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。
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。
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。
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。
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。
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。
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。
Through trained, BP neural network can obtain strong nonlinear mapping ability to learn the data characteristics of the hydrodynamic performance of ship propeller as a mathematic analytic form.
BP人工神经网络模型通过训练可以具备强大的非线性映射能力，以数学解析的形式，较好地提取了海量螺旋桨水动力性能数据特征；
Then it introduces the basic principle of BP neural network, topology structure, and the mapping relationship, analyses the training algorithm of BP neural network and its ideas.
然后介绍了BP神经网络的基本原理，拓扑结构和映射关系；分析了BP神经网络的训练算法及算法构成思想。
The convergence speed of region mapping model is faster than that of BP neural network, and the model has a good identification ratio.
模型从根本上保证了分类准则与训练准则的一致性，具有比BP网络更快的训练速度和更高的识别率。
The BP neural network has ability of nonlinear-mapping and self-accommodating. It can be used to recognize mode, forecast and so on.
BP神经网络具有很强的非线性映射和自适应学习功能，可用于模式识别和预测评估等领域。
The BP neural network has ability of nonlinear-mapping and self-accommodating. It can be used to recognize mode, forecast and so on.
BP神经网络具有很强的非线性映射和自适应学习功能，可用于模式识别和预测评估等领域。
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