同时，考虑到路面扰动输入对悬架控制的重要影响，建立出积分白噪声形式的路面不平度数学模型及正弦激励模型。
Considering the influence of the input disturbance, a mathematical description of road surface irregularity is established, which is the model of integral white noise and inspire with sine wave.
在仿真试验中，比较了给定功率阶跃扰动信号、白噪声信号及伪随机信号分别作为输入信号进行辨识的结果。
In simulation experiment, results of identifying models using step disturbance of given power signal, white noise signal, and pseudorandom signal as input signals have been compared.
向重建模型中输入高斯噪声进行扰动分析，这样有利于对不确定性的评定。
Gaussian noise is added to the reconstruction model for perturbation analysis using synthetic images, thus is helpful for uncertainty evaluation.
在辨识实际系统时，非平稳噪声扰动是较多见的。
The systems disturbed by nonstationary noise are often encountered in the practical identification.
设计出的自适应逆控制系统，不仅可以得到好的动态响应，还可以使噪声和扰动减小到最小。
We can not only obtain good dynamic response, but also make the influence of noise and disturbance to the minimum.
阐述了加性噪声扰动的广义M集的物理意义。
The physical meaning of the additive noise perturbed generalized M sets was expounded.
减背景操作后，用形态学方法和检测连通域面积进行后处理，消除噪声和背景扰动带来的影响；
After the threshold operation, morphologic operation and connected region area measurement are introduced to solve the background disturbance problem.
最后，针对输入扰动和量测噪声不同的广义系统提出了一种新的观测器设计方法，讨论了噪声对误差的影响。
Finally, for descriptor systems with different input disturbances and measurement noises, we get a new observer method, and give a discussion about the effect of the noises to the error.
研究了系统固有频率受二值噪声扰动时，调制二值噪声驱动二阶过阻尼线性系统的随机共振现象。
The phenomena of stochastic resonance of an over-damped second-order linear system with modulated dichotomous noise are investigated.
通过在回路中对噪声进行预测，有效地补偿了数字反馈回路造成的噪声信号的延迟，从而改善了系统的扰动控制性能。
By predicting the noise in the loop the delay of noise signal in digital feedback loop is compensated effectively, thus the control capability of the system on disturbance is enhanced.
采用小波软阈值去噪方法对信号噪声进行预处理，很大程度地减小了噪声对扰动检测的干扰。
Wavelet soft-threshold de-noising method was applied to preprocess the noisy signal, and the noise interference in disturbance detection was reduced to a great extent.
采用小波软阈值去噪方法对信号噪声进行预处理，很大程度地减小了噪声对扰动检测的干扰。
Wavelet soft-threshold de-noising method was applied to preprocess the noisy signal, and the noise interference in disturbance detection was reduced to a great extent.
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