An incremental-PID-controlled particle swarm optimization algorithm for EEG-data-based estimation of operator functional state

2014 ◽  
Vol 14 ◽  
pp. 272-284 ◽  
Author(s):  
Jianhua Zhang ◽  
Shaozeng Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Functional State ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Eeg Data ◽  
Operator Functional State

scholarly journals The Design Of Intelligent Filter For EEG

2018 ◽  
Vol 232 ◽  
pp. 04023
Author(s):  
Dachao Yue ◽  
Haikuan Liu
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Filter Design ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Iir Filter ◽  
Data Processing Method ◽  
Eeg Data ◽  
Filtering Effect

EEG data processing method is usually digital filter designed by the traditional method. Its disadvantage is the transition zone is wide and the filtering effect is poor. Using an improved particle swarm optimization algorithm on IIR digital filters design, the performances of filters designed by various methods are compared and analyzed. Experiments illustrate particle swarm optimization algorithm is effective in IIR filter design and its performance is promising.

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