Antithetical Stratified Sampling Estimator for Filtering Signals with Discontinuities
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- v270q
- Type
- D - Journal article
- DOI
-
10.1016/j.sigpro.2020.107910
- Title of journal
- Signal Processing
- Article number
- 107910
- First page
- -
- Volume
- 181
- Issue
- -
- ISSN
- 0165-1684
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes an alias-free implementation of digital filters approximating behaviour of continuous-time filters with finite-duration impulse response. Owing to the use of random, antithetical stratified sampling and simple but specialised signal processing algorithm, the output of the proposed filter is an unbiased estimator of its continuous-time counterpart. The variance of the estimator converges fast towards zero with the increasing density of signal samples. It is proven that depending on smoothness of the processed signal, the convergence rate is inverse-proportional to the second, fourth or even fifth power of samples’ density.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
