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Cluster Computing
Erschienen in: Cluster Computing 1/2019

07.10.2017

Gesture recognition based on modified adaptive orthogonal matching pursuit algorithm

verfasst von: Bei Li, Ying Sun, Gongfa Li, Jianyi Kong, Guozhang Jiang, Du Jiang, Bo Tao, Shuang Xu, Honghai Liu

Erschienen in: Cluster Computing | Sonderheft 1/2019

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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.
Vorheriger Artikel Study of spectral reflectance reconstruction based on regularization matrix R method
Nächster Artikel An effective task scheduling algorithm based on dynamic energy management and efficient resource utilization in green cloud computing environment

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Metadaten
Titel
Gesture recognition based on modified adaptive orthogonal matching pursuit algorithm
verfasst von
Bei Li
Ying Sun
Gongfa Li
Jianyi Kong
Guozhang Jiang
Du Jiang
Bo Tao
Shuang Xu
Honghai Liu
Publikationsdatum
07.10.2017
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 1/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1231-7

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