Global Noise Estimation Based on Tensor Product Expansion with Absolute Error

Akitoshi ITAI  Hiroshi YASUKAWA  Ichi TAKUMI  Masayasu HATA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E90-A   No.4   pp.778-783
Publication Date: 2007/04/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e90-a.4.778
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Selected Papers from the 19th Workshop on Circuits and Systems in Karuizawa)
Category: 
Keyword: 
global noise reduction,  tensor product expansion,  absolute error,  electromagnetic wave,  signal processing,  

Full Text: PDF>>
Buy this Article




Summary: 
This paper proposes a novel signal estimation method that uses a tensor product expansion. When a bivariable function, which is expressed by two-dimensional matrix, is subjected to conventional tensor product expansion, two single variable functions are calculated by minimizing the mean square error between the input vector and its outer product. A tensor product expansion is useful for feature extraction and signal compression, however, it is difficult to separate global noise from other signals. This paper shows that global noise, which is observed in almost all input signals, can be estimated by using a tensor product expansion where absolute error is used as the error function.