TY - GEN
T1 - Desynchronization of the chaotic-bursting neuronal ensemble based on LaSalle invariant principle
AU - Che, Yanqiu
AU - Li, Ruixue X.
AU - Yang, Tingting T.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - In this paper, an adaptive control scheme is presented for the desynchronization of a neuronal population based on LaSalle invariant principle. This control can asymptotically stabilize the mean field of the popolation at a fixed point to achieve desynchronization. A realistic model described by Hindmarsh-Rose equations is chosen as our example. The simulation results demonstrate the effectiveness of the proposed control scheme.
AB - In this paper, an adaptive control scheme is presented for the desynchronization of a neuronal population based on LaSalle invariant principle. This control can asymptotically stabilize the mean field of the popolation at a fixed point to achieve desynchronization. A realistic model described by Hindmarsh-Rose equations is chosen as our example. The simulation results demonstrate the effectiveness of the proposed control scheme.
UR - http://www.scopus.com/inward/record.url?scp=84886443240&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84886443240&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/AMM.427-429.1109
DO - 10.4028/www.scientific.net/AMM.427-429.1109
M3 - Conference contribution
AN - SCOPUS:84886443240
SN - 9783037858905
T3 - Applied Mechanics and Materials
SP - 1109
EP - 1112
BT - Mechanical Engineering, Industrial Electronics and Information Technology Applications in Industry
T2 - 2nd International Conference on Mechanical Engineering, Industrial Electronics and Informatization, MEIEI 2013
Y2 - 14 September 2013 through 15 September 2013
ER -