| 用自适应蚁群算法的生理信号情感状态识别 |
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| 引用本文： | 鲁舜,刘光远.用自适应蚁群算法的生理信号情感状态识别[J].计算机应用,2009,29(Z1). |
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| 作者姓名： | 鲁舜 刘光远 |
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| 作者单位： | 西南大学,电子信息工程学院,重庆,400715 |
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| 基金项目： | 国家自然科学基金，西南大学国家重点学科基础心理学科研基金 |
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| 摘 要： | 针对生理信号的情感识别问题,将蚁群优化算法用于情感生理信号特征选择,并采用自适应的适应度参数值、变异策略和临近位置交换策略对算法进行改进,使用K近邻法进行情感分类,以获得较高的识别率和有效特征组合.通过四种生理信号(EMG、SC、ECG、RSP)来识别四种情感(joy、anger、sadness、pleasure),实验仿真结果表明,将蚁群优化算法引入情感识别的研究是可行的.
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| 关 键 词： | 情感识别 蚁群算法 自适应 生理信号 特征选择 |
Emotion recognition from physiological signal based on adaptive ACO |
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| LU Shun,LIU Guang-yuan.Emotion recognition from physiological signal based on adaptive ACO[J].journal of Computer Applications,2009,29(Z1). |
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| Authors: | LU Shun LIU Guang-yuan |
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| Affiliation: | School of Electronic and Information Engineering;Southwest University;Chongqing 400715;China |
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| Abstract: | Aiming at the problem about emotion recognition of physiological signals,a method of feature selection was based on Ant Colony Optimization(ACO).The paper used adaptive fitness parameter,mutation strategy and neighbor position exchanged to improve the ACO algorithm,used k-nearest for recognizing emotion classify to obtain upper correct recognizing rate and the effective feature subset.The survey recognized 4 emotion states(joy,anger,sadness,pleasure) using 4 physiological signals(EMG,SC,ECG,RSP),Simulation ... |
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