| ²é¿´: 1797 | »Ø¸´: 10 | |||
| µ±Ç°Ö»ÏÔʾÂú×ãÖ¸¶¨Ìõ¼þµÄ»ØÌû£¬µã»÷ÕâÀï²é¿´±¾»°ÌâµÄËùÓлØÌû | |||
yingo8577гæ (СÓÐÃûÆø)
|
[½»Á÷]
³æÓÑÃÇ£¬Çë°ïæSCI\ISTPµÄ¼ìË÷ºÅ ÒÑÓÐ3È˲ÎÓë
|
||
|
SCI\ISTP¼ìË÷µÄ·½·¨£¨Õª×ÔÍøÉÏ£©£º (1). µÇ½http://www.isiknowledge.com/ (2). ÊäÈëÒª²éÕÒµÄÎÄÕÂÃû×Ö£¨¿ÉÒÔ²¿·ÖÊäÈ룩£¬µã»÷search (3). ÔÚËÑË÷½á¹ûÀïÃæ£¬µã»÷web of scienceͼ±ê»òÕßcurrent contents connectͼ±ê»òISI proceedingͼ±ê (4). ÔÚеÄÒ³ÃæÀïѰÕÒIDS Number ¼´¿É Çë³æÓÑÃǰïæ²éѯһÏÂÒÔÏÂÎåÆªÎÄÕµļìË÷ºÅ£¬¼±Óã¬Ô½ÏêϸԽºÃ¡£·Ç³£¸Ðл¡£ 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 ÒòΪ£¬ÎÒÕâ±ßû·¨µÇ½¸ÃÍøÕ¾£¬ËùÒÔÖ»ºÃÇë´ó¼Ò°ïæÁË£¬ÔٴθÐл [ Last edited by yingo8577 on 2010-6-4 at 15:03 ] |
» ²ÂÄãϲ»¶
Ò»Ö¾Ô¸»ªÖпƼ¼´óѧ071000£¬Çóµ÷¼Á
ÒѾÓÐ4È˻ظ´
ÉúÎïѧһ־Ը985£¬·ÖÊý349Çóµ÷¼Á
ÒѾÓÐ4È˻ظ´
ÉúÎïѧµ÷¼Á
ÒѾÓÐ4È˻ظ´
Çóµ÷¼ÁԺУÐÅÏ¢
ÒѾÓÐ4È˻ظ´
085600²ÄÁÏÓ뻯¹¤306
ÒѾÓÐ4È˻ظ´
286Çóµ÷¼Á
ÒѾÓÐ10È˻ظ´
328Çóµ÷¼Á£¬Ó¢ÓïÁù¼¶551£¬ÓпÆÑоÀú
ÒѾÓÐ9È˻ظ´
Ò»Ö¾Ô¸±±¾©»¯¹¤´óѧ070300 ѧ˶336Çóµ÷¼Á
ÒѾÓÐ4È˻ظ´
286·ÖÈ˹¤ÖÇÄÜרҵÇëÇóµ÷¼ÁÔ¸Òâ¿ç¿¼£¡
ÒѾÓÐ8È˻ظ´
×ÊÔ´Óë»·¾³ µ÷¼ÁÉêÇë(333·Ö)
ÒѾÓÐ5È˻ظ´
» ±¾Ö÷ÌâÏà¹Ø¼ÛÖµÌùÍÆ¼ö£¬¶ÔÄúͬÑùÓаïÖú:
¡¾½Ì³Ì¡¿¹úÍâÈý´óË÷Òý SCI¡¢EI¡¢ISTP ¼ìË÷·½·¨Óë¼¼ÇÉ
ÒѾÓÐ1590È˻ظ´
sciºÍistpµÄ¼ìË÷ºÅÊDz»ÊDZäÁË£¿
ÒѾÓÐ5È˻ظ´
SCI(E)ÊÕ¼µÄ¼ìË÷ºÅµ½µ×ÊÇÄÄÒ»Ïî°¡£¬»¹ÓÐSCIºÍISTPÔõô´Ó¼ìË÷ºÅÀ´Çø·Ö£¿
ÒѾÓÐ12È˻ظ´
ÈçºÎÇø±ðSCI¼ìË÷ºÅºÍISTP¼ìË÷ºÅ£¿
ÒѾÓÐ13È˻ظ´
°ïÃ¦Çø·ÖÒ»ÏÂISTPºÍSCIÊÕ¼ºÅµÄÇø±ð£¬¿´Ò»ÏÂÕâ¸ö½á¹ûÊÇʲô¼ìË÷
ÒѾÓÐ6È˻ظ´
ÖØ½ðÇë°ï¿´Á½ÆªÎÄÕÂÊÇ·ñSCI¼°ISTP¼ìË÷
ÒѾÓÐ11È˻ظ´
ÇëÎÊÏÂÈý´ó¼ìË÷SCI£¬EI£¬ISTPÖеÄISTPÊÇʲô£¿ÓÐûÓпÉÄÜÂÛÎÄͬʱ±»Èý¸ö¼ìË÷¼ìµ½£¿
ÒѾÓÐ6È˻ظ´
ÆÈÇÐÏ£ÍûºÃÐÄÈ˰ï²é goldschmidt 2010 »áÒé 6Ô¿ªµÄ ISTP »òSCI ¼ìË÷ûÓÐ
ÒѾÓÐ5È˻ظ´
¡¾2010-7-11¡¿¡¾ÄÏÄþ,Öйú¡¿CIS 2010¼ÆËãÖÇÄÜÓ밲ȫ¹ú¼Ê»áÒéÕ÷ÎÄ(SCI/EI/ISTP¼ìË÷)
ÒѾÓÐ4È˻ظ´
תÌû£ºSCI¡¢SSCI¡¢EI¡¢ISTP¡¢CSSCI¡¢CSCD¼ò½é
ÒѾÓÐ28È˻ظ´
yingo8577
гæ (СÓÐÃûÆø)
- Ó¦Öú: 0 (Ó×¶ùÔ°)
- ½ð±Ò: 163.6
- ºì»¨: 1
- Ìû×Ó: 162
- ÔÚÏß: 24.3Сʱ
- ³æºÅ: 605089
- ×¢²á: 2008-09-17
9Â¥2010-06-04 20:03:05
lxj_zk
Òø³æ (СÓÐÃûÆø)
- Ó¦Öú: 2 (Ó×¶ùÔ°)
- ½ð±Ò: 1809.6
- É¢½ð: 68
- Ìû×Ó: 272
- ÔÚÏß: 149.8Сʱ
- ³æºÅ: 719152
- ×¢²á: 2009-03-10
- רҵ: Á÷ÌåÁ¦Ñ§
|
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
lxj_zk
Òø³æ (СÓÐÃûÆø)
- Ó¦Öú: 2 (Ó×¶ùÔ°)
- ½ð±Ò: 1809.6
- É¢½ð: 68
- Ìû×Ó: 272
- ÔÚÏß: 149.8Сʱ
- ³æºÅ: 719152
- ×¢²á: 2009-03-10
- רҵ: Á÷ÌåÁ¦Ñ§
|
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
lxj_zk
Òø³æ (СÓÐÃûÆø)
- Ó¦Öú: 2 (Ó×¶ùÔ°)
- ½ð±Ò: 1809.6
- É¢½ð: 68
- Ìû×Ó: 272
- ÔÚÏß: 149.8Сʱ
- ³æºÅ: 719152
- ×¢²á: 2009-03-10
- רҵ: Á÷ÌåÁ¦Ñ§
|
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













»Ø¸´´ËÂ¥