Name
Abstract | ||
|---|---|---|
A novel approach for signal parameter estimation, named the non-linear instantaneous least squares (NILS) estimator, is proposed and a high SNR statistical analysis of the estimates is presented. The algorithm is generally applicable to deterministic signal in noise models. However, it is of particular interest in applications where the "conventional" non-linear least squares criterion suffers from numerous local minima. The key idea here is to apply a sliding window to estimate the instantaneous amplitude, which is then used in a separable least squares criterion-function. Hereby the radius of attraction of the global minimum is under the control of the user, which makes the NILS approach advantageous to use in practical applications. Numerical results using polynomial-phase signals validate the theoretical results. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/ICASSP.1999.756212 | ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 |
Keywords | Field | DocType |
instantaneous amplitude,novel approach,squares criterion-function,nils approach,squares criterion,non-linear instantaneous,key idea,high snr statistical analysis,signal parameter estimation,high snr analysis,polynomial-phase signal,global minimum,least square,local minima,noise,signal to noise ratio,algorithm,least squares approximation,sliding window,statistical analysis,maximum likelihood estimation,signal processing,parameter estimation,polynomials | Least squares,Mathematical optimization,Signal-to-noise ratio,Non-linear least squares,Estimation theory,Residual sum of squares,Total least squares,Recursive least squares filter,Mathematics,Estimator | Conference |
ISSN | ISBN | Citations |
1520-6149 | 0-7803-5041-3 | 4 |
PageRank | References | Authors |
0.49 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jakob Ängeby | 1 | 15 | 1.57 |
| M. Viberg | 2 | 917 | 188.13 |
| Tony Gustafsson | 3 | 4 | 0.49 |