Sign function based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian noise environments
DOI10.3390/A9030054zbMath1461.94052OpenAlexW2516757268MaRDI QIDQ1736823
Publication date: 26 March 2019
Published in: Algorithms (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3390/a9030054
convergence analysisnon-Gaussian noiserobust sparse channel estimationsign function based least mean square error (SLMS)sparsity-promoting function
Inference from stochastic processes and prediction (62M20) Least squares and related methods for stochastic control systems (93E24) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)
Cites Work
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- Uncertainty principles and ideal atomic decomposition
- Non-Gaussian noise models in signal processing for telecommunications: new methods an results for class A and class B noise models
- Zero‐attracting variable‐step‐size least mean square algorithms for adaptive sparse channel estimation
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