The Background Noise Estimation in the ELF Electromagnetic Wave Data Using Outer Product Expansion with Non-linear Filter

Akitoshi ITAI  Hiroshi YASUKAWA  Ichi TAKUMI  Masayasu HATA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E97-A   No.11   pp.2114-2120
Publication Date: 2014/11/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E97.A.2114
Type of Manuscript: Special Section PAPER (Special Section on Smart Multimedia & Communication Systems)
background noise reduction,  tensor product expansion,  electromagnetic wave,  signal processing,  

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This paper proposes a background noise estimation method using an outer product expansion with non-linear filters for ELF (extremely low frequency) electromagnetic (EM) waves. We proposed a novel source separation technique that uses a tensor product expansion. This signal separation technique means that the background noise, which is observed in almost all input signals, can be estimated using a tensor product expansion (TPE) where the absolute error (AE) is used as the error function, which is thus known as TPE-AE. TPE-AE has two problems: the first is that the results of TPE-AE are strongly affected by Gaussian random noise, and the second is that the estimated signal varies widely because of the random search. To solve these problems, an outer product expansion based on a modified trimmed mean (MTM) is proposed in this paper. The results show that this novel technique separates the background noise from the signal more accurately than conventional methods.