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- Sward, JohanLund University,Lunds universitet,Statistical Signal Processing Group,Forskargrupper vid Lunds universitet,Lund University Research Groups (author)
A generalization of the sparse iterative covariance-based estimator
- Article/chapterEnglish2017
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- 2017
- 5 s.
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- LIBRIS-ID:oai:lup.lub.lu.se:f2882b4b-f828-4814-8fa0-3f309ca6a9bd
- https://lup.lub.lu.se/record/f2882b4b-f828-4814-8fa0-3f309ca6a9bdURI
- https://doi.org/10.1109/ICASSP.2017.7952898DOI
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- Language:English
- Summary in:English
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- In this work, we extend the popular sparse iterative covariance-based estimator (SPICE) by generalizing the formulation to allow for different norm constraint on the signal and noise parameters in the covariance model. For any choice of norms, the resulting generalized SPICE method enjoys the same benefits as the regular SPICE method, including being hyperparameter free, although the choice of norm is shown to govern the sparsity in the resulting solution. Furthermore, we show that there is a connection between the generalized SPICE and a penalized regression problem, both for the case were one allows the noise parameters to differ for each sample, and when treating each noise parameter as being equal. We examine the performance of the method for different choices of norms, and compare the results to the original SPICE method, showing the benefits of using the generalized version. We also provide a way of solving the generalized SPICE using a gridless method, which solves a semi-definite programming problem.
Subject headings and genre
- TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Signalbehandling hsv//swe
- ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing hsv//eng
- convex optimization
- Covariance fitting
- sparse reconstruction
Added entries (persons, corporate bodies, meetings, titles ...)
- Adalbjornsson, Stefan IngiLund University,Lunds universitet,Matematik LTH,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematics (Faculty of Engineering),Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH(Swepub:lu)mats-sao (author)
- Jakobsson, AndreasLund University,Lunds universitet,Statistical Signal Processing Group,Forskargrupper vid Lunds universitet,Lund University Research Groups(Swepub:lu)mats-aaj (author)
- Statistical Signal Processing GroupForskargrupper vid Lunds universitet (creator_code:org_t)
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- In:2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings, s. 3954-39589781509041176
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