分解系数

Besides, as to inpainting problem in wavelet domain, we introduce a new iterative model. In this model low frequency and high frequency will carry on processing separately, enormous speed up the image repair convergence rate, and even if as high as 90% wavelet coefficient have been lost, this model will also be able to have the very good repair effect. In the old model, to compute the curvature we have to transform the coefficients to the pixel domain, and then transform back to the coefficient domain for several times and this method can solve this problem and speed up the iterative convergence.

其次针对小波域中图像修复的问题，本文提出了一种新的小波域图像修复模型，该模型根据小波变换后系数相关性的特点，将低频和高频分别进行处理，极大的加快了图像修复的收敛速度，并且即使丢失高达90%的小波系数，该模型也会有很好的修复效果，有效的解决了传统的TV- Wavelet模型在计算图像的平均曲率WCURV时，需要反复进行小波分解与重构的计算，迭代速度慢的问题。

It takesthe weighted average of the L2 norm of the difference of the observation and thesolution of the system and the L2 norm of the difference of conormal derivativeat the different sides of the interface for every subdomain as cost functional andthe smooth coefficients of the subproblem and the value of solution of the originalproblem at interface as identification parameters;Using the property of continu-ous functional defined on compact set,the existence of the optimal solution of theidentification problem is proved;The necessary conditions of optimality charac-terized by the system equation,the adjoit equation and the variational inequalitysimultaneously are given by introducing the conception ofdifferential andadjoit variable;An algorithm is devised and its flow graph is given.

其次，针对分片光滑动力系统的特征，结合正演过程的区域分解算法，建立了分片光滑系统的分解区域参数辨识模型，该模型以子区域上解的实测值与计算值之差的L2范数和界面两侧的通量差的L2范数的加权平均作目标泛函，各子问题的光滑系数及界面上真解的值为待辨识参量；利用紧致集上连续泛函的性质，证明了子区域上参数辨识问题最优辨识参量的存在性；引入微分的概念，借助伴随变量，给出了由系统方程，伴随方程和变分不等式共同表征的最优性必要条件；根据此必要条件设计了算法，给出了算法的程序框图。

Multi-focus images are taken as experimental data, mean square error, difference coefficient, correlation coefficient are used to evaluate the results, and comparison with results based on wavelet transform is also carried out .

对多聚焦图像进行了实验，采用均方误差、偏差指数和相关系数对融合结果进行了客观评价，并与基于小波变换的融合进行了比较，实验结果表明该方法除分解2层时与小波性能相当，取其他分解层数时均获得更好的融合效果。

The main contributions include:(1) Energy conservation law of Haar wavelets transform is proved to compress data streams.(2) The relation between the coincidence measure and trend of streams is revealed as along with the invariability under parallel shift and the equivalence law over coincidence measure to approximately express data-streams by the wavelet coefficient of the characteristic stream and its energy.(3) Multi-Scales energy decomposition model is proposed to improve the compression precision.(4) The multi-scales compression algorithm and the energy conservation reconstruction algorithm are designed.(5) Extended experiments show that the compression ratio of the new methods is 2~4 times as the traditional method.

主要研究成果包括：(1)证明了Haar小波变换服从能量守恒规律，并用于压缩数据流；(2)揭示了数据流的偶合度与变化趋势的相关性、偶合度的平移不变性及等价规律，采用特征流序列的小波系数和流能量近似表示流的趋势，达到压缩的目的；(3)提出了多尺度能量分解模型，提高了表示精度；(4)设计了多尺度能量分解压缩算法以及多尺度重构算法；(5)在真实数据集上的实验表明，新方法的压缩比是传统小波方法的2～4倍。

A novel multisensor images fusion algorithm is presented based on lifting quincunx wavelt. First, the lifting quincunx wavelet transform is used to perform a multiscale decomposition of each image. Then, the wavelet coefficients of fused image are constructed using multiple operators according to different fusion rules. Finally, the reconstructed image is obtained through the inverse transform.

提出了一种基於提升方案的五株形小波的多传感器图像融合方法，即在提升五株形小波多尺度分解的基础上，对每一幅图像进行多尺度分解，按照不同的融合规则和融合运算子去构造融合图像对应的各小波系数，再通过逆变换重构融合后的图像。

The condition for the solvability of the controllers is expressed by using the coefficient matrices of the whole system.

控制器的可解性条件由系统的系数矩阵表达，因此不需要矩阵分解，可避免由矩阵分解产生的数值问题。

The Seebeck coefficient of ultrasonic PAn is greater than that of conventional PAn, both of them increase with the increase of temperature.

在聚苯胺分解温度以下，两种聚苯胺的Seebeck系数均随温度的升高而增大，直至聚苯胺的分解。

Wavelet packet decompresses vibration signals, and wavelet packet nodes which are sensitive to the change of state, as eigen-nodes, form a decomposition tree; the signal restructured at all eigen-nodes can be used as the fingerprint in many breaker diagnostic systems. Support vector machine with the "most important" factors at eigen-nodes as input vector classifies the states at "one to others" strategy.

首先利用小波包分解振动数据，提取状态变化敏感节点作为特征节点形成分解树，利用敏感节点重构完好状态振动信号，并以此作为当前大多断路器诊断系统中使用的指纹信号；同时提取特征节点最大系数形成特征向量，作为支持向量机的输入向量，使用&一对其余&策略进行特征分类。

The 1D wave equation inverse scattering problem includes many proce- dures such as time-depth conversion,Z transform,1D spectral fac- torization,reflection coefficient and transmission coefficient,et...

三维波动方程逆散射的关键环节可类比于一维波动方程反问题，一维波动方程逆散射中的时深转换、Z变换、一维谱分解和反射与透射系数等环节，在多维波动方程逆散射或速度横向变化介质逆散射的研究中，被替换为射线坐标系、单程波算子、基于Witt积的多维谱分解和反射与透射算子的平面波响应。

On the basis of taking full advantage of multi scale wavelet analysis,the proposed algorithm improves the contrast of the approximations of the wavelet transform through two lifting steps,and shrinkages the coefficients of wavelet transform on the diferent degree and then enhances the coefficients.

在多尺度分析基础上，该算法对小渡分解得到的低频子带图像采用两步提升法进行对比度增强处理，而对小波分解得到的不同方向上的小波系数进行不同程度的去噪并增强。

Cynanchum Lingtai apricot production in the average weight 65 grams, the brightly-colored fruit, juicy rich, sweet-sour taste, sweet from the nucleolus, when the late Qing Dynasty famous Shaanxi, Gansu provinces, the Qing imperial court Tongzhi tribute for years.

灵台生产的牛心杏平均单果重65克，果实色泽鲜艳，汁多味浓，甜酸适口，离核仁甜，清末时就驰名陕、甘两省，清同治年间曾为朝廷贡品。

Chenopodium album,Solanum nigrum, and Amaranthus retroflexus were very susceptible to the herbicides. Polygonum persicaria and Abutilon theophrasti were relatively less susceptible to the herbicides, and Lycopersicon esculentum was not susceptible to it. The relationship between reduction rates of weed biomass and PPM values of weed leaves 2,4, and 6 days after treatment was established.

供试的6种杂草对该混剂的敏感性存在显著差异：红心藜Chenopodium album、龙葵Solanum nigrum和反枝苋Amaranthus retroflexus对该混剂最敏感，ED90值分别为47.65、71.67和29.17g/hm2；春蓼Polygonum persicaria和苘麻Abutilon theophrasti敏感，ED90值分别为96.91、114.20g/hm2；而番茄不敏感。