The optimizing problems of nonlinear functions are discussed.
研究非线性函数的优化问题。
The question of surveying data processing in space of nonlinear functions is one front line task in this field.
非线性函数空间的测量数据处理问题是测量数据处理理论研究中的前沿课题之一。
This paper introduces a method of direct searching optimal value for nonlinear functions with inequality constraints.
本文提出了一种对具有不等式约束的非线性函数进行寻优的直接方法。
Based on the Hamiltonian principle, the coupled nonlinear functions of the system are presented as a Neumann problem.
由哈米尔顿原理作为动力学基础，建立起系统的非线性耦合运动方程组。
Abstract : A class of nonlinear non-affine pure-feedback SISO systems with unknown nonlinear functions are investigated.
摘要：研究了一类非仿射的纯反馈单输入单输出非线性系统。
After determining duality nonlinear functions of two subsystem, we give the general form of yield loss forecasting model.
在两个亚系统的二元非线性模式确定以后，给出了产量损失预测模型的一般形式。
A simple three-layer BP network using simple nonlinear transfer functions can approximate any nonlinear functions with any precision.
一个简单的三层BP前馈网络，采用简单的非线性转移函数，就可以以任意精度逼近任何非线性函数。
In order to construct new perfect nonlinear functions, investigating the preimage distributionsof perfect nonlinear functions is very important.
为构造新的完全非线性函数，研究完全非线性函数的原像分布特征具有十分重要的作用。
Based upon different perfect nonlinear functions, different frequency-hopping sequence families with optimal Hamming correlation property could be obtained.
利用不同的完全非线性函数，可以得到不同的并且具有最优汉明相关性能的跳频序列族。
In respect of programming, the improved Newton iteration algorithm is associated with function designations, therefore input and transfer of nonlinear functions are solved.
在编程技术方面，将改进的牛顿迭代法与函数调用相结合，解决了非线性函数的输入与转移问题。
At last, this paper USES the RBF neural network that was optimized by the mentioned parallel model to predict the value of some nonlinear functions and the close of several stocks.
最后，本文应用上述并行模型优化的RBF神经网络对非线性函数值以及证券个股收盘价进行预测。
BP neural network can implement approximating nonlinear functions by arbitrary accuracy through regulating variable weight connection. This character can fit the nonlinear functions relations.
BP神经网络通过调节连接权重可以实现以任意精度逼近非线性函数，利用这一特点可对非线性函数关系进行拟合。
BP neural network can implement approximating nonlinear functions by arbitrary accuracy through regulating variable weight connection. This character can fit the nonlinear functions relations.
BP神经网络通过调节连接权重可以实现以任意精度逼近非线性函数，利用这一特点可对非线性函数关系进行拟合。
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