Underlying Trend Extraction via Joint Ensemble Intrinsic Timescale Decomposition Algorithm and Matching Pursuit Approach

2019 ◽  
Vol 38 (10) ◽  
pp. 4621-4639 ◽  
Author(s):  
Xiaoling Wang ◽  
Bingo Wing-Kuen Ling
Keyword(s):  
Matching Pursuit ◽  
Decomposition Algorithm ◽  
Trend Extraction ◽  
Underlying Trend

Optimum packing of rectangles based on heuristic dynamic decomposition algorithm

2013 ◽  
Vol 33 (7) ◽  
pp. 1908-1911
Author(s):  
Bo LI ◽  
Shi WANG ◽  
Songxin SHI ◽  
Junyong HU
Keyword(s):  
Decomposition Algorithm ◽  
Dynamic Decomposition

Kernel Matching Pursuit Based on Immune Clonal Fast Algorithm for Image Object Recognition

2011 ◽  
Vol 30 (5) ◽  
pp. 1104-1108 ◽  
Author(s):  
Shui-ping Gou ◽  
Li-cheng Jiao ◽  
Xiang-rong Zhang ◽  
Yang-yang Li
Keyword(s):  
Object Recognition ◽  
Fast Algorithm ◽  
Matching Pursuit ◽  
Image Object

Compressed Sensing Image Reconstruction Based on Improved Particle Swarm Optimization Algorithm

2014 ◽  
Vol 599-601 ◽  
pp. 1453-1456
Author(s):  
Ju Wang ◽  
Yin Liu ◽  
Wei Juan Zhang ◽  
Kun Li
Keyword(s):  
Particle Swarm Optimization ◽  
Image Reconstruction ◽  
Compressed Sensing ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Matching Pursuit ◽  
Particle Swarm ◽  
Premature Convergence ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization

The reconstruction algorithm has a hot research in compressed sensing. Matching pursuit algorithm has a huge computational task, when particle swarm optimization has been put forth to find the best atom, but it due to the easy convergence to local minima, so the paper proposed a algorithm ,which based on improved particle swarm optimization. The algorithm referred above combines K-mean and particle swarm optimization algorithm. The algorithm not only effectively prevents the premature convergence, but also improves the K-mean’s local. These findings indicated that the algorithm overcomes premature convergence of particle swarm optimization, and improves the quality of image reconstruction.

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