提出了一种复合神经网络的算法模型，用该模型训练全加器(FA)获得了高精度分类结果。
A model of algorithm has been proposed for composite neural network and the classification results of high precision are obtained through a full adder (FA) fostered by the model.
考虑工业系统故障预知的滞后，软件设计中采用了特殊的复合神经网络结构以便于维护和拓展。
Considered the lag of the fault detection, the design introduces a specific compound network architecture that makes the software convenient for maintainability and extension.
提出了一种用于刀具状态监测的复合神经网络模型，模型由多个神经网络组成，神经网络的数目等于要监测的刀具故障数目。
This paper proposes a composite neural model for tool condition monitoring. It is composed with several neural networks and the number of neural networks is equal to the number of tool faults.
为从无偏振混浊介质背向散射光确定散射光学参数，设计了倾斜入射的模拟光路以及用复合反向传播神经网络求解的方案。
To determine the optical parameters of turbid media with an unpolarized backscattering light an oblique incidence geometry with the compound bp neural network has been designed.
本文采用动态小波神经网络方法，对复合材料疲劳剩余寿命进行了预测，结果与试验结果很接近。
The dynamic wavelet neural network method is applied to predict the fatigue residual life of the composite material. The predicting result is very close to the testing result.
为从无偏振混浊介质背向散射光确定散射光学参数，设计了倾斜入射的模拟光路以及用复合反向传播神经网络求解的方案。
To determine the optical parameters of turbid media with an unpolarized backscattering light, an oblique incidence geometry with the compound BP neural network has been designed.
在数字复合正交神经网络的基础上提出一种模拟复合正交神经网络，并用于直流双闭环调速系统中。
This paper covers an analog compound orthogonal neural network controller and its application to two closed-loop DC speed governing system.
提出了埋设于复合材料内部的光纤系统将成为未来飞行器结构的“神经网络系统”而使结构成为“智能结构”等新概念。
The optical fiber system embedded in composite materials will become a "Neutral Network System" of the future aircraft structures, leading to new concepts of the "Intelligent Structures".
综合比较了核机器方法与人工神经网络法的预测效果，同时展示了常规核与复合核的性能对比。
Experiment results show that, kernel machine method is better than artificial neural network, and compound kernel functions is better than common single kernel functions.
采用基于人工神经网络的专家系统，建立了颗粒增强金属基复合材料的本构方程。
The expert system based on artificial neural network was used, and the constitutive equation of PRMMCs was built.
仿真结果显示，复合余弦基神经网络图像去噪滤波器各项特性接近理想滤波器。
The simulation results reached nearly ideal filter characteristics, and the performance of removing image noise using this filter was compared with the median filter.
建立了新的变形预测与控制理论，并应用神经网络技术进行了某高层建筑复合地基变形预测的工程实践。
New settlement prediction and control theory is given. Finally, the neural networks technology is used in the practice of settlement calculation for a high rise building built on composite foundation.
研究表明，论文提出的复合型模糊神经网络不仅在建模精度上有着明显的优势，而且在实际生产过程的应用上具有良好前景。
This study shows that the compound fuzzy neural network not only possesses evident dominant in modeling precision, but also possesses a good prospect in the application of production process.
将专家系统与人工神经网络相结合提出了复合专家系统的概念。
The concept of the neural expert system which combines ES and ANN is put forward.
对于一类复合型模糊神经网络，论文首先进行了多方面的改进研究尝试。
This paper researched on a class of compound fuzzy neural network and made a variety of improvements.
提出利用CMAC神经网络与PID的复合控制，实现非线性系统控制。
This paper designed a control model, which is constructed based on CMAC neural network and combined with a PID controller.
本文运用正交试验法优化了对复合沉积层中纳米颗粒复合量有较大影响的各工艺参数，然后用BP神经网络分析方法对其结果进行分析处理。
In this paper, the optimized process parameters that have major influence on nanoparticle content were obtained by orthogonal test, and the result was further analyzed by BP neural network.
依据复合故障特性，提出了一种基于信息融合与神经网络的复合振动故障诊断方法。
According to the compound vibration fault attribute, a method of compound vibration fault diagnosis based on information fusion and neural networks is proposed.
并对装设有svc的两区域四机电力系统进行计算机数字仿真，结果表明基于神经网络逆系统方法设计出的复合非线性控制器可以有效地改善SVC控制性能。
The simulation of the two-area four-machine SVC system verifies that the compound nonlinear controller designed by the proposed method can effectively improve the control ability of SVC system.
通过数字复合正交神经网络的连续化算法处理获得了一种模拟复合正交神经网络，并作为前馈控制器。
The analog compound orthogonal neural network was obtained by means of a continuous algorithm treatment for a digital compound orthogonal neural network, and was used as the feedforward controller.
在数字复合正交神经网络的基础上提出一种模拟复合正交神经网络，并用于非线性伺服系统控制中。
An analog compound orthogonal neural network was presented on the basis of the digital compound orthogonal neural network and was applied in the control of the servo system with nonlinearity.
在数字复合正交神经网络的基础上提出一种模拟复合正交神经网络，并应用于机械臂的控制。
An analog compound orthogonal neural network was presented on the basis of the digital compound orthogonal neural network and was applied in the position control of a manipulator.
设计了以装配力信号为输入的小脑模型神经网络，建立了机器人复合柔顺装配作业的CMAC系统，收到良好的装配效果。
CMAC neutral network controller is designed, which receives the assembly force signals, CMAC System of Active-Passive compound Compliance in the Robotic assembly Process is setup, and good res...
进而提出了一种将计算力学、神经网络和实验模态分析相结合的复合材料结构脱层损伤检测的新方法。
Furthermore, a new method combining computational mechanics, neural network and experimental modal analysis was demonstrated for composite health monitoring.
目的用前馈(BP)神经网络对过碳酸钠合成工艺进行研究，筛选新的复合稳定剂。
Objective To study the synthetic process of sodium percarbonate using Back Propagation Artificial Neural Network (BP-ANNS).
对现行的深层搅拌桩设计方法存在的问题进行探讨，提出了用人工神经网络模型对复合地基承载力进行计算的新思路。
A new athematics model of artificialneural network is set up and applied to the calculation of the bearing capacity of compound foundation to deep mixing pile.
针对煤层气的特性，本文提出了一种基于CMAC神经网络和PID复合控制的空燃比控制方法，并对其算法进行了详细的阐述。
Aimed at the characteristics of coal bed methane, an air-fuel ratio control method which is based on CMAC neural network and PID is adopted and its arithmetic is elaborated in this article.
对于复杂的诊断对象，本文提出了一种复合模糊神经网络结构，该神经网络结构集成了一系列模糊神经子网络，来完成故障分类任务。
In this paper, a hybrid fuzzy neural network architecture is proposed for complex diagnosis objects. A series of fuzzy neural sub networks are integrated to perform the task of fault classification.
以神经网络为基本工具，利用其强大的非线性映射能力，并结合有限元法动力分析成果，为预测在复合射孔条件下岩层裂缝扩展深度提供了一条新的途径。
By using ANN and its powerful nonlinear mapping ability and combining production of FEM dynamic analysis, a new way to predicting terrane crack depth of complex fire hole is offered.
以神经网络为基本工具，利用其强大的非线性映射能力，并结合有限元法动力分析成果，为预测在复合射孔条件下岩层裂缝扩展深度提供了一条新的途径。
By using ANN and its powerful nonlinear mapping ability and combining production of FEM dynamic analysis, a new way to predicting terrane crack depth of complex fire hole is offered.
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