Abstract
Aiming at the disadvantages of greedy algorithms in sparse solution, a modified adaptive orthogonal matching pursuit algorithm (MAOMP) is proposed in this paper. It is obviously improved to introduce sparsity and variable step size for the MAOMP. The algorithm estimates the initial value of sparsity by matching test, and will decrease the number of subsequent iterations. Finally, the step size is adjusted to select atoms and approximate the true sparsity at different stages. The simulation results show that the algorithm which has proposed improves the recognition accuracy and efficiency comparing with other greedy algorithms.
Original language | English |
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Number of pages | 10 |
Journal | Cluster Computing |
Early online date | 7 Oct 2017 |
DOIs | |
Publication status | Early online - 7 Oct 2017 |
Keywords
- pursuit algorithm
- gesture recognition
- pattern recognition
- sparse representation
- estimation