Maximum-likelihood autoregressive estimation on incomplete spectra

被引：0

作者：

Weruaga, Luis ^{[1
]}

Kepesi, Marian ^{[2
]}

机构：

[1] Austrian Acad Sci, VISKOM, Donau City Str, A-1090 Vienna, Austria

[2] Graz Univ Technol, SPSC Lab, A-8010 Graz, Austria

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL III, PTS 1-3, PROCEEDINGS | 2007年

关键词：

autoregressive model; frequency domain; incomplete spectrum; maximum likelihood;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Frequency-selective autoregressive (AR) estimation is arousing increasing interest. We propose herein a new method to estimate the AR model from a reduced set of spectral samples. The proposed method is founded on the maximum likelihood criterion over the logarithmic spectral residue, and it is implemented efficiently with a multivariate Newton-Raphson algorithm. Results over deterministic and stochastic scenarios show its excellent performance.

引用

页码：1001 / +

页数：2

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