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Fuzzy adaptive unscented Kalman filter control of epileptiform spikes in a class of neural mass models

机译:一类神经质量模型中癫痫样峰的模糊自适应无味卡尔曼滤波控制

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摘要

Anewclosed-loop controlmethod based on the fuzzy adaptive unscented Kalman filter (FAUKF) is proposed to suppress epileptiform spikes in a class of neural mass modelswith uncertain measurement noise. The FAUKF is used to estimate the nonlinear system states of the underlying models and amend measurement noise adaptively. The control law is constructed via the estimated states. Numerical simulations illustrate the efficiency of the proposed method.
机译:提出了一种基于模糊自适应无味卡尔曼滤波器(FAUKF)的新型闭环控制方法,以抑制一类不确定测量噪声的神经质量模型中的癫痫样尖峰。 FAUKF用于估计基础模型的非线性系统状态,并自适应地修改测量噪声。控制律是通过估计状态构建的。数值仿真表明了该方法的有效性。

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