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approximator相关的网络例句

查询词典 approximator

与 approximator 相关的网络例句 [注:此内容来源于网络,仅供参考]

The Universal approximator and the universal controller are introduced.

针对模糊控制系统提出通用逼近子与通用控制器概念。

The characteristics of B|spline basis function is first discussed, based on which B|spline neural network is proved to be a universal approximator.

1引言对于一个给定的非线性函数,我们都知道用神经网络可以以任意的精度来逼近它,原因就是神经网络是全局逼近器[1]。

The states of system and the faults in system are estimated simultaneously. The inputs of the fault approximator are the estimated states.

首先提出一种状态估计器设计方法;然后在进行状态估计的同时用RBF神经网络来逼近系统所发生的故障。

Finally a generalized fuzzy hyperbolic model is proposed, which is proven to be a universal approximator, and two identification algorithms are derived.

最后提出一种广义模糊双曲正切模型,并证明了此模型具有全局逼近性。

After associating with the fuzzy neural network approximator and performance, the controller performs as well as the sliding mode controller and meanwhile smooth the control actions.

在引入模糊类神经网路近似器及概念后维持了系统的强健性及改善了系统控制输入的切跳现象。

A SVM approximator is constructed to monitor the behavior of dynamic system according to in-suit learning of the nonlinear fault function.

主要通过在线学习故障特性对系统进行监测,利用SVM的ε-不敏感损失函数控制SVM的输出,抑制模型不确定性的影响,从而提高故障诊断系统的鲁棒性。

By this way, the obstacles are removed for the research on the theoretical problems of adaptive fuzzy logic system in a unitary frame, for instance the problem of the general fuzzy logic system as universal approximator of nonlinear function.

在概念上明确了专家信息的本质特征可以看作是来自语言的模糊信息,为通过自适应模糊逻辑系统对专家信息的研究和利用打开了通道。

The common assumptions on the time-delays of the system are not required; only one fuzzy approximator is needed for compensating all the unknown functions. Thus, the structure of the controller is simplified.

该方法取消了对系统时滞常做的假设,仅采用一个模糊逼近器便使所有的未知函数得到补偿,简化了控制器的结构。

One of the key issues in the design of fault diagnosis scheme is the effect of modelling uncertainties and disturbances. By using neural networks observer or approximator, the fault detection and diagnosis strategy for a class of nonlinear systems with modelling uncertainties are investigated.

而非线性系统故障诊断算法的鲁棒性则是一个极其关键的问题,本文主要针对非线性系统,进行了基于神经网络的鲁棒故障诊断方法研究。

Using the RBF neural network approximator, the main assumption of the first approach is that the minimal approximation errors satisfy certain bounding conditions.

利用RBF神经网络逼近器,第一种方法主要的假设是最小逼近误差满足确定有界条件。

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