Fast adaptive PARAFAC decomposition algorithm with linear complexity
We present a fast adaptive PARAFAC decomposition algorithm with low computational complexity. The proposed algorithm generalizes the Orthonormal Projection Approximation Subspace Tracking (OPAST) approach for tracking a class of third-order tensors which have one dimension growing with time. It has...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
ĐHCN
2016
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| Subjects: | |
| Online Access: | http://repository.vnu.edu.vn/handle/VNU_123/13033 |
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| Institution: | Vietnam National University, Hanoi |
| Language: | English |
| Summary: | We present a fast adaptive PARAFAC decomposition algorithm with low computational complexity. The proposed algorithm generalizes the Orthonormal Projection Approximation Subspace Tracking (OPAST) approach for tracking a class of third-order tensors which have one dimension growing with time. It has linear complexity, good convergence rate and good estimation accuracy. To deal with large-scale problems, a parallel implementation can be applied to reduce both computational complexity and storage. We illustrate the effectiveness of our algorithm in comparison with the state-of-the-art algorithms through simulation experiments. |
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