Name
Abstract | ||
|---|---|---|
A new, efficient recursive lattice method for autoregressive spectral analysis is presented. This method is based on an estimate of the covariance matrix, which is Toeplitz, while allowing an unbiased estimation of the frequencies of sinusoidal signals. The algorithm works recursively similarly to Burg's (1975) algorithm for maximum entropy autoregressive spectral estimation. It is shown that for truncated sinusoids in additive white noise, this method is superior to the original Burg's algorithm in resolution, positional bias (it is unbiased in the absence of noise), and spurious peaks in the spectrum, while having about the same arithmetic complexity. It also has better finite precision properties than the Levinson algorithm |
Year | DOI | Venue |
|---|---|---|
1990 | 10.1109/29.57578 | IEEE Trans. Acoustics, Speech, and Signal Processing |
Keywords | Field | DocType |
autocorrelation,spectral estimation,unbiased estimator,spectrum,resolution,white noise,noise reduction,toeplitz matrix,covariance matrix,maximum entropy,lattices | Autoregressive model,Mathematical optimization,Toeplitz matrix,White noise,Matrix method,Covariance matrix,Principle of maximum entropy,Lattice multiplication,Mathematics,Covariance | Journal |
Volume | Issue | ISSN |
38 | 8 | 0096-3518 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui-Min Zhang | 1 | 0 | 0.34 |
| P. Duhamel | 2 | 286 | 51.30 |
| S. Tressens | 3 | 269 | 18.38 |