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UKF-based key-parameters compensation control for abnormal firing in PR model

机译:基于UKF的PR模型异常触发的关键参数补偿控制

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摘要

Abnormal firing of neurons is often caused by the abnormality of one or more parameters. These parameters can't be measured in actual physical experiment, but can be estimated with estimator. Brain is a complex nonlinear system with a large amount of noise. UKF (Unscented Kalman Filter) is a good choice to estimate the parameters of nonlinear system. In this paper we design a compensation control based on UKF to recover the morbid system. Take the deviation between the estimated and the standard parameters as control signal and use this signal to control the firing state of the neurons. It is found that our control can eliminate the abnormal firing caused by two or more abnormal parameters.
机译:神经元异常放电通常是由一个或多个参数异常引起的。这些参数无法在实际的物理实验中测量,但可以使用估算器估算。脑是具有大量噪声的复杂非线性系统。 UKF(无味卡尔曼滤波器)是估计非线性系统参数的理想选择。在本文中,我们设计了一种基于UKF的补偿控制来恢复病态系统。将估计参数与标准参数之间的偏差作为控制信号,并使用该信号来控制神经元的放电状态。发现我们的控制可以消除由两个或多个异常参数引起的异常触发。

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