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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Grenier, Y. |
| Copyright Year | 1983 |
| Description | Author affiliation: Ecole Nationale Superieure des Telecommunications, Paris, France (Grenier, Y.) |
| Abstract | This paper describes two methods for time-dependent moving-average modelling of non-stationary signals. In both of them, the finite-order MA model is approximated by an infinite-order auto-re gressive model. In the second one, the use of the AR model is explicit : by means of the inversion of this model, the innovation is estimated and the MA model is then obtained by a least-square procedure. In the first method, the AR model is implicit : a vector signal is associated to the scalar one, and the MA algorithm contains two steps : Schur parametrization of an estimate of the covariance of the vector process, followed by a reduction of the vector model to a scalar one. |
| Starting Page | 268 |
| Ending Page | 271 |
| File Size | 68698 |
| Page Count | 4 |
| File Format | |
| DOI | 10.1109/ICASSP.1983.1172159 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1983-04-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Signal processing algorithms Speech synthesis Technological innovation Signal processing Adaptive signal processing Signal synthesis Speech analysis White noise |
| Content Type | Text |
| Resource Type | Article |
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