系数域

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。

A new method based on subtractive image segmentation for weighted image fusion is put forward from another viewpoint. It adopts the improved particle swarm optimization to calculating the segmentation threshold of subtractive image and the corresponding weighted fusion coefficient in space domain or in wavelet decomposition domain. Moreover, it doesnt need to construct the eigenspace and quantitative eigenvalue for the weighted fusion coefficients.

本文从另外一个角度提出了一种基于差值图像分割的加权图像融合方法，它采用改进的粒子群优化方法在空间域或小波分解域求解差值图像的分割阈值和对应的加权融合系数，而不需要为计算融合系数而构造特征空间和定量特征关系。

Finally, FastICA in time domain is derived based on instantaneous BSS system, and convolutional mixture BSS algorithm in frequency domain is obtained based on convolutional mixture BSS in time domain. Then we combine the two algorithms together and present the complex-value FastICA algorithm in frequency domain, which is a new BSS technique. We merge preprocessing in time domain and correlation coefficient solution in time domain into this new algorithm and present Time-Frequency domain FastICA BSS System.

最后，本文在瞬时混合盲分离系统基础上推出时域FastICA算法，在时域卷积混合盲分离系统基础上推出频域卷积混合盲分离算法，将这两种算法相结合，提出了频域复值FastICA算法，再将此算法与时域预处理方法以及最后回到时域中的利用相关系数求解分离信号方法相结合，从而建立了基于FastICA的时频域盲分离系统，并将其应用到实际环境中的语音信号盲分离中。

Chaper 3 is general description of ADA encryption. Chapter 4 deals with the transform domain encryption. Includes the element of perfect and quasi-perfect transform domain encryption, and presents two type new schemes. Chapter 5 deals with asynchronous ADA encryption. Extends the general theory and model of asynchronous ADA scrambling, and introduces two type phase-distortion-free a synchronous ADA schemes. Chapter 6 is about new direction of ADA encryption. Includes TASI scrambling, transform domain dummy insertion scrambling, noise coving scrambling and other multi-dimension ADA scrambling, and proposes an adaptive dummy spectrum insertion asynchronous scrambling and a new adaptive noise-coving DFT scrambling algorithm. Chapter 7 is on permutation key. presents part results on permutation features, selecting criterion and constructing method. Chapter 8 introduces the hard and software design of a common ADA encryption/decryption system, and presents the experimental results on several proposed ADA encryption schemes.

第一章为绪论；第二章为语声信号、及其处理基础；第三章为模数模加密的一般描述；第四章为变换域加密研究，包括变换域加密机理，变换域完善与准完善保密研究，提出两种新的变换域加密方案；第五章为异步模数模加密研究，扩充了异步模数模加密的一般理论，介绍了两种新的无相位失真异步加密方案的原理与实现方法；第六章对模数模加密新方向：TASI应用途径、变换域伪谱插空置乱、噪声掩盖、多维置乱加密的原理和方法进行介绍，提出了自适应伪频插空异步模数模置乱算法与自适应DFT系数噪声掩盖置乱新算法；第七章为置换密钥性质、筛选准则以及构造方法研究的部分结果；第八章介绍了通用模数模加/解密实验系统的硬件、软件研制概况，并给出了几种加密方法的实验结果。

The method includes steps: each point in sequence x with length L, i=0, 1, 2,apostrophe L-1 is served as a independent variable of k order polynomial; changing coefficient of polynomial to generate multiple sequence f with length L, where k is nonnegative integer; operation in polynomial is carried out in Galois Field GF, where Q=pm, p as a prime number, and m as nonnegative integer; assigning generated sequences to multiple sectors to set of create biased sequences for each sector; it is different in constant terms of polynomial, and identical to other coefficients of coefficients corresponding to sequence assigned to same sector; creating corresponding time - frequency pattern unit from biased sequences of the sector; repeating TFP unit with equal interval in frequency domain so as to obtain integrated TFP.

本发明涉及一种时频资源的分配方法，所述方法包括：把一个长度为L的序列{x，i＝0，1，2，…L-1}中的每一点作为一个k次多项式的自变量，改变多项式的系数生成多个长度为L的序列{f}，其中k是非负整数，多项式中的运算在伽罗华域GF中进行，其中Q＝p m ，p是一个素数，m是非负整数；把生成的序列分配给多个小区，生成各小区的偏置序列集合，其中分配给同一个小区的序列所对应的生成多项式的常数项不同，其他项的系数都相同；由所述小区的偏置序列生成对应的时频图案单元，将时频图案单元经过频域等间隔重复，得到完整的时频图案。

We make use of a normal element and circular permutations to construct polynomials over the intermediate extension field between F_q and F_ denoted by F_ where s divides t. The polynomials we constructed are F_q-linearly independent and return elements in F_q when they are evaluated at elements of the extension fields.

结合Reed-Solomon码的构造特点，我们将Chaoping Xing与San Ling所构造的线性码的方法推广到有限域的任意次扩张上，首先利用正规元和循环排列来构造系数属于F_q和F_q的任意次扩域F_之间的中间域的具有特殊性质的多项式，中间域记为F_，其中s为t的真因子，由正规元的选择可以保证所构造多项式的F_q-线性无关性，并且这些多项式在扩域F_中取值都属于F_q，从而构造出一类q元线性码。

First, four groups of filter coefficients matrix for DCT domain deblocking are deduced. Then frequency characteristic parameters are extracted to instruct the selection of the filter coefficients matrix. The selected filter coefficients matrix multiplied with the DCT coefficients and the blocking artifacts is alleviated in the filtered DCT blocks.

在DCT-AFBAR算法中，首先推导出四组用于DCT域滤波的系数矩阵，然后根据解码块的频率特征参数来选取当前DCT块滤波所使用系数矩阵，最后将相应的DCT系数块与选好的系数矩阵进行相乘，即得到消除了块效应的DCT系数块。

Tansformed the real part and imaginary part of interferogram to stationary wavelet domain, analyzed the PDF of signal and noise wavelet coefficients using Pearson distribution system, then evaluated the wavelet coefficients of signal in stationary wavelet domain by Maximum A Posterior criteria to reconstruct the interferogram.

2将干涉图的实部和虚部分解到静态小波域，用Pearson分布系作近似，分析了信号和噪声小波系数的概率密度函数，在静态小波域用MAP准则估计信号的小波系数用于干涉图的重建。

Contourlet coefficients are modeled using a hidden Markov tree model with Gaussian mixtures that can capture all interscale, interdirection, and interlocation dependencies, which is more valid than wavelet HMT model.

Contourlet域隐马尔科夫树模型不但可以描述尺度间的相关性，而且可以对方向子带间contourlet系数的相关性做出统计描述，是一种比小波域HMT模型更为有效的系数相关性描述方法。

First, our approaches are capable of processing the queries directly from the wavelet synopses retained in the main memory without using IDWT to reconstruct the data cells. Moreover, our approaches enable the users to query the DSMS within their range of interest.

由於我们设计出来的方法，避免了将频域系数转换成时域系数所需消耗的运算负担，因此，和许多现有的演算法相比，我们的演算法，能以更有效率的方式，计算出相关查询的答案。

Singer Leona Lewis and former Led Zeppelin guitarist Jimmy Page emerged as the bus transformed into a grass-covered carnival float, and the pair combined for a rendition of "Whole Lotta Love".

歌手leona刘易斯和前率领的飞艇的吉他手吉米页出现巴士转化为基层所涵盖的嘉年华花车，和一双合并为一移交&整个lotta爱&。

This is Kate, and that's Erin.

这是凯特，那个是爱朗。