该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。
The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.
利用人工神经网络理论，通过对设备振动信号采集、处理和提取特征参数的方法，对装载机机械系统工作状态进行智能监测与故障诊断。
This paper involves ANN based intelligent condition monitoring and diagnosing of loaders, focusing on signal collecting and processing as well as characteristic parameter picking up.
最后阐述应用rbf神经网络进行基于混沌的语音信号非线性处理。
Then RBF neural network used in nonlinear processing of speech signals based on chaos aspects is presented.
本文提出了以径向基函数(RBF)神经网络处理表面粗糙度光纤传感器输出信号的方法。
A new method for processing output of surface roughness optical fibre sensor by radial basis function (RBF) neural network is presented in the paper.
实际上，复交替投影神经网络不仅可用于信号处理中的带限信号外推，还可用于选频、陷波等场合。
In practice complex alternating projection neural networks can be widely applied to signal processing, such as band-limited signal extrapolation, frequency selector and trap filter.
并介绍了实验以及内埋光纤阵列传感信号的人工神经网络处理的情况。
The experiment and the signal processing of embedded optical fiber sensing network are also presented.
介绍了利用GAL算法对装备产生的声音信号进行处理，改进完善了基于竞争学习的GAL神经网络。
In this paper, introduces a new method of GAL algorithm that can process the sound signal of armored vehicle and improves GAL network based on self-learning.
通过对安装在反应堆压力壳上的多个加速度传感器的信号进行采集，并经过信号预处理、时频变换、神经网络计算等过程，实现对核电站松动件碰撞位置的定位。
The loose part impact positions are located by analyzing signals from accelerometers mounted on the reactor vessel with signal pre processing, time frequency transforms, and neural networks.
基于汽车的常见被盗方式，介绍了用多传感器采集信号、信息融合技术处理信号的方法，分析了信息融合技术的基本算法，讲述了神经网络的自学习和自组织能力。
Based on the usual means of stealing an automobile, this paper mainly introduces the methods of signal acquisition based on multi sensors and signal processing with information fusion technology.
描述了一种新颖的光纤传感阵列和适宜的神经网络信号处理技术。
A novel optic fiber sensing array and suitable neural network signal processing techniques are described.
人工神经网络是模仿人脑神经元结构、特性和大脑认知功能而构成的新型信号、信息处理系统。
Neural network, which simulates the frame, the character and the cognizing ability of nerve element cerebrum, is a new system that can handle many kinds of information semaphore.
在无损检测信号处理和特征构造的基础上，用神经网络对缺陷进行识别，然后运用模糊积分对多个神经网络的分类结果进行融合。
In this paper, defects for NDT are classified with neural network which USES features extracted from signal processing. Then classification results from networks are fused with fuzzy integral.
然后，采用小波包对采集的铣削力信号进行分解和消噪处理，并提取其能量特征作为BP神经网络的输入向量。
Then, wavelet packet was used to decompose and de-noise the milling force signal, as well as extracts the signals 'energy characteristics as import vectors of BP Neural Network.
而在处理实际问题时，有必要在细胞间引入信号传输延迟，这种带延迟项的系统称为延时细胞神经网络。
It's necessary to induce delays, among cell when transmitting information in solving real problems. This is so called Delayed Cellular Neural Networks (DCNNs).
本文应用BP神经网络处理服装革的手感检测信号，为织物、皮革等服装材料的手感评定探索出了一条新途径。
A new approach was suggested for data processing in assessment of fabric and leather handle in the paper.
本文应用BP神经网络处理服装革的手感检测信号，为织物、皮革等服装材料的手感评定探索出了一条新途径。
A new approach was suggested for data processing in assessment of fabric and leather handle in the paper.
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