Chaotic particle swarm optimization algorithm based on nonlinear conjugate gradient algorithm

2010 ◽  
Vol 29 (12) ◽  
pp. 3273-3276
Author(s):  
Hong-an CHEN ◽  
Ying-jie ZHANG ◽  
Jian-hui WU
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Conjugate Gradient ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Conjugate Gradient Algorithm ◽  
Gradient Algorithm ◽  
Swarm Optimization ◽  
Nonlinear Conjugate Gradient ◽  
Chaotic Particle Swarm Optimization

Research of Tent Map Based Chaotic Particle Swarm Optimization Algorithm for Emotion Recognition

2010 ◽  
Vol 143-144 ◽  
pp. 1280-1284
Author(s):  
Hai Ning Wang ◽  
Shou Qian Sun ◽  
Jian Feng Wu ◽  
Fu Qian Shi
Keyword(s):  
Particle Swarm Optimization ◽  
Emotion Recognition ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Feature Reduction ◽  
Experimental Simulation ◽  
Swarm Optimization ◽  
Tent Map ◽  
Chaotic Particle Swarm Optimization

For the problem of feature redundancy of emotion recognition based on multi-channel physiological signals and low efficiency of traditional feature reduction algorithms on great sample data, a new chaotic particle swarm optimization algorithm (TM-CPSO) was proposed to solve the problem of emotion feature selection by combining tent map based chaos search mechanism and improved particle swarm optimization algorithm. The problem of falling into local minimum can be avoided by mapping the search process to the recursive procedure of the chaotic orbit. The recognition rate and efficiency was increased and the algorithm's validity was verified through the analysis of experimental simulation data and the comparison of several recognition methods.

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