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Lower-norm criterion based background noise estimation for simple observation model | IEEE Conference Publication | IEEE Xplore

Lower-norm criterion based background noise estimation for simple observation model


Abstract:

This paper shows a novel estimation algorithm based on the outer product expansion with lower norms for the background noise. We have proposed a blind source separation u...Show More

Abstract:

This paper shows a novel estimation algorithm based on the outer product expansion with lower norms for the background noise. We have proposed a blind source separation using an outer product expansion with L1 norm minimization. The effectiveness of outer product expansions for artificial signals and an electromagnetic wave data was represented. However, the estimation performance is decreasing with an increasing of local signals. In this paper, we propose the outer product expansion with lower norms (0.1 ~ 0.9). Simulation results show that the proposed method produces the accurate background noise estimation.
Date of Conference: 25-28 October 2016
Date Added to IEEE Xplore: 05 January 2017
ISBN Information:
Conference Location: Jeju, Korea (South)

References

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