Cascade of Linear Predictors for Deconvolution of Non-Stationary Channels in Sparse and Antisparse Scenarios Article Swipe
Renan Brotto
,
Kenji Nose-Filho
,
Romis Attux
,
João Marcos Travassos Romano
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.14209/jcis.2021.10
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.14209/jcis.2021.10
This work deals with adaptive predictive deconvolution of non-stationary channels. In particular, we investigate the use of a cascade of linear predictors in the recovering of sparse and antisparse original signals. To do so, we first discuss the behavior of the Lp Prediction Error Filter (PEF), with p different of 2, showing that it has a superior ability to deal with non-minimum phase channels in comparison with the classical L2 PEF, although it still presents intrinsic limitations due to its direct linear structure. The cascade structure emerges as a possible solution to circumvent this issue. We apply the proposed cascade structure in the deconvolution of non-stationary channels, with minimum-, maximum- , mixed- and variable-phase response, and also noise scenarios. From the simulation results we observed that, besides the duality relation between the Lp norms, they present different algorithmic behavior: the L1 norm attains a fast convergence, enhancing the cascade tracking capacity, but is more sensible to noise. The L4 norm, on the other hand, is more robust to noise, but presents slower convergence and tracking capability.
Related Topics
Concepts
Cascade
Deconvolution
Mathematics
Convergence (economics)
Filter (signal processing)
Computer science
Norm (philosophy)
Noise (video)
Algorithm
Mathematical optimization
Control theory (sociology)
Artificial intelligence
Image (mathematics)
Economic growth
Computer vision
Chromatography
Chemistry
Control (management)
Economics
Law
Political science
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.14209/jcis.2021.10
- https://jcis.sbrt.org.br/jcis/article/download/724/520
- OA Status
- diamond
- Cited By
- 3
- References
- 17
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3160265307
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3160265307Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.14209/jcis.2021.10Digital Object Identifier
- Title
-
Cascade of Linear Predictors for Deconvolution of Non-Stationary Channels in Sparse and Antisparse ScenariosWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-01-01Full publication date if available
- Authors
-
Renan Brotto, Kenji Nose-Filho, Romis Attux, João Marcos Travassos RomanoList of authors in order
- Landing page
-
https://doi.org/10.14209/jcis.2021.10Publisher landing page
- PDF URL
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https://jcis.sbrt.org.br/jcis/article/download/724/520Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://jcis.sbrt.org.br/jcis/article/download/724/520Direct OA link when available
- Concepts
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Cascade, Deconvolution, Mathematics, Convergence (economics), Filter (signal processing), Computer science, Norm (philosophy), Noise (video), Algorithm, Mathematical optimization, Control theory (sociology), Artificial intelligence, Image (mathematics), Economic growth, Computer vision, Chromatography, Chemistry, Control (management), Economics, Law, Political scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1, 2022: 2Per-year citation counts (last 5 years)
- References (count)
-
17Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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