In this paper, an efficient engineering classification of ship noises based on a local adaptive wavelet neural network is presented.
提出了一种用于船舶噪声分类的局域自适应子波神经网络分类方法。
A soft-measurement model based on the adaptive wavelet neural network was developed to measure the total mass flow-rate of oil-water two-phase flow.
采用的方法中构建了基于自适应小波神经网络的油水两相流质量流量软测量模型，实现了两相混合总质量流量的测量。
The self-adaptive learning rate and momentum coefficient are used to avoid the local minimum point in the training process of wavelet neural network.
小波神经网络的训练采用自适应调整学习率及动量系数的方法，以避免陷入局部极小值。
Secondly, this paper summarizes the current main methods of harmonic detection and puts forward a harmonic detection method based on wavelet neural network (WNN).
其次，总结了当前主流的谐波检测方法，提出了一种基于小波神经网络的谐波检测方法。
It extracted eigenvalues from pretreated medical images, and then classified medical images by using classifier based on improved wavelet neural network algorithm.
将经过预处理的医学图像提取特征值，然后利用基于改进的小波神经网络算法的分类器对医学图像进行分类。
Integrating the merit of wavelet transform with that of artificial neural network, a wavelet neural network (WNN) model for forecasting network traffic was created.
结合小波变换和人工神经网络的优势，建立一种网络流量预测的小波神经网络模型。
To improve early diagnosis accuracy of breast cancer, an improved wavelet neural network algorithm combining wavelet theory with neural network theory was proposed.
为了提高乳腺癌早期诊断的准确率，将小波理论与神经网络理论相结合提出改进的小波神经网络算法。
On the base of a great deal of reference literatures, intelligent PID control algorithm of ship roll motion based on dyadic wavelet neural network has been proposed.
在研究大量参考文献的基础上，本文提出了船舶横摇运动基于二进小波神经网络整定的智能PID控制算法。
A designing method of wavelet neural network structure based on multiresolution learning is put forward, and the studies of network weights adopt damped least squares.
文章提出一种基于多分辨率学习的正交基小波神经网络结构的设计方法，网络权值的学习采用阻尼递推最小二乘算法。
A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented in this paper.
本文在对小波神经网络及其算法研究的基础上，提出了一种对脑电信号压缩表达和痫样脑电棘波识别的新方法。
Adaptive wavelet neural network intelligent detection is a method in which the wavelet function substitutes for the activation function of hidden layer in the neural network.
自适应小波神经网络检测法就是利用小波函数取代通常神经网络中隐层的作用函数来实现的。
The wavelet neural network model to forecast and control equipment development expense is established on the basis of theory and method of wavelet together with its transform.
通过小波及小波变换的原理和方法，建立了适用于武器装备研制费用的小波神经网络预测与控制模型。
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.
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。
Experimental results show that, comparing with RBF neural prediction method, wavelet neural network prediction method approaches better result, and the error margin is smaller.
实验表明，与rbf神经预测方法相比，小波神经网络预测方法的逼近效果更好、误差更小。
I also introduced wavelet neural network nonlinear combination forecast method in soft base settlement forecast to furthest advance the veracity of soft-base settlement forecast.
并将小波神经网络非线性组合预测方法引入软基沉降预测中，以最大限度地提高软基沉降预测的准确性。
Based on the wavelet neural network, this paper proposes a new network named varying scales wavelet neural network to reduce wavelet-neuron Numbers and simplify network structure.
基于小波神经网络，文中提出了可变尺度小波神经网络，可减少隐层神经元数目，精简网络结构。
The wavelet neural network is applied in target identification of step frequency MMW radar. The results of experiment indicate that the method is valuable for target classification.
将所提出的小波神经网络用于毫米波频率步进雷达目标一维距离像识别。
The wavelet neural network, which has good approximation and generalization performance in nonlinear modeling, is used to predict the final settlements of soft ground in expressway.
利用小波神经网络在非线性建模中的收敛迅速等优越性 ，提出利用小波神经网络预测高速公路软土地基的最终沉降量的方法。
Aiming at the issue about multi-step prediction of the traffic flow chaotic time series, a fast learning algorithm of wavelet neural network (WNN) based on chaotic mechanism is proposed.
针对交通流量混沌时间序列多步预测的问题，提出了一种基于混沌机理的小波神经网络(WNN)快速学习算法。
The method for the multiple model failure detection is presented based on wavelet neural network and the designed neural network observer to increase the precision of the identification.
提出了一种利用小波神经网络辨识非线性系统多模型故障的方法。
This paper presents a new approach for real-time tuning the parameters of a conventional power system stabilizer using the wavelet neural network, which is used to design the stabilizer.
提出一种应用小波神经网络进行动态实时调整传统电力系统稳定器参数的设计方法。
Combining wavelet analysis and neural network characteristics, the error back propagation wavelet neural network based structure and algorithm to ship roll time series prediction are given.
结合小波分析和神经网络的特点，建立了应用于船舶横摇运动时间序列预报的误差反传小波神经网络结构并给出了算法。
The results validate more validity of nonlinear error correction model on the wavelet neural network than linear vector autoregressive model, and forecast validly the nonlinear economy system.
研究证明，小波神经网络所建立的非线性误差校正模型有较好的预测效果，能够有效地预测非线性经济系统。
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.
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。
Wavelet neural network short term load forecasting, neural network model and BP learning algorithm.
小波神经网络实现短期电力负荷预测，神经网络模型及其BP学习算法。
Structure model and algorithms of Wavelet Neural Network (WNN) are designed combining the advantages of both wavelet transform and Artificial Neural Network (ANN).
结合小波变换和神经网络的优势给出小波神经网络的结构模型，研究了小波神经网络的学习算法；
The paper proposes application of Wavelet Neural Network in high-frequency time series calendar effects' study. At last, the paper proves that WNN is better than classical FFF regression.
提出了用小波神经网络（WNN）来定量研究高频金融时间序列“日历效应”，通过比较发现WNN是比弹性傅立叶形式（FFF）回归技术更具优势的方法。
A novel method of pattern recognition and fault diagnosis in electrical machine based on the wavelet-neural network is proposed according to the frequency spectrum characteristics of vibration signal.
针对电机振动信号的频谱特点，提出基于小波神经网络技术的电机故障模式识别与诊断的新方法。
A novel method of pattern recognition and fault diagnosis in electrical machine based on the wavelet-neural network is proposed according to the frequency spectrum characteristics of vibration signal.
针对电机振动信号的频谱特点，提出基于小波神经网络技术的电机故障模式识别与诊断的新方法。
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