which could limit the application of OFDM in ultra-reliable lowlatency communication scenarios. In this paper, the challenge of IN elimination for OFDM-based wireless systems is efficiently overcome by the proposed sparse learning algorithms and probabilistic framework inspired by the emerging machine learning theories. For the first time, the sparse machine learning theory is introduced to IN recovery and elimination. Exploiting the measurement vector of IN observed from the reserved null sub-carriers as the inp...
  • BB

  • Molecular epidemiologic tools for waterborne pathogens Cryptosporidium spp. and Giardia duodenalis

    • Authors: Feng, Y.; Xiao, L.;  Advisor: -;  Participants: - (2017)

  • Molecular diagnostic tools have played an important role in improving our understanding of the transmission of Cryptosporidium spp. and Giardia duodenalis, which are two of the most important waterborne parasites in industrialized nations. With the recent development in next generation sequencing techniques, whole genome sequencing and comparative genomic analysis are increasingly used in characterizing Cryptosporidium spp. and G. duodenalis. The use of these tools in epidemiologic studies has identified significant differences in the transmission of Cryptosporidium spp. in humans between developing countries and industrialized nations, especially the role of zoonotic transmission in ...