Anew method to pulp consistency sensor nonlinear estimation and dynamic calibration based on artificial neural networks is proposed.
本文提出了一种基于人工神经网络的纸浆浓度传感器非线性估计和动态标定新方法。
When the Angle modulation signals made up of the message model have passed through a randomly time-varying channel, a complex nonlinear estimation model is formed.
当此消息模型构成的角调信号通过随机时变信道后，形成复杂的非线性估计模型。
Unscented Kalman Filter (UKF), which is an evolutional algorithm of Extended Kalman Filter (EKF), has been successfully applied in many nonlinear estimation problems.
无轨迹卡尔曼滤波器(ukf)作为扩展卡尔曼滤波器(ekf)的进化算法在许多非线性估计问题上取得了成功的应用。
Unscented Kalman Filter (UKF), which is an evolutional algorithm of Extended Kalman Filter (EKF), has been successfully applied in many nonlinear estimation problems.
无轨迹卡尔曼滤波器(ukf)作为扩展卡尔曼滤波器(ekf)的进化算法在许多非线性估计问题上取得了成功的应用。
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