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Secondly, a improvement of image denoising algorithm based Ridgelet tra...

其次,针对图像去噪中常用阈值方法的缺点和不足,提出了一种基于脊波变换的改进的图像去噪算法,该算法采用指数型阈值函数,利用SureShrink自适应阈值。

This paper advanced a method to eliminate noises on images by wavelet transform and Gauss function ,it could not only eliminate white noise and at the same time is good for eliminating specking noise .

提出了小波变换与高斯函数相结合进行影像去噪的方法,在去除高斯白噪声的同时能够有效去除椒盐噪声。

Prestack migration method presented in this paper should be developed to apply in observational teleseismic P waveform data, to study the inhomogeneity of crust and upper mantle.

对本文所提出的接收函数叠前偏移方法作进一步的发展,可以用于实际的远震体波波形数据,在揭示地壳上地幔结构的横向非均匀性研究中,具有颇为广阔的应用前景。

In this paper, those teleseismic records with clear P waveforms are chosen to carry out receiver function analysis and modeling. A simple crustal structure model beneath the station is obtained, in which the Moho depth is 28 km. On the top of the upper crust is a 2 kmthick low velocity layer with a shear wave velocity of only 23 km/s. The shear wave velocity increases gradually with depth to 38 km/s in the lower crust.

本文对具有清晰P波波形的远震记录进行了接收函数处理和计算模拟,得到台站下简单的地壳结构模型,其莫霍面深度为28 km,上地壳顶部有一层2 km厚的低速层,横波速度只有23 km/s,向下逐渐过渡到横波速度为38 km/s的下地壳。

And then we use 27 pairs of P/SH teleseismic body waves to make tests for our CAPtele method,which shows that the best t_p~*=1,t_~*/t_p~*=5 and length of source time function is 3.5s.

与其相对的,我们还利用环境噪音互相关的方法获取了面波的格林函数。

A new method is described for determining the microwave dielectric properties of solid materials,for example agricultural products,mineral,of known densities from the dielectric properties of pulverized samples measured by employing the short circuited waveguide principle at a few different bulk densities.

本文介绍一个测定不能进行机械加工的&坚实材料&的微波介电特性的新方法。将这类材料研碎,成为&空气-粒子&混合物。应用短路波导方法,在几个不同的混合物&松密度&上测量其介电特性。当已知待测材料的&坚实密度&时,利用这些测量的特性与混合物&松密度&的线性函数关系进行&外推&,从而获得&坚实密度&下的农产品的微波介电特

According to the equivalence of traffic forecasting and function estimating and approaching,the essay puts forward a method of short-term traffic forecasting which is based upon wave decompounding and support vector regress.

基于交通流预测问题与函数估计和逼近问题是等价的的思想,提出一种基于小波分解-支持向量回归的短时交通量预测方法。

Aiming at these characters of original data, this paper upbuilds a kind of noise departure model via wavelet packet and soft threshold syncretizing, meanwhile, the relevant scaled functions are controlled by the required accuracy value so that we can obtain the needed accuracy and noise.

文中针对原始数据的特征,建立对其小波包分解后的各高频门限权值融合,并利用要求的数据精度值控制权函数的噪声分离模型,得到σ控制的数据和各种噪声的分离。

Simulation results indicate that this method can effectively suppress the Pseudo-Gibbs phenomena in the vicinities of the singular points of the signal due to the discontinuity of the hard threshold function. It also reserves the edge information of the signals under the condition of thorough elimination of noises.

仿真结果表明,采用基于Lipschitz指数的小波阈值去噪方法不仅有效抑制了由于硬阈值函数的不连续性而在信号奇异点附近产生的Pseudo-Gibbs现象,而且在更加彻底去噪的前提下很好地保留了信号的边缘信息。

In the paper, the BP Neural Network is introduced to pick up the first break. And aiming at the shortcomings of BP neural network, such as the low speed in training, the tendency to local minimum, the limitation of amplitude, the momentum factor method and the self-adjusting learning rate are used to improve the BP algorithm.

将BP神经网络引入到初至波拾取中,并针对经典BP神经网络收敛速度慢、易于陷入局部极小的缺点,利用组合函数法、限幅法、动量因子法及自适应学习率法等进行了改进。

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