查询词典 interior approximation

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。

Since the structure self-organization and self-learning abilities of GFNN, it is different from the universal approximation theorem of FLS and BP theorem of NN.

由于GFNN的结构自组织和参数自学习能力，使得它与模糊逻辑系统中的万能逼近定理以及人工神经网络的BP逼近定理不同，GFNN不再只是一个存在性定理，它给出了GFNN的实现过程。

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]。

Main foundation is the approximation theorem of completely continuous operators and the Guo-Krasnosel' skii fixed point theorem of cone expansion-compression type.

主要工具是全连续算子的逼近定理和锥拉伸与锥压缩型的Guo-Krasnosel' skii不动点定理。

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。

Thirdly, for Bernstein-Durrmeyer-Bezier operators, we have given the approximation equivalent theorem in L_p(1 ≤ p≤∞).

三、我们给出了Bernstein-Durrmeyer-Bézier算子于L_p(1≤p≤∞)空间中逼近的等价定理。

In this paper, we use the coupled fixed point theorem for mixed monotone condensing operators to obtain an existence, uniqueness and iterative approximation theorem of solutions of initial value problems for second order mixed monotone type of impulsive differential equations.

利用混合单调凝聚算子的耦合不动点定理，给出了二阶混合单调型脉冲微分方程的初值问题的解的存在唯一性及迭代逼近定理。

Proposed in the paper are the ordered monotony property of MFNNs when the transfer function is monotone, the continuous mapping theorem, and non approximation theorem to function.

给出了单调传递函数的 MFNNs按序单调特性、连续映射定理以及非函数一致逼近定理。

Using the information consistency principle, the first step of the algorithm transforms the identification problem into a constrained convex programming ,the result of which is then used ,in the second step, to approximate systems in the uncertainty set to obtain the identified nominal model based on a polynomial approximation theorem.

第一步通过信息一致性原理把辨识问题转化为受限凸规划问题，第二步利用一个多项式逼近定理在第一步结果基础上，对不确定集中的系数进行逼近，得到辨识出的名义模型。

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。

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"第二次生命是显着容易的工作，并且很受欢迎，"

For example, we usually assume that materials are homogeneous and isotropic and free of internal defects or flaws.

为了得到适合有限元分析的模型，我们必须经过如图2所示的简化步骤。