Title |
Distributed Gram-Schmidt orthogonalization with simultaneous elements refinement
|
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Published in |
EURASIP Journal on Advances in Signal Processing, February 2016
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DOI | 10.1186/s13634-016-0322-6 |
Pubmed ID | |
Authors |
Ondrej Slučiak, Hana Straková, Markus Rupp, Wilfried Gansterer |
Abstract |
We present a novel distributed QR factorization algorithm for orthogonalizing a set of vectors in a decentralized wireless sensor network. The algorithm is based on the classical Gram-Schmidt orthogonalization with all projections and inner products reformulated in a recursive manner. In contrast to existing distributed orthogonalization algorithms, all elements of the resulting matrices Q and R are computed simultaneously and refined iteratively after each transmission. Thus, the algorithm allows a trade-off between run time and accuracy. Moreover, the number of transmitted messages is considerably smaller in comparison to state-of-the-art algorithms. We thoroughly study its numerical properties and performance from various aspects. We also investigate the algorithm's robustness to link failures and provide a comparison with existing distributed QR factorization algorithms in terms of communication cost and memory requirements. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 5 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 2 | 40% |
Student > Ph. D. Student | 1 | 20% |
Student > Master | 1 | 20% |
Unknown | 1 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 1 | 20% |
Computer Science | 1 | 20% |
Physics and Astronomy | 1 | 20% |
Engineering | 1 | 20% |
Unknown | 1 | 20% |