Blind estimation of the PN sequence in lower SNR DS-SS signals with residual carrier

This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR.     

基于Tau域奇异值分解的航空电磁数据解卷积计算

目前很多国际先进公司的AEM系统都具有不同的发射波形,给后续数据处理带来不便。为去除不同发射电流波形对电磁数据响应的影响,利用SVD分解法,以e指数为基函数,将时域航空电磁响应数据展开成Tau域参数T_i及其系数A_i形式,通过选取有效个数的Tau值,将基函数与发射电流进行卷积,形成新基底函数。通过对相应发射电流的响应以新基底展开,将新基底系数B_i与原基底结合,实现解卷积计算,得到阶跃波形发射电流情况下的电磁响应。仿真实例计算结果表明,经奇异值分解的Tau域分解方法保证了计算的精度和稳定性,基于奇异值分解的解卷积计算方法能够获得原阶跃电流响应,相对误差为1.61%。     

基于DDWT的复合型数字图像水印算法

提出了一种鲁棒性数字水印和脆弱性数字水印相结合的复合式水印算法,具有较好的双重保护性能,即用于版权认证方面的鲁棒性数字水印和用于图像内容保护的脆弱性数字水印.首先,对原始图像进行DDWT和SVD变换在频域中嵌入鲁棒性数字水印;然后,在空域中嵌入脆弱性数字水印.仿真实验表明,该算法具有很好的应用前景.     

混合总体最小二乘的迭代解算算法

总体最小二乘估计能够同时顾及线性模型中系数矩阵[WTHX]A和观测向量L的 误差,平差理论相对更为严密。如果系数矩阵[WTHX]A[WTBZ]的部分元素没有误差,这种总体最小二乘模 型为混合总体最小二乘模型。针对混合总体最小二乘(Least squares total least squares, LS TLS)解算问题,应用测量平差中 的 原理和方法,推导了混合总体最小二乘的迭代逼近解算公式,通过与奇异值分解法分析比较 ,分析了两种解算方法具有等价性,最后通过实验数据分析得出迭代算法的有效性 和合理性。     

基于模型的单视图线性共面四点算法

通过利用三维点的仿射坐标对于刚体变换而言是不变的,并且对计算机坐标系到图像坐标系的坐标变换而言也是不变的这一特性,开发了从一个目标单视图线性复原其三维位姿的新算法,该算法只需4个特征点即可精确实现目标的三维位姿的线性重建。实验表明,该算法快速高效,误差性能良好,抗噪能力较强。     

MIMO-OFDM系统中的自适应比特分配

正交频分复用(OFDM)与多天线(MIMO)技术的结合可以有效提高系统的性能。为了研究自适应比特分配对MIMO-OFDM系统性能的影响,首先介绍了MIMO-OFDM的系统结构和MIMO信道的奇异值分解(SVD)过程。将多载波系统中的Hughes-Hartogs自适应分配算法应用于天线数为2×2的MIMO-OFDM系统中。仿真结果表明,采用Hughes-Har-togs算法的MIMO-OFDM系统的数据速率达到甚至超过了单天线OFDM(SISO-OFDM)系统的2倍,但SVD分解也带来了巨大的运算量,提出了在MIMO-OFDM系统中使用自适应分配算法的策略。     

基于奇异值分解的机器人工具坐标系标定

机器人通过在末端安装不同的操作工具来完成各种作业任务,而工具参数的准确度直接影响着机器人操作精度,因此研究一种准确、快速的工具坐标系标定方法具有重要的意义。该文提出一种称为三点五步法的机器人工具坐标系标定方法,并基于矩阵的奇异值分解理论对该标定方法进行了严密的数学推理,证明该标定方法理论上的可行性。采用该算法进行工具坐标系标定具有操作简单、标定精度高、可靠性强和算法易于程序实现的特点。     

A CBIR system based on saliency driven local image features and multi orientation texture features

In Content-based Image Retrieval (CBIR), the user provides the query image in which only a selective portion of the image carries the foremost vital information known as the object region of the image. However, the human visual system also focuses on a particular salient region of an image to instinctively understand its semantic meaning. Therefore, the human visual attention technique can be well imposed in the CBIR scheme. Inspired by these facts, we initially utilized the signature saliency map-based approach to decompose the image into its respective main object region (ObR) and non-object region (NObR). ObR possesses most of the vital image information, so block-level normalized singular value decomposition (SVD) has been used to extract salient features of the ObR. In most natural images, NObR plays a significant role in understanding the actual semantic meaning of the image. Accordingly, multi-directional texture features have been extracted from NObR using Gabor filter on different wavelengths. Since the importance of ObR and NObR features are not equal, a new homogeneity-based similarity matching approach has been devised to enhance retrieval accuracy. Finally, we have demonstrated retrieval performances using both the combined and distinct ObR and NObR features on seven standard coral, texture, object, and heterogeneous datasets. The experimental outcomes show that the proposed CBIR system has a promising retrieval efficiency and outperforms various existing systems substantially.