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wavelet and wavelet package
相关语句
  小波及小波包
     A great number of seismic signals caused by moving wheeled vehicle and tracked vehide are obtained from field testing,and they have been processed applying Fourier transform,wavelet and wavelet package transform.
     该文对由典型地面车辆目标———轮式车、履带式车引起的地震动信号进行了实时探测 ,对实验所得的信号 ,应用短时傅立叶变换、小波及小波包分析方法对信号进行了处理 ,得到了时频分布矩阵奇异值分布特征 (SVD)和小波及小波包分解能量分布特征 (WWDD)。
短句来源
  “wavelet and wavelet package”译为未确定词的双语例句
     And wavelet and wavelet package methods are presented to process and analysis the collected signal.
     提出用小波和小波包方法对采集的超声信号进行分析与处理,并取得良好的效果。
短句来源
     On the basis of processing results, target recognition has been made by improved BP neural network, the result indicates that the recognition portion is as high as 85% on the eigenvector of wavelet and wavelet package decompose (WWPP),and shows that the eigenvector of WWPD has better performance.
     采用改进的BP网络 ,对远距离目标的地震动信号进行目标识别 ,应用WWDD对远距离信号的识别率可达 85%以上 ,说明WWDD具有更好的可分性。
短句来源
  相似匹配句对
     d-Wavelet Set
     d-小波集
短句来源
     On wavelet processing
     子波处理方法的研究
短句来源
     Spline and Wavelet
     样条与小波
短句来源
     Wavelet and its Computations
     小波与其计算
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     Package & Nature
     包装与自然
短句来源
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A great number of seismic signals caused by moving wheeled vehicle and tracked vehide are obtained from field testing,and they have been processed applying Fourier transform,wavelet and wavelet package transform. On the basis of processing results, target recognition has been made by improved BP neural network, the result indicates that the recognition portion is as high as 85% on the eigenvector of wavelet and wavelet package decompose (WWPP),and shows that the eigenvector of WWPD has better performance....

A great number of seismic signals caused by moving wheeled vehicle and tracked vehide are obtained from field testing,and they have been processed applying Fourier transform,wavelet and wavelet package transform. On the basis of processing results, target recognition has been made by improved BP neural network, the result indicates that the recognition portion is as high as 85% on the eigenvector of wavelet and wavelet package decompose (WWPP),and shows that the eigenvector of WWPD has better performance.

该文对由典型地面车辆目标———轮式车、履带式车引起的地震动信号进行了实时探测 ,对实验所得的信号 ,应用短时傅立叶变换、小波及小波包分析方法对信号进行了处理 ,得到了时频分布矩阵奇异值分布特征 (SVD)和小波及小波包分解能量分布特征 (WWDD)。采用改进的BP网络 ,对远距离目标的地震动信号进行目标识别 ,应用WWDD对远距离信号的识别率可达 85%以上 ,说明WWDD具有更好的可分性。

To classify the wheeled vehicle from tracked vehicle, the seismic signals of two kinds of vehicle are analyzed in different ways in the paper. In frequency domain, the methods of FFT and classical PSD are used to process the signals, and the features of FFT and PSD are obtained. In time-frequency domain, the signals are processed by the methods of the STFT, the wavelet and wavelet package, and the feature of SVD and the feature of the energy spectrum are obtained, After then, a separable measure is proposed...

To classify the wheeled vehicle from tracked vehicle, the seismic signals of two kinds of vehicle are analyzed in different ways in the paper. In frequency domain, the methods of FFT and classical PSD are used to process the signals, and the features of FFT and PSD are obtained. In time-frequency domain, the signals are processed by the methods of the STFT, the wavelet and wavelet package, and the feature of SVD and the feature of the energy spectrum are obtained, After then, a separable measure is proposed based on the space, and it is applied into the evaluation of the above features, the result of the evaluation shows that the features the of FFT, PSD, and the energy spectrum all have the better separation ability, and this result is validated by the result of the target identification by neural network. Accordingly, we make sure that the proposed separable measure is effective.

为了进一步对车辆目标分类 ,对实验获得的典型地面运动目标—轮式车、履带式车的地震动信号从频域、时—频域等多方面进行特征提取。在频域上 ,应用傅立叶变换、经典功率谱分析等常用的信号处理方法对信号进行处理 ,提取了信号的 FFT特征和功率谱特征。在时 -频域应用短时傅立叶变换、小波及小波包分析方法对信号进行处理 ,得到时频分布矩阵奇异值分布特征和小波包分解能量分布特征。之后基于距离可分性设计了一个模式特征可分性测度 ,对时域和时—频域所提取的各种特征进行对比评价 ,结果表明 FFT特征、功率谱特征和小波分解后的能量特征具有更好的可分性。该结果与将各特征应用神经网络进行目标识别的结果是一致的。这表明所设计的模式特征可分性测度是有效的。

There exist noise signals independent, of strata properties in most well logs in field oil production. The wavelet transform technique applied for removal treatment of the noise signals is presented based on the feature. Using this technique mainly including noise-removal methods of dimensional wavelet and wavelet package, a part of noise signal values could be restored to in-situ original ones by density-porosity logs and neutron porosity logs processing. The results show that the noise curves have been...

There exist noise signals independent, of strata properties in most well logs in field oil production. The wavelet transform technique applied for removal treatment of the noise signals is presented based on the feature. Using this technique mainly including noise-removal methods of dimensional wavelet and wavelet package, a part of noise signal values could be restored to in-situ original ones by density-porosity logs and neutron porosity logs processing. The results show that the noise curves have been inhibited after the processing of wavelet transform. With higher quality of logs, it allows to make comprehensive interpretation together with rest of well logs, provide more proper prediction of related numbers and locations of gas layers, and grasp reliable bases for natural gas exploitation.

在实际生产中,大多数测井曲线都含有与地层性质无关的噪声信号,基于这一特征,提出了采用小波变换新方法进行处理。该方法以一维小波去噪方法和小波包去噪方法为主,通过对密度孔隙度曲线和中子孔隙度曲线同时进行处理,减少噪声信号的部分值,恢复真实信号,对处理结果进行综合分析表明,经小波变换后的曲线噪声得以压制,质量得以提高,能更好地与其它测井曲线配合进行综合解释,能准确预测气层的层数、位置,为天然气开发提供可靠的依据。

 
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