Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/55484
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Type: Journal article
Title: Robust adaptive-scale parametric model estimation for computer vision
Author: Wang, H.
Suter, D.
Citation: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004; 26(11):1459-1474
Publisher: IEEE Computer Soc
Issue Date: 2004
ISSN: 0162-8828
1939-3539
Statement of
Responsibility: 
M. Pathmanathan, C. Tang, W.L. Soong and N. Ertugrul
Abstract: Small-scale wind turbines commonly use AC/DC converters such as rectifiers, switched mode rectifiers (SMRs) and inverters. Another power converter, the semi-bridge SMR has been researched for automotive applications, and is utilised by a number of small-scale wind turbine manufacturers. This paper applies a novel modulation technique developed for automotive applications of the semi-bridge SMR for Lundell and interior permanent magnet alternators to small-scale wind turbines utilising surface permanent magnet generators. The performance obtained using the semi-bridge SMR is compared to that obtained using single-switch SMRs and inverters.
Keywords: Image Interpretation, Computer-Assisted
Image Enhancement
Subtraction Technique
Cluster Analysis
Sensitivity and Specificity
Reproducibility of Results
Algorithms
Feedback
Artificial Intelligence
Computer Graphics
Computer Simulation
Numerical Analysis, Computer-Assisted
Signal Processing, Computer-Assisted
User-Computer Interface
Information Storage and Retrieval
Pattern Recognition, Automated
DOI: 10.1109/TPAMI.2004.109
Description (link): http://ieeexplore.ieee.org/servlet/opac?punumber=4807911
Published version: http://dx.doi.org/10.1109/tpami.2004.109
Appears in Collections:Aurora harvest
Computer Science publications
Environment Institute publications

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