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1¡¢Nonlinear Dynamics of EEG Signal based on Coupled Network Lattice Model

2¡¢Dynamic Synchrony Analysis of ERP During Visual Sentences Justification

3¡¢A Method for Estimating Initial Conditions of Coupled Map Lattices Based on Time-Varying Symbolic Dynamics

4¡¢Initial condition estimate of coupled map lattices system based on symbolic dynamics

5¡¢Chaos Dynamics Modeling Based On Multiple Wavelet Neural Network And Its Application

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³æÓÑÃÇ£¬Çë°ïæ²éÕâһƪ£ºRecovery of statistical property of initial conditions based on time-varying parameter from coupled map lattices
9Â¥2010-06-04 20:03:05
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lxj_zk

Òø³æ (СÓÐÃûÆø)

FN ISI Export Format
VR 1.0
PT  S
AU  Shen, MF
Chang, GL
Wang, SW
Beadle, PJ
AF  Shen, Minfen
Chang, Guoliang
wang, Shu Wang
Beadle, Patch J.
ED  Wang, J; Yi, Z; Zurada, JM; Lu, BL; Yin, H
TI  Nonlinear dynamics of EEG signal based on coupled network lattice model
SO  ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS
SE  LECTURE NOTES IN COMPUTER SCIENCE
LA  English
DT  Proceedings Paper
CT  3rd International Symposium on Neural Networks (ISNN 2006)
CY  MAY 28-31, 2006
CL  Chengdu, PEOPLES R CHINA
SP  Univ Electr Sci & Technol China, Chinese Univ Hong Kong, Asia Pacific Neural Network Assembly, European Neural Network Soc, IEEE Circuits & Syst Soc, IEEE Computat Intelligence Soc, Int Neural Network Soc, Natl Nat Sci Fdn China, KC Wong Educ Fdn Hong Kong
ID  MAP LATTICE; DIMENSION
AB  EEG signals were expressed as the typical non-stationary signal. More and more evidences were found that both EEG and ERP signals are also chaotic signal from the nonlinear dynamics system. A novel model based on the time-varying coupled map lattice model is proposed for investigating the nonlinear dynamics of EEG under specified cognitive tasks. Moreover, the time-variant largest Lyapunov exponent (LLE) is defined for the purpose of defining quantitative parameters to reveal the global characters of system and extract new information involved in the system. Both simulations and real ERP signals were examined in terms of LLE parameter for studying the signal's dynamic structure. Several experimental results show that the brain chaos changes with time under different attention tasks of the information processing. The influence of the LLE with the different attention tasks occurs in P2 period.
C1  Guangdong Univ Technol, Coll Informat Engn, Guangzhou, Peoples R China.
Shantou Univ, Key Lab Image Proc, Guangdong, Peoples R China.
Univ Portsmouth, Sch Syst Engn, Portsmouth, Hants, England.
RP  Shen, MF, Guangdong Univ Technol, Coll Informat Engn, Guangzhou, Peoples R China.
EM  mfshen57@vip.163.com
NR  9
TC  0
PU  SPRINGER-VERLAG BERLIN
PI  BERLIN
PA  HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
SN  0302-9743
BN  3-540-34482-9
J9  LECT NOTE COMPUT SCI
PY  2006
VL  3973
BP  560
EP  565
PG  6
SC  Computer Science, Theory & Methods
GA  BET87
UT  ISI:000239485300082
2Â¥2010-06-04 16:22:04
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lxj_zk

Òø³æ (СÓÐÃûÆø)

FN ISI Export Format
VR 1.0
PT  J
AU  Minfen, S
Ting, KH
Fung, PWC
Chan, FHY
AF  Minfen, S.
Ting, K. H.
Fung, P. W. C.
Chan, F. H. Y.
TI  Dynamic synchrony analysis of erp during visual sentences justification
SO  BRAIN AND COGNITION
LA  English
DT  Meeting Abstract
C1  Shantou Univ, Ctr Sci Res, Shantou, Guangdong, Peoples R China.
NR  0
TC  0
PU  ACADEMIC PRESS INC ELSEVIER SCIENCE
PI  SAN DIEGO
PA  525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA
SN  0278-2626
J9  BRAIN COGNITION
JI  Brain Cogn.
PD  OCT
PY  2006
VL  62
IS  1
BP  86
EP  87
PG  2
SC  Neurosciences; Psychology, Experimental
GA  096HT
UT  ISI:000241368900036
3Â¥2010-06-04 16:23:33
ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû

lxj_zk

Òø³æ (СÓÐÃûÆø)

FN ISI Export Format
VR 1.0
PT  J
AU  Shen, MF
Liu, Y
Lin, LX
AF  Shen Min-Fen
Liu Ying
Lin Lan-Xin
TI  A method of estimating initial conditions of coupled map lattices based on time-varying symbolic dynamics
SO  CHINESE PHYSICS B
LA  English
DT  Article
DE  coupled map lattices; symbolic dynamics; initial condition estimation
ID  CHAOTIC SIGNAL ESTIMATION
AB  A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices (CMLs). The presented method combines symbolic dynamics with time-varying control parameters to develop a time-varying scheme for estimating the initial condition of multi-dimensional spatio temporal chaotic signals. The performances of the presented time-varying estimator in both noiseless and noisy environments are analysed and compared with the common time-invariant estimator. Simulations are carried out and the obtained results show that the proposed method provides an efficient estimation of the initial condition of each lattice in the coupled system. The algorithm cannot yield an asymptotically unbiased estimation due to the effect of the coupling term, but the estimation with the time-varying algorithm is closer to the Cramer-Rao lower bound (CRLB) than that with the time-invariant estimation method, especially at high signal-to-noise ratios (SNRs).
C1  [Shen Min-Fen; Lin Lan-Xin] Shantou Univ, Coll Engn, Shantou 515063, Peoples R China.
[Liu Ying] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China.
RP  Shen, MF, Shantou Univ, Coll Engn, Shantou 515063, Peoples R China.
EM  mfshen@stu.edu.cn
FU  National Natural Science Foundation of China [60271023, 60571066]; Natural Science Foundation of Guangdong Province, China [5008317, 7118382]
FX  Project supported by the National Natural Science Foundation of China (Grant Nos 60271023 and 60571066) and the Natural Science Foundation of Guangdong Province, China (Grant Nos 5008317 and 7118382).
NR  19
TC  0
PU  IOP PUBLISHING LTD
PI  BRISTOL
PA  DIRAC HOUSE, TEMPLE BACK, BRISTOL BS1 6BE, ENGLAND
SN  1674-1056
J9  CHIN PHYS B
JI  Chin. Phys. B
PD  MAY
PY  2009
VL  18
IS  5
BP  1761
EP  1768
PG  8
SC  Physics, Multidisciplinary
GA  451GD
UT  ISI:000266457800008
4Â¥2010-06-04 16:25:20
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