Iterative missing data recovery algorithm for non-stationary signals
(2022) In Signal, Image and Video Processing 16(7). p.1731-1738- Abstract
This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding components to convert them into stationary components. Following this, a relatively recent nonparametric iterative missing data recovery procedure is employed to reconstruct the time-varying amplitudes of the signal components. The complete signal is constructed by adding all the estimated components, which is used as an input signal to re-estimate the... (More)
This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding components to convert them into stationary components. Following this, a relatively recent nonparametric iterative missing data recovery procedure is employed to reconstruct the time-varying amplitudes of the signal components. The complete signal is constructed by adding all the estimated components, which is used as an input signal to re-estimate the IFs and time-varying amplitudes in an iterative procedure. Studies based on simulated and real data sets show that the proposed approach provides better estimates as compared to the state of the art.
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- author
- Khan, Nabeel Ali ; Butt, Naveed R. LU and Jakobsson, Andreas LU
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Amplitude-modulation frequency modulation (AM-FM), Instantaneous frequency, Missing data, Non-stationary signals, Time–frequency
- in
- Signal, Image and Video Processing
- volume
- 16
- issue
- 7
- pages
- 1731 - 1738
- publisher
- Springer
- external identifiers
-
- scopus:85124564877
- ISSN
- 1863-1703
- DOI
- 10.1007/s11760-021-02128-5
- language
- English
- LU publication?
- yes
- id
- c38d9ba0-feab-43be-a061-ea9887896345
- date added to LUP
- 2022-04-14 12:11:40
- date last changed
- 2022-10-31 14:56:19
@article{c38d9ba0-feab-43be-a061-ea9887896345, abstract = {{<p>This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding components to convert them into stationary components. Following this, a relatively recent nonparametric iterative missing data recovery procedure is employed to reconstruct the time-varying amplitudes of the signal components. The complete signal is constructed by adding all the estimated components, which is used as an input signal to re-estimate the IFs and time-varying amplitudes in an iterative procedure. Studies based on simulated and real data sets show that the proposed approach provides better estimates as compared to the state of the art.</p>}}, author = {{Khan, Nabeel Ali and Butt, Naveed R. and Jakobsson, Andreas}}, issn = {{1863-1703}}, keywords = {{Amplitude-modulation frequency modulation (AM-FM); Instantaneous frequency; Missing data; Non-stationary signals; Time–frequency}}, language = {{eng}}, number = {{7}}, pages = {{1731--1738}}, publisher = {{Springer}}, series = {{Signal, Image and Video Processing}}, title = {{Iterative missing data recovery algorithm for non-stationary signals}}, url = {{http://dx.doi.org/10.1007/s11760-021-02128-5}}, doi = {{10.1007/s11760-021-02128-5}}, volume = {{16}}, year = {{2022}}, }