Information Technology Reference
In-Depth Information
Comon P (1994) Independent component analysis, a new concept? Sig Process 36(3):287
-
314
Cong F, Alluri V, Nandi AK et al (2013) Linking brain responses to naturalistic music through
analysis of ongoing EEG and stimulus features. IEEE Trans Multimedia 15(5):1060
-
1069
Cornelius RR (1996) The science of emotion. Prentice Hall, Upper Saddle River
Cowie R, Douglas-Cowie E (2000)
“
FEELTRACE
”
: an instrument for recording perceived
emotion in real time. In: Proceedings of the ISCA workshop on speech and emotion: a
conceptual framework for research, Belfast, pp 19
-
24
Daly I, Nasuto SJ, Warwick K (2011) Single tap identification for fast BCI control. Cogn
Neurodyn 5(1):21
30
Daly I, Nasuto SJ, Warwick K (2012) Brain computer interface control via functional connectivity
dynamics. Pattern Recogn 45(6):2123
-
2136
Dy J (2004) Feature selection for unsupervised learning. J Mach Learn Res 5:845
-
889
Ekman P (2003) Emotions revealed: recognizing faces and feelings to improve communication
and emotional life. Weidenfeld & Nicolson, London
Fontaine JRJ, Scherer KR, Roesch EB et al (2007) The world of emotions is not two-dimensional.
Psychol Sci 18(12):1050
-
1057
Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res
3:1157
-
1182
Hevner SK (2007) EMuJoy: software for continuous measurement. Behav Res Methods 39
(2):283
-
290
Hwang HJ, Kim S, Choi S et al (2013) EEG-based brain
-
computer interfaces (BCIs): a thorough
literature survey. Int J Human Comput Interact 29(12):814
-
826
Izard CE (2007) Basic emotions, natural kinds, emotion schemas, and a new paradigm. Perspect
Psychol Sci 2:260
-
280
Kokkinos I, Maragos P (2005) Nonlinear speech analysis using models for chaotic systems. IEEE
Trans Speech Audio Process 13(6):1098
-
1109
Lang PJ, Bradley MM, Cuthbert BN (2008) International affective picture system (IAPS): affective
ratings of pictures and instruction manual. Technical Report A-6, University of Florida,
Gainesville, Fl
Larsen RJ, Diener E (1987) Affect intensity as an individual difference characteristic: a review.
J Res Pers 21(1):1
-
39
Lee H, Seungjin C (2003) PCA + HMM + SVM for EEG pattern classi
cation. In: Proceedings of
signal processing and its applications, vol 1, pp 541
-
544
Lin Y, Juny T, Chen J (2009) EEG dynamics during music appreciation. In: Annual international
conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in
Medicine and Biology Society, pp 5316
-
5319
Lin Y-P, Wang C-H, Jung T-P et al (2010) EEG-based emotion recognition in music listening.
IEEE Trans Biomed Eng 57(7):1798
-
1806
Lin Y-P, Chen J-H, Duann J-R et al (2011) Generalizations of the subject-independent feature set
for music-induced emotion recognition. In: 33rd annual international conference of the IEEE,
EMBS, Boston, Massachusetts, USA
Liu M, Wan C (2001) Feature selection for automatic classification of musical instrument sounds.
In: Proceedings of the
first ACM/IEEE-CS joint conference on digital libraries
-
—
JCDL
'
01.
ACM Press, New York, pp 247
248
-
Lotte F, Congedo M, L
cuyer A et al (2007) A review of classi
cation algorithms for EEG-based
brain-computer interfaces. J Neural Eng 4(2):1
é
13
Matthews G (1990) Re
ning the measurement of mood: the UWIST mood adjective checklist. Br J
Psychol 81(1):17
-
42
-
Mitrovi
D, Zeppelzauer M, Breiteneder C (2010) Features for content-based audio retrieval. Adv
Comput 78:71
ć
150
M
ü
ller KR, Krauledat M, Dornhege G et al (2004) Machine learning techniques for brain-
computer interfaces. Biomed Eng 49(1):11
-
22
-
