Estimation of Fourier Transform Using Alias-free Hybrid-Stratified Sampling
- Submitting institution
-
The University of Westminster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 9vy72
- Type
- D - Journal article
- DOI
-
10.1109/TSP.2016.2540602
- Title of journal
- IEEE Transactions on Signal Processing
- Article number
- -
- First page
- 3065
- Volume
- 54
- Issue
- 12
- ISSN
- 1053-587X
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2016
- 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
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- We propose a fast-converging estimator of windowed Fourier Transform, using a finite number of signal samples. Owing to the use of specialised random sampling scheme and signal processing algorithm, the estimator is unbiased in an arbitrarily wide frequency range. Its pointwise and uniform convergence rates, as measured by its variance, are inverse proportional to the fifth power of the number of samples N. The uniform convergence rates of competing solutions published beforehand in the research literature are inverse proportional to N. In terms of pointwise convergence rate, none of them is faster than the method proposed here.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
