查询词典 proved

It can be proved mathematically that the associated approximation error in the proposed approach is of details omitted due to lack of space

它算术地可能被在被计画的方式中的联合近似值错误是细节省略预定空间缺乏

Then for discrete time single-input single-output system,a theorem of Hankel-norm approximation is proposed and proved.

相反，有限脉冲响应滤波器可以得到严格的线性相位，但是要获得一定的选择性则信号时延较大。

And then, the GFNN (generalized fuzzy neural network) is put forwand, the GFNN approximation theorem is proved.

从非线性系统本身的物理背景出发，根据系统本身的内在特性、先验知识和经验建立系统辨识模型，提出了广义模糊神经网络。

By using the interpolation mechanism of fuzzy system, an approach of building the series of fuzzy systems, which can uniformly approximate any continuous function on a compact domain to any accuracy, is given, and then the universal approximation theorem is generally proved.

利用模糊系统的插值模型来代替被控对象的真实模型，设计了一个自适应模糊控制策略；为保证系统的全局稳定性，增加了一个补偿控制律，它是根据模糊系统的逼近误差估计量来设计的，因此这里系统跟踪误差的收敛性不依赖于模型最小误差的平方可积性[70，71]。

The approximation theorem of the rough neural network is proved. Then the method is applied to the fault verification of fighter plane, the simulation results show that the rough neural network is efficient.

最后将此方法应用于歼击机的故障认定系统，仿真结果表示，此粗糙神经网络可以很好地对具有区间数的歼击机故障认定系统进行故障认定。

To cousider the least,we have to establish these facts under some comparablystrong but not the most proper conditions.From [12] and [13],if we suppose thatfis Lipschitz continuous in t,then all the above conditions(H1)-(H3) canbe established to a class of approximating problems of (1)(2).So the followingtheorem can be proved by theorem 5 through approximation process.

这时，我们只好"退而求其次"，在较强的"看来不是最适当的条件"下，来建立这些事实，从[12]和[13]中我们看到，只要加上"〓对t为Lipschitz连续"，则对（1）（2）的逼近问题族，上述条件（H1）-（H3）都可建立起来，从而，通过逼近过程，用定理5就可得到如下的定理。

Wang-type fuzzy logic system and its functional approximation ability are researched deeply, A class of Gauss-type fuzzy logic system is presented and studied What it defers from Wang-type fuzzy logic system is its using Gauss fuzzifier The analytical expression of this fuzzy logic system is derived detailed Its universal approximation theorem for nonlinear functions is proved by StoneWeiestrass theorem.

通过对两类模糊系统作为非线性辨识器的仿真研究显示出高斯型模糊逻辑系统在抗数据干扰方面比Wang型模糊系统有优势。对非线性动态系统的辨识问题，借助递归神经网络的研究成果，提出一种基于递归网络结构的自适应模糊逻辑系统和参数学习算法。

By the best approximation theory, it is first proved that the SISO (single-input single-output) linear Takagi-Sugeno fuzzy systems can approximate an arbitrary polynomial which, according to Weierstrass approximation theorem, can uniformly approximate any continuous functions on the compact domain.

借助于最优逼近理论，证明了线性SISO TS模糊系统可以逼近任意一个多项式，然后以Weierstrass逼近定理为桥梁，证明了该模糊系统可以以任意精度逼近一个任意的连续函数，从而得到了该模糊系统万能逼近性的一个新的充分条件。

This paper presents that FCP network model and improved T-S model used in the disquisition are universal approximator, with the latter proved.

本文指出文中用到的FCP网络模型和改进T-S模型为通用逼近器，同时给出后者的证明。

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］。

As she looked at Warrington's manly face, and dark, melancholy eyes, she had settled in her mind that he must have been the victim of an unhappy attachment.

每逢看到沃林顿那刚毅的脸，那乌黑、忧郁的眼睛，她便会相信，他一定作过不幸的爱情的受害者。

Maybe they'll disappear into a pothole.

也许他们将在壶穴里消失