Name
Abstract | ||
|---|---|---|
An important hurdle in multi-exponential analysis is the correct detection of the number of components in a multi-exponential signal and their subsequent identification. This is especially difficult if one or more of these terms are faint and/or covered by noise. We present an approach to tackle this problem and illustrate its usefulness in motor current signature analysis (MCSA), relaxometry (in FLIM and MRI) and magnetic resonance spectroscopy (MRS). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.amc.2017.11.007 | Applied Mathematics and Computation |
Keywords | Field | DocType |
Multi-exponential analysis,Padé approximation,Spectral analysis | Exponential function,Padé approximant,Mathematical analysis,Algorithm,Filter (signal processing),Spectral analysis,Relaxometry,Mathematics | Journal |
Volume | ISSN | Citations |
327 | 0096-3003 | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Annie Cuyt | 1 | 161 | 41.48 |
| Min-nan Tsai | 2 | 0 | 0.34 |
| Marleen Verhoye | 3 | 108 | 16.65 |
| Wen-shin Lee | 4 | 182 | 15.67 |