334 research outputs found
Multi-Step Knowledge-Aided Iterative ESPRIT for Direction Finding
In this work, we propose a subspace-based algorithm for DOA estimation which
iteratively reduces the disturbance factors of the estimated data covariance
matrix and incorporates prior knowledge which is gradually obtained on line. An
analysis of the MSE of the reshaped data covariance matrix is carried out along
with comparisons between computational complexities of the proposed and
existing algorithms. Simulations focusing on closely-spaced sources, where they
are uncorrelated and correlated, illustrate the improvements achieved.Comment: 7 figures. arXiv admin note: text overlap with arXiv:1703.1052
Randomized Rank-Revealing QLP for Low-Rank Matrix Decomposition
The pivoted QLP decomposition is computed through two consecutive pivoted QR
decompositions, and provides an approximation to the singular value
decomposition. This work is concerned with a partial QLP decomposition of
low-rank matrices computed through randomization, termed Randomized Unpivoted
QLP (RU-QLP). Like pivoted QLP, RU-QLP is rank-revealing and yet it utilizes
random column sampling and the unpivoted QR decomposition. The latter
modifications allow RU-QLP to be highly parallelizable on modern computational
platforms. We provide an analysis for RU-QLP, deriving bounds in spectral and
Frobenius norms on: i) the rank-revealing property; ii) principal angles
between approximate subspaces and exact singular subspaces and vectors; and
iii) low-rank approximation errors. Effectiveness of the bounds is illustrated
through numerical tests. We further use a modern, multicore machine equipped
with a GPU to demonstrate the efficiency of RU-QLP. Our results show that
compared to the randomized SVD, RU-QLP achieves a speedup of up to 7.1 times on
the CPU and up to 2.3 times with the GPU
Issues Around Researching OHS of Samoan Migrant Workers
Workers from Pacific nations constitute a substantial proportion of the labour force in NZ, particularly in Auckland, which has one of the largest concentrations of Pacific Island workers in the world. Samoans constitute the largest Pacific ethnic group in NZ, comprising 131,103 or 49% of the resident Pacific population (265,974) (Statistics NZ, 2010). However, Pacific Island workers in NZ are typically employed in low paid, precarious, hazardous work that often has little chance of advancement. There is also some evidence that Pacific Island workers are overĂ‚Ârepresented in NZ’s workĂ‚Ârelated injury and illness statistics (Allen & Clarke, 2006). While occupational health and safety (OHS) of Pacific Island migrant workers highlights a number of issues, studies often provide inadequate explanations of what exactly is occurring or fully capture the working experiences of Pacific Island migrant workers. This paper reports on the initial work undertaken as part of an international collaborative study located in Samoa and NZ, aimed at investigating the OHS experiences of Samoan migrant workers. In particular, the paper presents a multiĂ‚Âlayered framework and a set of research principles that can be used to illuminate often inaccessible populations located in changing working and living environments. Finally, this study exemplifies the complex issues surrounding the migrant workers’ health and safety, workers’ compensation and rehabilitation
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