Based on the theorem of the existence of multilayered neural network mapping, a model of artificial neural network is set up for approximate structural analysis.
基于多层神经网络映射存在定理，建立近似结构分析的人工神经网络模型。
The improved BP algorithm added momentum item and chaotic mapping was adopted in fault diagnosis of power supply system based on chaotic neural network.
基于混沌神经网络的供配电系统故障诊断，采用引入动量项和混沌映射的改进BP算法。
With the non linearity mapping of neural network, this problem can be well handled.
利用神经网络的非线性映射及泛化功能，就能很好解决上述问题。
With the nonlinear mapping ability of neural network, this method can give relatively excellent prediction to target.
该方法利用了神经网络的非线性映射能力，能够较好地对目标进行预测。
Network neural is fit for dealing with nonlinear problems especially for its good ability for nonlinear mapping.
神经网络具有良好的非线性映射能力，特别适合于处理各种非线性问题。
Because the feedforward neural network has an ability of approach to arbitrary nonlinear mapping, it can be used effectively in the modeling and controlling of nonlinear system.
前馈神经网络由于具有理论上逼近任意非线性连续映射的能力，因而非常适合于非线性系统建模及构成自适应控制。
The powerful nonlinear mapping function of BP neural network can settle the nonlinear problem of torque Angle control.
BP神经网络具有强大的非线性映射能力，可以解决转矩角控制中的非线性问题。
This mapping relation is determined by training neural network with a back-propagation algorithm, which is utilized to estimate images at finer resolution from coarser versions.
使用反向传播算法训练神经网络，确定这种映射关系；根据该映射关系由低分辨力图像估计高分辨力图像。
The result indicates that based on CP neural network, the fault pattern recognition system has strong nonlinear mapping ability, therefore it can be used to correctly classify the mechanical faults.
结果表明，以CP神经网络构筑的故障模式识别器有很强的非线性映射能力，可对机械设备故障模式进行正确分类。
The inverse mapping is achieved through BP network, and neural network modul is constructed for designing process parameters.
通过误差逆传播(BP)网络实现了逆映射，建立了工艺参数设计的神经网络模块。
The application of a robotic manipulator based on mutual mapping neural network(MMNN) is discussed.
讨论了一种基于双映射神经网络的机械臂运动控制器。
With the implicit function relation, BP (Back Propagation) neural network can easily realize the mapping between input data and output data.
通过找出其隐式函数关系，误差反向传播神经网络可以实现输入和输出间的任意映射。
Furthermore, neural network model, which has better nonlinear mapping capability, is studied and founded.
同时，研究并建立了具有较强非线性映射能力的神经网络模型。
The artificial neural network has the character of express arbitrary nonlinear mapping, thus, it works very well in operating classification and learning, and its tolerant errors as well.
人工神经网络具有表达任意非线性映射的特性，从而在分类、学习和容错方面表现了较好的能力。
It adopts cloud neural network to study the cloud mapping relationship between variables, so as to generate cloud decision tree.
运用云神经网络学习变量间的云映射关系，从中生成云决策树。
Meanwhile a HCMAC neural network is fabricated to replace the complex calculation of the inverse Jacobian mapping.
同时，利用分层神经网络代替视觉空间到任务空间的映射，避免了复杂的逆矩阵计算。
Simulation results show that extensive mapping ability of neural network and rapid global convergence of ant system can be obtained by combining ant system and neural network.
仿真实验表明：用蚁群算法训练神经网络，可兼有神经网络广泛映射能力和蚁群算法快速全局收敛的性能。
A lossless data compression scheme based on neural network is obtained through the structure specific mapping, integral function and BP neural network.
通过构造特别的映射、整函数和BP神经网络，获得一套基于神经网络的无损数据压缩方案。
Because the BP neural network may realize the free linearity or the non-linear function mapping, it may satisfy the request of the forecast for the endpoint oxygen content.
由于BP神经网络可以实现任意线性或非线性的函数映射，所以可以满足终点氧含量的预报要求。
Forward Generating Neural network (FGNN) is a special network for solving mapping problems.
前向生成神经网络是一种解决映射问题的神经网络。
BP neural network method is different from the traditional log interpretation method of CRA (complex reservoir analysis) and it is of a strong antijamming ability and nonlinear mapping ability.
BP神经网络不同于传统的CRA(碳酸盐岩复杂岩性处理程序)测井解释方法，具有强的抗干扰能力和非线性映射能力。
The mapping model of film thickness of micro-arc oxidation(MAO) on magnesium alloys is built on BP neural network with three layer structure.
选择三层结构的BP神经网络，建立镁合金微弧氧化膜厚的映射模型。
The I/O relationship of back propagation algorithm (BP algorithm) for Feed-Forward Multi-layered Neural Network is a mapping relationship, which can resolve the above nonlinear problem.
多层前向神经网络的误差逆传播算法（简称BP算法）的输入输出关系实际上是一种映射关系，适于解决上述非线性映射问题。
According to a learning algorithm of self organizing neural network for mapping character, a CMOS implementation of its synaptic weight by circuit is presented in this paper.
本文根据自组织特征映射神经网络学习算法，提出了其权值的CMOS实现电路。
Financial time series has high randomicity and nonlinearity. Neural network is quite suitable in the process of financial time series data for its good ability of nonlinear mapping and generalization.
金融时间序列具有很强的随机性和非线性性，而神经网络具有良好的非线性映射能力及自适应、自学习和良好的泛化能力，因此非常适合处理金融时间序列这样的数据。
Artificial neural network has good nonlinear mapping and a high degree of parallel processing of information capacity.
人工神经网络具有良好的非线性映射和高度的并行处理信息能力。
The paper, by adopting jointly Artificial Neural Network (ANN), general Amold mapping, and statistical methods, intends to formulate an algorithm based on image spatial domain watermark.
将人工神经网络（ANN）、广义猫映射及概率统计等知识相结合构造了一种图像空间域水印算法。
The BP neural network has the ability to solve many practical problems because of its strong mapping. However, it has slow convergence rate and is prone to fall into local extremum.
BP神经网络具有很强的映射能力，可以解决许多实际问题，但同时还存在着收敛速度慢，易陷于局部极小的缺点。
This method utilizes the nonlinear mapping ability of the BP neural network. By training, the BP neural network achieves the error compensation for multi sensor system.
该方法利用BP网络较强的非线性映射能力，网络通过学习能实现对传感器系统误差的补偿。
Due to the high-dimensional mapping that neural network fits contains complex intrinsic attribute dependencies, the traditional optimization methods have not conducted the analytical study on it.
由于神经网络拟合的高维映射存在复杂的内在属性依赖关系，而传统的优化方法却没有对其进行分析研究。
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