Name
Title | ||
|---|---|---|
Time-variant harmonic signal modeling by using polynomial approximation and fully automated spectral analysis |
Abstract | ||
|---|---|---|
We present a novel approach to modelling time-variant harmonic content in audio signals. We show that both amplitude and fundamental frequency time variations can be compactly captured in a single time polynomial which modulates the fundamental harmonic component. A correct estimation of the fundamental frequency is assured through the fully automated spectral analysis method (ASA).The best-fit is easily obtained by linear least-squares, given the fact that the set of equations is linear-in-parameters. In contrast to the existing methods, the proposed approach is designed to properly describe harmonic structures in audio signals under conditions of both AM and FM modulations and low signal-to noise ratios. |
Year | Venue | Keywords |
|---|---|---|
2009 | Glasgow | audio signal processing,harmonics,polynomial approximation,spectral analysis,am modulation,fm modulation,amplitude time variations,audio signal,automated spectral analysis method,fully automated spectral analysis,fundamental frequency estimation,fundamental frequency time variations,fundamental harmonic component,single time polynomial,time-variant harmonic content,time-variant harmonic signal,estimation,frequency modulation,time frequency analysis,polynomials,harmonic analysis |
Field | DocType | ISBN |
Audio signal,Mathematical optimization,Fundamental frequency,Polynomial,Algorithm,Harmonic,Harmonic analysis,Time–frequency analysis,Frequency modulation,Amplitude,Mathematics | Conference | 978-161-7388-76-7 |
Citations | PageRank | References |
3 | 0.91 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zivanovic, M. | 1 | 59 | 10.80 |
| Johan Schoukens | 2 | 4 | 2.61 |