Lower-norm criterion based background noise estimation for simple observation model
| Autor: | Akitoshi Itai, Yuta Hara |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Background noise
Mathematical optimization Norm (mathematics) 0202 electrical engineering electronic engineering information engineering Norm minimization Outer product 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology Algorithm Blind signal separation Electromagnetic radiation Mathematics |
| Zdroj: | APCCAS |
| DOI: | 10.1109/apccas.2016.7803884 |
| Popis: | 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 L 1 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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