Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
Copyright © 2013 Xian Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The problem of analyzing and controlling epileptiform spikes in a class of
neural mass models is concerned with. Since the
measured signals are always contaminated by measurement noise, an algebraic
estimation method is utilized to observe the state from the noisy measurement. The feedback control is constructed via the estimated state. The feasibility of using such a strategy to control epileptiform spikes in a regular network of coupled neural
populations is demonstrated by simulations. In addition, the
influence of the type of the controlled populations, the number of
the controlled populations, and the control gain is
investigated in details.