Name
Abstract | ||
|---|---|---|
The problem of determining sparse MA models has received much attention in recent years and is of fundamental importance in various application areas such as speech (multi-pulse excitation) or seismic data (wavelet time of arrival). This paper addresses the problem of selection and identification of non-zero coefficients in the MA models (pulse position and amplitude). The selection is done globally in the Fourier transform domain using a (complex) Pisarenko procedure, instead of sequentially. Moreover, the pulses being frequently placed in contiguous locations as a short solvo, a new MA identification method is proposed for this special case. This method only uses the AR model coefficients and the prediction residual as entries. |
Year | DOI | Venue |
|---|---|---|
1986 | 10.1109/ICASSP.1986.1169007 | Acoustics, Speech, and Signal Processing, IEEE International Conference ICASSP '86. |
Keywords | DocType | Volume |
predictive models,fourier transforms,tail,deconvolution,fourier transform,signal analysis,stochastic processes,time of arrival,ar model | Conference | 11 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gueguen, C. | 1 | 0 | 0.34 |
| Moreau, N. | 2 | 9 | 1.72 |