Bin Shen
Robust Nonnegative Matrix Factorization via $L_1$ Norm Regularization.
Thu, 04/12/2012 - 15:01 — SomNambulAuthors: Bin Shen, Luo Si, Rongrong Ji, Baodi Liu
Subjects: Learning
AbstractNonnegative Matrix Factorization (NMF) is a widely used technique in many
applications such as face recognition, motion segmentation, etc. It
approximates the nonnegative data in an original high dimensional space with a
linear representation in a low dimensional space by using the product of two
nonnegative matrices. In many applications data are often partially corrupted
with large additive noise. When the positions of noise are known, some existing
variants of NMF can be applied by treating these corrupted entries as missing
values.- Read more
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A Study of Medium Access Control Protocols for Wireless Body Area Networks.
Fri, 04/23/2010 - 15:01 — SomNambulAuthors: Sana Ullah, Kyung Sup Kwak, Pervez Khan, Shahnaz Saleem, Bin Shen, S.M. Riazul Islam
Subjects: Networking and Internet Architecture
AbstractThe seamless integration of low-power, miniaturised, invasive/non-invasive
lightweight sensor nodes have contributed to the development of a proactive and
unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health
monitoring of a patient without any constraint on his/her normal dailylife
activities. This monitoring requires low-power operation of
invasive/non-invasive sensor nodes. In other words, a power-efficient Medium
Access Control (MAC) protocol is required to satisfy the stringent WBAN
requirements, including low-power consumption.
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