approximation error中文是什么意思

• 逼近误差
• 近拟误差
• 近似误差

• approximation    n. 1.接近；近似。 2.【数学】近似值。 3.概算， ...
• error    n. 1.错误；失错。 2.谬见，误想；误信；误解。 3 ...
• error of approximation    近似误差
• integral square error approximation    积分平方误差近似
• least square error approximation    最小二乘方逼近; 最玄乘方逼近
• minimum-squared-error approximation    最小方差近似; 最薪差近似
• approximation    n. 1.接近；近似。 2.【数学】近似值。 3.概算，略计。 successive approximations 逐次近似计算法。 be a very close approximation to 很接近于…。
• approximation approximation    近似，逼近
• be in error    弄错了
• by error    错误地
• error    n. 1.错误；失错。 2.谬见，误想；误信；误解。 3.罪过。 4.【数学】误差；【法律】误审，违法；(棒球中的)错打。 commit [make] an error 犯[出]错。 correct errors 改正错误。 a clerk's [clerical] error 笔误。 mean errors 标准误差。 a writ of error 【法律】(推翻错误原判的)再审命令。 nature's error 天生畸形。 in error 弄错了的；错误地。 errors of commission [omission] 违犯[疏忽]罪。 fall into error 误入歧途。 nature's error 天生畸形。 adj. -less 无错误的，正确的。
• in error    弄错了的；错误地
• no error    无差错, 无错误; 无失误
• acoustic approximation    声学近似
• adiabatic approximation    绝热近似法
• allowable approximation    容许近似值
• alternative approximation    交互近似法
• analog approximation    模拟近似
• analytical approximation    解析近似
• approx approximation    近似.略计
• approximation algorithm    近似算法
• approximation algorithms    第三十五章 近似算法
• approximation and correction    近似与校正
• approximation andcorrectionon    近似与校正
• approximation by excess    过剩逼近

• Firstly , based on backstepping and the supervisory control strategy , a robust adaptive fuzzy controller is designed for a class of nonlinear systems . the first type fuzzy logic system is used to approximate the unknown part of the process . the adaptive compensation term of the optimal approximation error is adopted
  本文首先针对一类不确定非线性系统，基于backstepping方法，利用监督控制，引入最优逼近误差的自适应补偿项，并利用型模糊逻辑系统逼近系统的未知部分，提出了一种鲁棒自适应模糊控制器设计方案，运用李亚普诺夫第二方法，先证明了闭环模糊控制系统全状态有界，再证明了跟踪误差收敛到零。
• Secondly , based on a modified supervisory control strategy and the approximation capability of generalized multilinear fuzzy logic systems ( gmfls ) , a new scheme called model reference adaptive fuzzy control ( mrafc ) for a class of siso nonlinear systems is proposed , the external disturbances and the approximation error are considered
  其次针对一类具有siso的不确定非线性系统，同时考虑外界干扰和建模误差，基于一种修改的监督控制方案并利用广义多线性模糊逻辑系统的逼近能力，提出一种模型参考自适应模糊控制器设计的新方案。
• Abstract : in this paper a new identification model constructed by neural networks with modified inputs and stable filters is presented for continuous time nonlinear systems in order to reduce the inherent network approximation errors . an adaptive law with projection algorithm is employed to adjust the parameters of networks . under certain conditions , convergence of the identification error is proved
  文摘:在用神经网络进行系统建模时，建模误差的存在是难免的.为了减小这种误差，本文对连续时间非线性系统提出了一种新的神经网络辨识模型，它是由带有输入修正的神经网络和稳定滤波器组合而成.文中给出了权值的学习算法，即权值是根据辨识误差的投影算法来改变，证明了在一定条件下辨识误差的收敛性
• Because the extension of dynamic change in weak nonlinear system is not large , the robust reliable controller designed by ldi can make the whole controlled system stable when time lag and faults exit in the system , at the same time , satisfying robust performance index of the system . next , considered that the approximation error produced by ldi , the unmodeling error produced by system , the parameter uncertainties and the external disturbances can not be ignored , a dynamic neural network controller is designed to compensate their effect on line . adjusted by the state output error between the ideal model and the controlled system , the cooperation of on - line network compensator and linear h _ ( ) controller of ideal model makes the whole close - loop system guar antee robust stability and track the specified signal well
  本文在基于线性微分包含( ldi )的技术基础上，提出了两种非线性系统的鲁棒控制方法，首先讨论了一类弱非线性时滞控制系统中的鲁棒可靠控制器设计问题，由于弱非线性系统本身的动态变化范围不大，在确保整个系统鲁棒性能指标的前提下，当系统存在时滞和故障时，通过ldi设计出的鲁棒可靠控制器可以镇定整个被控系统；其次，在考虑运用ldi技术产生的逼近误差、系统本身的未建模误差及参数不确定性以及外部扰动的影响不能被忽略的情况下，设计了在线补偿这部分影响的动态神经网络控制器，在理想模型和被控系统状念输出误差的调节作用下，在线神经网络补偿器与理想模型的线性h _控制器相互配合，使得整个闭环系统既可以保证鲁棒稳定性又能够跟踪给定的指令信号。
• Adaptive bounding technique is used to deal with unknown boundedness of approximation errors . the arbitrary output tracking accuracy is achieved by tuning the design parameters . thirdly , based on the results in chapter 3 , two design approaches of adaptive iterative learning control ( ailc ) are proposed for two classes of parametric nonlinear time - delay systems
  神经网络用于逼近未知的非线性时滞函数，当状态不可测时，采用时滞滤波器估计系统状态，利用backstepping技术设计权值自适应律和控制律，占优化方法处理时滞基函数，自适应界化技术处理逼近误差的未知上界，通过调节设计参数可以实现对目标轨线任意精度的跟踪。
• In this approach , the neural network is used to learning the nonlinear function of the system . the network weights are derived using lyapunov - based design and are adapted on - line . due to the existence of neural network approximation error and external disturbance , the sliding mode control which is insensitive to disturbance and parameter pertabation is used to achieve robust tracking for the system
  该方法利用神经网络学习系统中的非线性函数，神经网络的权值由lyapunov稳定性理论导出，并且在线调整；考虑到网络逼近误差和外部干扰的存在，文中利用滑动模态对参数和扰动不敏感的特点，实现了系统的鲁棒输出跟踪。
• This paper researches the numeric approximation characteristic of series - parallel fuzzy system and points out that the number of fuzzy rules should not exceed the number of the samples . in addition , the influence of approximation error and system initial error on the performance of the series - parallel fuzzy system is also investigated
  本文研究了串并联方式模糊系统的数字逼近特性，得出结论：当模糊规则数等于样本数时，已经可以实现精确插值，因此模糊规则条数不能超过样本数目，否则将冗余，并可能引起振荡，削弱模糊系统的泛化能力。

• approximation errorとは意味：近似誤差｛きんじ ごさ｝