Name
Title | ||
|---|---|---|
Tensor Decompositions With Several Block-Hankel Factors and Application in Blind System Identification. |
Abstract | ||
|---|---|---|
Several applications in biomedical data processing, telecommunications, or chemometrics can be tackled by computing a structured tensor decomposition. In this paper, we focus on tensor decompositions with two or more block-Hankel factors, which arise in blind multiple-input-multiple-output (MIMO) convolutive system identification. By assuming statistically independent inputs, the blind system iden... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TSP.2017.2695445 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Tensile stress,Matrix decomposition,MIMO,Finite impulse response filters,Additive noise,Telecommunications,Signal processing algorithms | Uniqueness,Mathematical optimization,Subspace topology,Tensor,Underdetermined system,Matrix decomposition,MIMO,Finite impulse response,System identification,Mathematics | Journal |
Volume | Issue | ISSN |
65 | 15 | 1053-587X |
Citations | PageRank | References |
1 | 0.35 | 26 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frederik Van Eeghem | 1 | 3 | 1.73 |
| Mikael Sørensen | 2 | 80 | 10.55 |
| Lieven De Lathauwer | 3 | 3002 | 226.72 |