研究证明，小波神经网络所建立的非线性误差校正模型有较好的预测效果，能够有效地预测非线性经济系统。
The results validate more validity of nonlinear error correction model on the wavelet neural network than linear vector autoregressive model, and forecast validly the nonlinear economy system.
提出了传感器非线性误差校正的径向基函数(RBF)神经网络方法，并与采用BP神经网络校正非线性误差进行了比较。
The method of radial basis function neural network (RBFNN) is given to correct the nonlinear errors of the sensors. A BP neural network has been developed to solve the same problem for comparison.
介绍了径向基函数网络的函数逼近原理和方法，提出了一种基于广义回归神经网络（GRNN）的传感器非线性误差校正方法。
The RBF network function approximation theory and method are introduced, and the method of nonlinear error correction of sensor is presented based on generalized regression neural network(GRNN).
与传统的线性自动校正算法相比，这种算法可以有效地消除矢量地图中的非线性误差，理论上也有所深入。
Compared to the traditional linear auto-adjusting algorithm, it can effectively remove the nonlinear errors of a vector map and also runs deep on theory.
指出并非对任意非线性协整系统，都存在误差校正模型的表现形式。
The research results show that the error—correcting model may not exist in arbitrary non—linear cointegration system .
以距离传感器为例，将基于BP神经网络的校正方法应用于减少距离传感器的非线性输出误差。
As an example, a correction method based on BP is applied to reduce the nonlinear output errors of range sensors.
应用线化和校正方法，研究了单摆的非线性振动，作出了周期比和相对误差随摆角的变化曲线。
The vibration of the nonlinear pendulum is studied by means of linearization and correction method, the curves of the period ratio and the relative error is plotted.
计算结果表明，这种方法对线性和非线性问题都具有良好的效果，在侦破出过失误差的同时，可得到相应的数据校正结果。
The calculation results show that the approach provides good reconciled data, and at same time, can correctly identify gross errors for both linear and nonlinear systems.
提出了一种用支持向量机校正传感器非线性误差的原理和方法。
Principle and method of correcting nonlinear error of sensors based on the support vector machine is given.
为减少检测系统的测量误差，在自动检测系统中需要对非线性误差进行校正。
In order to reduce the measuring error of automatic detection systems, it is needed to adjust the nonlinear error for automatic detection systems.
为保证测量精度，应对非线性误差进行校正。
To ensure accuracy, the nonlinear error should be calibrated.
然而由于响应率的非线性和噪声等原因两点线性校正后仍然存在误差。
However, nonlinearity of the responsibility and noise result in the nonuniformity error.
然而由于响应率的非线性和噪声等原因两点线性校正后仍然存在误差。
However, nonlinearity of the responsibility and noise result in the nonuniformity error.
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