Thumbnail
Access Restriction
Subscribed

Author Lu Wang ♦ Kachenoura, A. ♦ Albera, L. ♦ Karfoul, A. ♦ Hua Zhong Shu ♦ Senhadji, L.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Applied physics
Subject Keyword Signal to noise ratio ♦ Signal processing algorithms ♦ Independent component analysis ♦ Blind source separation ♦ Algorithm design and analysis ♦ Conferences
Abstract In many Independent Component Analysis (ICA) problems the mixing matrix is nonnegative while the sources are unconstrained, giving rise to what we call hereafter the Semi-Nonnegative ICA (SN-ICA) problems. Exploiting the nonnegativity property can improve the ICA result. Besides, in some practical applications, the dimension of the observation space must be reduced. However, the classical dimension compression procedure, such as prewhitening, breaks the nonnegativity property of the compressed mixing matrix. In this paper, we introduce a new nonnegative compression method, which guarantees the nonnegativity of the compressed mixing matrix. Simulation results show its fast convergence property. An illustration of Blind Source Separation (BSS) of Magnetic Resonance Spectroscopy (MRS) data confirms the validity of the proposed method.
Description Author affiliation: LIST, Southeast Univ., Nanjing, China (Hua Zhong Shu) || Mech. & Electr. Eng., AL-Baath Univ., Homs, Syria (Karfoul, A.) || INSERM, Rennes, France (Lu Wang; Kachenoura, A.; Albera, L.; Senhadji, L.)
ISBN 9781479914814
ISSN 2151870X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-06-22
Publisher Place Spain
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 1.22 MB
Page Count 4
Starting Page 81
Ending Page 84


Source: IEEE Xplore Digital Library