Improvement of background signal reduction using modified trimmed mean based outer product expansion

• Published in: 2015 10th International Conference on Information, Communications and Signal Processing (ICICS) pp. 1 - 4
• Main Authors: Itai, Akitoshi, Yasukawa, Hiroshi, Takumi, Ichi, Hata, Masayasu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2015
• Subjects: Signal to noise ratio
• DOI: 10.1109/ICICS.2015.7459841

This paper shows a new denoising algorithm based on the outer product expansion with Modified Trimmed Mean(MTM) for a background noise. We have proposed novel source separation methods using the outer product expansion with non-linear filters. The effectiveness of outer product expansions for artificial signals and an electromagnetic wave data have reported. As for an outer product expansion based denoising algorithm, the MTM method with a small trimming distance provides the accurate background noise reduction. However, the denoising performance is not improved enough due to the trimming threshold problem. In this paper, the new background noise estimation technique which calculates the MTM recurrently and its solution algorithm is proposed. Simulation results show that the proposed method produces the accurate background noise reduction.