小波分析在高压电器放电检测中有很大的优越性，最优小波基的选择是小波分析的应用中的重要问题。
Wavelet analysis is very preponderant in acoustic emission detection of discharge in high voltage equipment. In its application, selection of best basis is important.
本文从小波变换的基本概念出发，提出了波形匹配的具体实现方法，利用优化函数来得到最优小波滤波器。
Based on the basic conceptions of wavelet transform, the realization of waveform matching and find the optimized wavelet filter is presented in this paper.
但目前小波分析处理超声检测信号的应用领域还很有限，并且应用过程中没有考虑最优小波基的选取问题。
But now the field is finite that wavelet analyses is used in the ultrasonic testing signal processing, and the problem of selecting the best wavelet didn't be considered in the application of wavelet.
首先用信息熵函数最小选择最优小波基，然后用其对燃气负荷进行二层分解得到负荷的低频信号和高频信号。
Firstly, the best wavelet basis selection was conducted via message entropy function; then the gas load was decomposed to low frequency signal and high frequency signal by two times through it.
新算法以融合能量代价函数为标准，在整个小波库中构造最优小波包基，从小波包基上提取信号最有价值的特征值。
The new arithmetic constructed the best wavelet packet based on the wavelet library with the criterion of fusing energy cost function and contract the most valuable features of the signals.
该变换具有最优稀疏约束条件，能使一次波在一组基函数上的投影能量尽可能小。
The transform is characterized by optimum sparseness constraint condition that makes the mapping energy of primary reflections on a set of basis function as small as possible.
小波是表示具有点奇异性函数的最优基，它由于具有时-频局部化特点和多尺度特性，在图像处理领域得到了广泛应用。
Wavelet is the best base of functions, with point singularity, and it has wide application in image processing because of its time-frequency localization and multiscale features.
该方法基于率失真曲线的精确理论模型，对小波分解后的不同子带提供最优的动态比特分配从而实现了小波系数的自适应量化编码，最后还实现了码率控制。
It provides optimal dynamic bit allocation for sub-bands of DWT and realizes adaptive quantization for wavelet coefficients. At last, it provides exact rate control for the coder.
基于信号在不同尺度下小波变换系数模不同的变化特征，结合最优梯度估计算法提出了一种边缘检测方法。
Based on different properties of the coefficient modulus of the signal in different scale wavelet transform, conjunction the best estimate of gradient algorithm an edge detecting method is proposed.
介绍了小波变换在动态估计和数据融合中的应用，给出了一种实时的最优动态多尺度估计和融合算法。
The application of Wavelet in dynamic estimation and data fusion is introduced in this paper; an optimal real-time multiscale estimation and fusion algorithm for dynamic system is given.
正则化图像恢复是条件约束的最优化问题，而小波系数的贝叶斯统计选择是基于图像的随机场观点。
A regularized image restoration is the optimization for some conditional constraint, and the selection of wavelet coefficients based Bayesian statistic is on the image random field view.
小波阈值降噪技术利用小波变换表示信号的稀疏性质，使用对角形式的阈值滤波器达到信号降噪的目的，这个方法在很多信号空间上是近似最优的。
Wavelet thresholding technology is using the sparse property of wavelet representation and diagonal filter for signal denoising . This method is nearly optimal in many signal spaces.
给出一种新的心电图压缩方法，该方法是在小波库中通过以信息熵作为代价函数寻找最优基，实现心电图压缩。
The paper reports a kind of new compression method of ECG signal. The method is realized by means of wavelet packets transform based on best basis performed by Shanon Weaker entropy criterion.
由于在小波降噪中不同的阈值适应的信号特征不同，采用多种小波阈值对城市轨道交通牵引供电系统谐波信号进行降噪，并从中选择了最优的降噪阈值，达到对信号的优化处理。
Due to different wavelet threshold fit for different characteristic of signal, various wavelet de-noise threshold was used to decline the harmonics of signal and the best threshold was chosen.
由于在小波降噪中不同的阈值适应的信号特征不同，采用多种小波阈值对城市轨道交通牵引供电系统谐波信号进行降噪，并从中选择了最优的降噪阈值，达到对信号的优化处理。
Due to different wavelet threshold fit for different characteristic of signal, various wavelet de-noise threshold was used to decline the harmonics of signal and the best threshold was chosen.
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