Applications of Particle Swarm Optimization and K-Nearest Neighbors to Emotion recognition from physiological signals

Proceedings - 2008 International Conference on Computational Intelligence and Security, CIS 2008

Volumn 2, Issue , 2008, Pages 52-56

  Defu, Cheng ^a   Guangyuan, Liu ^a   Qiu Yuhui, ^a  

^a SOUTHWEST UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

EMOTION FEATURE; EMOTION RECOGNITION; FEATURE COMBINATION; FEATURE SUBSET; IMPROVED METHODS; K-NEAREST NEIGHBORS; LOOK UP TABLE; MULTI-CLASSIFICATION; PHYSIOLOGICAL SIGNALS; RECOGNITION RATES; RESEARCH AND APPLICATION;

ARTIFICIAL INTELLIGENCE; STRUCTURAL OPTIMIZATION; TABLE LOOKUP;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 60349101049     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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2. Johannes Wagner, Jonghwa Kim, Elisabeth André. From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification[C]. In IEEE International Conference on Multimedia & Expo(ICME 2005), 2005, 940-943.
3. P. Pudil, J. Novovicǒvá, j. Kittler. Floating search methods in feature selection. Pattern Recognition Letters 15 (1994) 1119-1125.
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5. Huan Liu, Lei Yu. Toward Integrating Feature Selection Algorithms for Classification and Clustering. IEEE Transactions on knowledge and data engineering, 2005, 17(4):491-502.
6. Kennedy J, Eberhart RC.A discrete binary version of the particle swarm algorithm[A]. Proc.of the 1997 Conf. on Systems, Man, and Cybernetics [C]. Piscataway: IEEE Press, 1997.4104-4108.
7. JACOF.SCHUTTE and ALBERTA.GROENWOLD. A Study of Global Optimization Using Particle Swarms. Springer, Journal of Global Optimization (2005) 31: 93-108.
8. http://mm-werkstatt.informatik.uni-augsburg.de/project-details.php?id=33 .