Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognitio...Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognition using ElectroCardioGraphy(ECG) signals from multiple subjects.To collect reliable affective ECG data,we applied an arousal method by movie clips to make subjects experience specific emotions without external interference.Through precise location of P-QRS-T wave by continuous wavelet transform,an amount of ECG features was extracted sufficiently.Since feature selection is a combination optimization problem,Improved Binary Particle Swarm Optimization(IBPSO) based on neighborhood search was applied to search out effective features to improve classification results of emotion states with the help of fisher or K-Nearest Neighbor(KNN) classifier.In the experiment,it is shown that the approach is successful and the effective features got from ECG signals can express emotion states excellently.展开更多
本文针对工程与管理领域中的有约束组合优化问题,考虑变最维数大且变量间存在多重相关性的因素,以及变量间有强约束关系的特点,建立新的符合实际问题的数学模型.运用偏最小二乘回归(partial least squaresregression,PLSR)构建变量之间...本文针对工程与管理领域中的有约束组合优化问题,考虑变最维数大且变量间存在多重相关性的因素,以及变量间有强约束关系的特点,建立新的符合实际问题的数学模型.运用偏最小二乘回归(partial least squaresregression,PLSR)构建变量之间的回归模型,提出利用二进制粒子群算法优化变Km的n个水平,以期达到目标函数最优的要求,并依据求解问题的特殊性对该算法进行改进。制定新的初始种群产生策略,保证在可行解空间内进行寻优;引入动态惯性权重,保障算法具有更快的收敛性能;修改种群更新机制并加入判别函数,确保种群每次更新后都满足模型中的等式约束。通过算例和数值仿真分析,证实该算法是有效的,并能够得到较好的结果。展开更多
基金Supported by the National Natural Science Foundation of China (No.60873143)the National Key Subject Foundation for Basic Psychology (No.NKSF07003)
文摘Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognition using ElectroCardioGraphy(ECG) signals from multiple subjects.To collect reliable affective ECG data,we applied an arousal method by movie clips to make subjects experience specific emotions without external interference.Through precise location of P-QRS-T wave by continuous wavelet transform,an amount of ECG features was extracted sufficiently.Since feature selection is a combination optimization problem,Improved Binary Particle Swarm Optimization(IBPSO) based on neighborhood search was applied to search out effective features to improve classification results of emotion states with the help of fisher or K-Nearest Neighbor(KNN) classifier.In the experiment,it is shown that the approach is successful and the effective features got from ECG signals can express emotion states excellently.
文摘本文针对工程与管理领域中的有约束组合优化问题,考虑变最维数大且变量间存在多重相关性的因素,以及变量间有强约束关系的特点,建立新的符合实际问题的数学模型.运用偏最小二乘回归(partial least squaresregression,PLSR)构建变量之间的回归模型,提出利用二进制粒子群算法优化变Km的n个水平,以期达到目标函数最优的要求,并依据求解问题的特殊性对该算法进行改进。制定新的初始种群产生策略,保证在可行解空间内进行寻优;引入动态惯性权重,保障算法具有更快的收敛性能;修改种群更新机制并加入判别函数,确保种群每次更新后都满足模型中的等式约束。通过算例和数值仿真分析,证实该算法是有效的,并能够得到较好的结果。
