Multiple Window Time Varying Spectrum Estimation
| dc.citation.bibtexName | article | en_US |
| dc.citation.journalTitle | Cambridge University Press | en_US |
| dc.contributor.author | Baraniuk, Richard G. | en_US |
| dc.contributor.author | Bayram, Metin | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T00:36:12Z | en_US |
| dc.date.available | 2007-10-31T00:36:12Z | en_US |
| dc.date.issued | 2000-01-20 | en_US |
| dc.date.modified | 2004-01-22 | en_US |
| dc.date.submitted | 2004-01-09 | en_US |
| dc.description | Journal Paper | en_US |
| dc.description.abstract | We overview a new non-parametric method for estimating the time-varying spectrum of a non-stationary random process. Our method extends Thomson's powerful multiple window spectrum estimation scheme to the time-frequency and time-scale planes. Unlike previous extensions of Thomson's method, we identify and utilize optimally concentrated Hermite window and Morse wavelet functions and develop a statistical test for extracting chirping line components. Examples on synthetic and real-world data illustrate the superior performance of the technique. | en_US |
| dc.identifier.citation | R. G. Baraniuk and M. Bayram, "Multiple Window Time Varying Spectrum Estimation," <i>Cambridge University Press,</i> 2000. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/19712 | en_US |
| dc.language.iso | eng | en_US |
| dc.subject | time-varying spectrum | en_US |
| dc.subject | chirping line components | en_US |
| dc.subject.keyword | time-varying spectrum | en_US |
| dc.subject.keyword | chirping line components | en_US |
| dc.subject.other | Time Frequency and Spectral Analysis | en_US |
| dc.title | Multiple Window Time Varying Spectrum Estimation | en_US |
| dc.type | Journal article | en_US |
| dc.type.dcmi | Text | en_US |
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