Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography
A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large syste...
Main Authors: | , , , |
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Other Authors: | |
Format: | Journal Article |
Language: | English |
Published: |
2014
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/79633 http://hdl.handle.net/10220/19044 |