Name
Abstract | ||
|---|---|---|
In general, acoustic channels are not Gaussian distributed neither are second-order stationary. Considering them for signal processing methods designed for Gaussian assumptions is inadequate, consequently yielding in poor performance of such methods. This paper presents an analysis for audio signal corrupted by impulsive noise using non-Gaussian models. Audio samples are compared to the Gaussian, alpha-stable and Gaussian mixture models, evaluating the fitting by graphical and numerical methods. We discuss fitting properties as the window length and the overlap, finally concluding that the alpha-stable model has the best fit for all tested scenarios. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19122827 | SENSORS |
Keywords | Field | DocType |
noise estimation,non-Gaussian noise,maximum likelihood,acoustic channel | Signal processing,Audio signal,Maximum likelihood,Algorithm,Communication channel,Electronic engineering,Gaussian,Engineering,Numerical analysis,Mixture model | Journal |
Volume | Issue | ISSN |
19 | 12 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Danilo Pena | 1 | 0 | 0.68 |
| Carlos Lima | 2 | 0 | 0.34 |
| Matheus Dória | 3 | 0 | 0.34 |
| Luan Pena | 4 | 0 | 0.68 |
| Allan Martins | 5 | 0 | 0.68 |
| Vicente A. de Sousa Jr. | 6 | 92 | 9.52 |