Name
Abstract | ||
|---|---|---|
This work addresses the Auto-Regressive modeling in Single-Input Two-Outputs (SITO) scenarios, where the lack of input signal diversity prevents application of state-of-the-art multichannel methods. Firstly, we derive a system of Yule-Walker-like equations involving only the cross-correlation of the observations. Then, we leverage the Toeplitz, not Hermitian, structure of the system coefficient matrix to derive an Asymmetric Levinson recursion. Finally, we present a novel lattice based computation of the recursion, named Cross-Burg algorithm. The Cross-Burg lattice is built by two sub-lattices, mutually connected by the reflection coefficients. The Cross-Burg algorithm is inherently robust to uncorrelated additive noise on the two observed channels. Numerical simulations show that the Cross-Burg algorithm outperforms traditional methods in accuracy and noise robustness for SITO-AR modeling and spectral estimation. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LSP.2021.3101128 | IEEE SIGNAL PROCESSING LETTERS |
Keywords | DocType | Volume |
Signal processing algorithms, Lattices, Mathematical model, Numerical models, Estimation, Data models, Signal to noise ratio, Single Input Two Outputs AR modeling, Noise robust AR Modeling, Cross-Burg Method | Journal | 28 |
ISSN | Citations | PageRank |
1070-9908 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefania Colonnese | 1 | 137 | 26.43 |
| Francesco Conti | 2 | 0 | 0.34 |
| M. Biagi | 3 | 87 | 9.18 |
| Gaetano Scarano | 4 | 209 | 31.32 |