查询词典 transform

Consider the dependencies between the coefficients and their parents, a non-Gaussian bivariate distribution is given, and corresponding nonlinear threshold function is derived from the model using Bayesian estimation theory. According to non-subsampled Contourlet transform and bivariate threshold function, a novel Non-Subsampled Contourlet Transform based on Bivariate threshold function for image denoising is proposed. This scheme achieves enhanced estimation results for images that are corrupted with additive Gaussian noise over a wide range of noise variance.

该文依据非下采样Contourlet分解系数与其父系数之间的相关性，给出非高斯双变量分布，对该模型应用Bayes估值理论推导得到相应的非线性双变量阈值函数，综合非下采样Contourlet分解和双变量阈值函数，提出一种基于双变量阈值的非下采样Contourlet变换图像去噪方法。

We also analyze the mechanism of the initial zinc blende structure and wurtzite structure phase transition in II-VI and III-V compound materials. The results indicate that the transition of zinc blende structure to rocksalt structure due to "chair" structure transform, the transition of wurtzite structure to rocksalt structure due to "chair" and "boat" structure transform.

对II-VI族和III-V族初始相为闪锌矿或纤锌矿的压致结构相变机制进行的分析表明，闪锌矿结构到岩盐矿的相变是因为"椅式"结构的变化，纤锌矿结构到岩盐矿的相变是因为"椅式"和"船形"两种结构的变化。

The main jobs of the paper are as follows, Multi-scale decomposition and reconstruction of wavelet transform is utilized to filter the noise of negative-pressure-wave, which is brought by leakage. With the capacity to detect the signal singularity quickly and accurately, wavelet transform was used to catch the break point of pressure signal. Accordingly, the work improved the location accuracy.

主要研究工作有：利用小波变换的多分辨率分解和重构技术，对采集到的管道泄漏产生的负压波信号进行消噪处理，并对几个影响消噪质量的关键因素及其选取方法进行了分析；再利用小波变换技术对信号奇异点的快速、准确的识别能力，对经消噪后的负压波信号进行奇异点捕捉，从而实现更精确的单条燃气管道泄漏定位。

This paper combines with pipeline delivery of our countrys actual conditions and other methods of detection and location. To the leakage characteristic of the fault to the long-distance natural gas pipeline, a method is raised, which is on the basis of wavelet and negative-pressure-wave to detect the leakage and locate. Jobs in this paper are as follows:Multi-resolution decomposition and reconstruction of wavelet transform is utilized to filter the noises, which the leakage brings the noises of negative-pressure-wave. The research is worked in the wavelet and wavelet packet filter. The wavelet transform have a fast and accurate recognition capability to signal singularity. This paper chooses wavelet technology to catch the break point of pressure signal.

本文结合我国管道输送的实际情况和目前现有的各种泄漏检测与定位方法，针对天然气长输管线泄漏故障的特点，提出了基于小波分析和负压波相结合的方法检测泄漏并定位，其中主要进行了以下几个方面的工作：利用小波变换的多分辨率分解和重构技术，对采集到的管道发生泄漏时产生的负压波信号进行降噪处理，并对小波及小波包优化的降噪效果进行对比性研究；利用小波变换技术对信号奇异点的快速、准确的识别能力，捕捉负压波信号的突变点，从而判断是否有泄漏发生。

Because the temperature along the pipeline is not a constant, it changes the velocity of the negative-pressure-wave; the Romberg algorithm of numeric integral and the searching for algorithm are emloyed to locate the leakage.Multi-scale decomposition and reconstruction of wavelet transform is applied to filter the noise of negative-pressure-wave, which was brought by leakage. With the capacity to detect the signal singularity fast and accurately, wavelet transform was used to catch the break point of pressure signal. The work improved the accuracy of Δt in location formula, and the location accuracy is improved.

利用小波变换的多分辨分析和重构技术，对采集到的管道发生泄漏时产生的负压波信号进行了消噪处理；并利用小波变换技术对信号奇异点快速、准确的识别能力，对经过消噪处理后的负压波信号进行了奇异点捕捉，准确确定了定位公式中上、下游站点采集到的负压波奇异点的时间差△t，从而提高了定位的精度。

At the same time, combining with the actual condition of delivery pipeline of our country and some prevalent leak detection and location methods, this paper raised a method, which is based on wavelet analysis and negative- pressure-wave to detect and locate the leakage. Jobs in the paper are as follows:As affected by gas density, pressure, specific heat and pipe material, the velocity of negative-pressure-wave improved depending on the energy conservation. At one time, taking the affection of velocity of gas flow, the location formula was modified in some degree.When locating the leaks with location formula, the iterative approach algorithm was adopted as a new method to increase the location accuracy level of system.Multi-scale decomposition and reconstruction of wavelet transform is utilized to filter the noise of negative-pressure-wave, which was brought by leakage. With the capacity to detect the signal singularity fast and accurately, wavelet transform was used to catch the break point of pressure signal. The work improved the accuracy of At in location formula, accordingly improved the location accuracy.Wavelet is a suitable tool for signal analysis. The distinct character is that the mother-wavelet is of optional. That means choosing different mother-wavelet will get different analysis result. So we studied how to choose mother-wavelet and its scale for signal singularity detection. The method is to choose a wavelet by regularities of the wavelet and the signal.Finally, a plan, which bases on SCADA system for inspection and detection of natural gas leakage, is proposed in the article.

其中，主要进行了以下几方面的工作：针对泄漏产生的负压波在管道中的传播速度受媒介的密度、压力、比热及材质等因素的影响，而非声波在空气中传播的速度，本文利用能量守恒原理，对其进行了修正；考虑到管内气体流速对压力波速的影响，对原始的负压波定位公式进行了一定程度的改进，并在利用定位公式进行泄漏点定位时采用逐步迭代逼近算法，提高了系统的定位精度；利用小波变换的多分辨率分解和重构技术，对采集到的管道发生泄漏时产生的负压波信号进行了降噪处理；并利用小波变换技术对信号奇异点的快速、准确的识别能力，对经上述消噪后的负压波信号进行了奇异点捕捉，精确捕捉的结果提高了定位公式中上下游站点采集到的负压波奇异点的时间差△t的精度，从而进一步提高了定位的精度；考虑到小波变换是一种基波可变的信号分析工具，也就是说，不同的小波基波对信号分析的结果将有很大差别，这势必影响最终的处理结果，因此，我们又对比分析了本课题中小波基及尺度的选择问题，依据规则性系数相似性原理对母小波的选择进行了探索性研究；最后，还提出了基于SCADA的泄漏检测与定位系统的软件开发构想及系统的嵌入方案。

In view of crosswell and 3D VSP layout, we use high resolution Radon transform based on Cauchy distribution to perform Radon transform for hole data. In this process, we study discrete dip overlay operator, improve damping factor that affects Radon energy convergence in order to let Radon energy converge, 6 resolve leggy in Radon data, and decouple smoothing effect among each energy group, we use Cauchy distribution to regularize data, let energy focus on one point, and improve Radon resolution. All these work well in wavefield separation. Finally, by inversion results and model trial, we verify the feasibility and stability of this method.

在Radon变换原理分析基础上，采用基于柯西分布的高分辨率线性Radon变换对井孔数据进行Radon变换，其间通过对离散倾角叠加算子求取的研究，及对影响Radon能量收敛的重要参数阻尼因子算法的改进，使数据在Radon域以能量团的形式呈现，得到很好的收敛效果，基本解决了Radon域数据的一定程度的拖尾现象，消除了各能量团之间的平滑效应，采用柯西分布来规则化数据，提高了Radon域的分辨率，Radon域能量也收敛到一个点上，有利于上下行波或纵横波波场分离。

In view of crosswell and 3D VSP layout, we use high resolution Radon transform based on Cauchy distribution to perform Radon transform for hole data. In this process, we study discrete dip overlay operator, improve damping factor that affects Radon energy convergence in order to let Radon energy converge, 6 resolve leggy in Radon data, and decouple smoothing effect among each energy group, we use Cauchy distribution to regularize data, let energy focus on one point, and improve Radon resolution. All these work well in wavefield separation.

在Radon变换原理分析基础上，采用基于柯西分布的高分辨率线性Radon变换对井孔数据进行Radon变换，其间通过对离散倾角叠加算子求取的研究，及对影响Radon能量收敛的重要参数阻尼因子算法的改进，使数据在Radon域以能量团的形式呈现，得到很好的收敛效果，基本解决了Radon域数据的一定程度的拖尾现象，消除了各能量团之间的平滑效应，采用柯西分布来规则化数据，提高了Radon域的分辨率，Radon域能量也收敛到一个点上，有利于上下行波或纵横波波场分离。

This paper presents a new method for color image compression coding by using chromatism analysis and wavelet transform. In the method ,one of the three color components of a color image for example the G (component of a RGB color image is coded using wavelet transform ,and the chromatism between G and other two color componets RG, BG is coded respectively using chromatism analysis.

提出一种应用色差分析和小波变换对彩色图像进行压缩编码的新方法，该法是对彩色图像的三个色彩分量之一，如RGB图像的G进行小波变换编码，而对G与另外两个色彩分量的差值（RG和BG进行色差分析编码。

In the new algorithm,the circle detection problem is decomposed into two stages consisting of a 2D Hough transform to find circle centre and a 1D Hough transform to determine the radius.

利用局部梯度信息将检测圆所需的3D Hough变换转化为一个2D Hough变换检测圆心位置和一个1D Hough变换检测圆的半径。

Liapunov—Schmidt method is one of the most important method in the bifurcation theory.

Liapunov—Schmidt方法是分叉理论的最重要方法之一。

Be courteous -- even when people are most discourteous to you .

要有礼貌──即使当別人对你最不礼貌的时候。