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Contourlet watermarking algorithm based on Arnold scrambling and singular value decomposition 认领 引用 被引量：4
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作者 陈立全 孙晓燕 +1 位作者 卢苗 邵辰 《Journal of Southeast University(English Edition)》 EI CAS 2012年第4期386-391,共6页
A new digital watermarking algorithm based on the contourlet transform is proposed to improve the robustness and anti-attack performances of digital watermarking. The algorithm uses the Arnold scrambling technique and... A new digital watermarking algorithm based on the contourlet transform is proposed to improve the robustness and anti-attack performances of digital watermarking. The algorithm uses the Arnold scrambling technique and the singular value decomposition （SVD） scheme. The Arnold scrambling technique is used to preprocess the watermark, and the SVD scheme is used to find the best suitable hiding points. After the contourlet transform of the carrier image, intermediate frequency sub-bands are decomposed to obtain the singularity values. Then the watermark bits scrambled in the Arnold rules are dispersedly embedded into the selected SVD points. Finally, the inverse contourlet transform is applied to obtain the carrier image with the watermark. In the extraction part, the watermark can be extracted by the semi-blind watermark extracting algorithm. Simulation results show that the proposed algorithm has better hiding and robustness performances than the traditional contourlet watermarking algorithm and the contourlet watermarking algorithm with SVD. Meanwhile, it has good robustness performances when the embedded watermark is attacked by Gaussian noise, salt- and-pepper noise, multiplicative noise, image scaling and image cutting attacks, etc. while security is ensured. 展开更多
关键词 digital watermarking contourlet transform Arnold scrambling singular value decomposition （SVD）
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AN ACCELERATION FOR THE EIGENSYSTEM REALIZATION ALGORITHM WITH PARTIAL SINGULAR VALUES DECOMPOSITION 认领 引用
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作者 Zhou Zhou Zhou Yuxum 《Acta Mechanica Solida Sinica》 SCIE 2002年第2期127-132,共6页
The real-time identification of dynamic parameters is importantfor the control system of spacecraft. The eigensystme realizationalgorithm (ERA) is currently the typical method for such applica-tion. In order to identi... The real-time identification of dynamic parameters is importantfor the control system of spacecraft. The eigensystme realizationalgorithm (ERA) is currently the typical method for such applica-tion. In order to identify the dynamic parameter of spacecraftrapidly and accurately, an accelerated ERA with a partial singularvalues decomposition (PSVD) algorithm is presented. In the PSVD, theHankel matrix is reduced to dual diagonal form first, and thentransformed into a tridiagonal matrix. 展开更多
关键词 eigensystem realization algorithm partial singular value decomposition Sturm sequence dynamic parameter identification
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Application of Singular Value Decomposition(SVD)to the Extraction of Gravity Anomalies Associated with Ag-Pb-Zn-W Polymetallic Mineralization in the Bozhushan Ore Field,Southwestern China 认领 引用 被引量：6
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作者 Lingfen Guo Yongqing Chen Binbin Zhao 《Journal of Earth Science》 SCIE CAS CSCD 2021年第2期310-317,共8页
The Bozhushan Ore Field,located at the western margin of the South China Block,is an important area for Ag-Pb-Zn-W polymetallic mineralization which may be associated with the Late Cretaceous granitic magmaism.In this... The Bozhushan Ore Field,located at the western margin of the South China Block,is an important area for Ag-Pb-Zn-W polymetallic mineralization which may be associated with the Late Cretaceous granitic magmaism.In this paper,the singular value decomposition(SVD)was effectively applied to decompose gravity data at scale of 1:50000 within the Bozhushan Ore Field to extract deep ore-finding information.Two gravity anomaly images displaying different scales of the ore-controlling factors were obtained.(1)The low-pass filtered image may reflect the deeply buried geological structures,hidden intrusions and concealed ore bodies.The negative gravity anomaly may reflect the overall distribution of granite bodies in the Bozhushan Ore Field.One negative gravity anomaly area may correspond to the exposed part of the Baozhushan granitic intrusion and the other corresponds to the concealed part of the granitic intrusion.The granitic intrusions are the main ore-controlling factors in this ore district.(2)The band-pass filtered image depicts the shallow concealed geological structures and geological bodies within this study area.There are two obvious negative gravity anomalies,which may be created by the hidden granites at different depths at both northwestern and southeastern sides of the exposed granitic intrusion.Thus the two negative gravity anomalies are favorable prospecting areas for various type of polymetallic ore deposits at depth.The gravity anomalies extracted by using the SVD exactly reflect the distribution of the ore deposits,structures and intrusions,which will give new insights for further mineral exploration in the study area. 展开更多
关键词 singular value decomposition(SVD) gravity anomaly Ag-Pb-Zn-W polymetallic deposits Bozhushan granitic complex southwestern China
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Pulsed Eddy Current Signal Denoising Based on Singular Value Decomposition 认领 引用 被引量：1
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作者 朱红运 王长龙 +1 位作者 陈海龙 王建斌 《Journal of Shanghai Jiaotong university(Science)》 EI 2016年第1期121-128,共8页
The noise as an undesired phenomenon often appears in the pulsed eddy current testing(PECT)signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the P... The noise as an undesired phenomenon often appears in the pulsed eddy current testing(PECT)signal, and it is difficult to recognize the character of the testing signal. One of the most common noises presented in the PECT signal is the Gaussian noise, since it is caused by the testing environment. A new denoising approach based on singular value decomposition(SVD) is proposed in this paper to reduce the Gaussian noise of PECT signal. The approach first discusses the relationship between signal to noise ratio(SNR) and negentropy of PECT signal. Then the Hankel matrix of PECT signal is constructed for noise reduction, and the matrix is divided into noise subspace and signal subspace by a singular valve threshold. Based on the theory of negentropy, the optimal matrix dimension and threshold are chosen to improve the performance of denoising. The denoised signal Hankel matrix is reconstructed by the singular values of signal subspace, and the denoised signal is finally extracted from this matrix. Experiment is performed to verify the feasibility of the proposed approach, and the results indicate that the proposed approach can reduce the Gaussian noise of PECT signal more effectively compared with other existing approaches. 展开更多
关键词 pulsed eddy current testing(PECT) singular value decomposition(SVD) negentropy denoising
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Analysis of heart rate variability based on singular value decomposition entropy 认领 引用 被引量：2
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作者 李世阳 杨明 +1 位作者 李存岑 蔡萍 《Journal of Shanghai University(English Edition)》 2008年第5期433-437,共5页
Assessing the dynamics of heart rate fluctuations can provide valuable information about heart status. In this study, regularity of heart rate variability （HRV） of heart failure patients and healthy persons using th... Assessing the dynamics of heart rate fluctuations can provide valuable information about heart status. In this study, regularity of heart rate variability （HRV） of heart failure patients and healthy persons using the concept of singular value decomposition entropy （SvdEn） is analyzed. SvdEn is calculated from the time series using normalized singular values. The advantage of this method is its simplicity and fast computation. It enables analysis of very short and non-stationary data sets. The results show that SvdEn of patients with congestive heart failure （CHF） shows a low value （SvdEn： 0.056±0.006, p 〈 0.01） which can be completely separated from healthy subjects. In addition, differences of SvdEn values between day and night are found for the healthy groups. SvdEn decreases with age. The lower the SvdEn values, the higher the risk of heart disease. Moreover, SvdEn is associated with the energy of heart rhythm. The results show that using SvdEn for discriminating HRV in different physiological states for clinical applications is feasible and simple. 展开更多
关键词 heart rate variability （HRV） singular value decomposition （SVD） entropy congestive heart failure （CHF）
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Detection and correction of level echo based on generalized S-transform and singular value decomposition 认领 引用 被引量：1
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作者 ZHU Tianliang WANG Xiaopeng WANG Qi 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2021年第4期442-448,共7页
The echo of the material level is non-stationary and contains many singularities.The echo contains false echoes and noise,which affects the detection of the material level signals,resulting in low accuracy of material... The echo of the material level is non-stationary and contains many singularities.The echo contains false echoes and noise,which affects the detection of the material level signals,resulting in low accuracy of material level measurement.A new method for detecting and correcting the material level signal is proposed,which is based on the generalized S-transform and singular value decomposition(GST-SVD).In this project,the change of material level is regarded as the low speed moving target.First,the generalized S-transform is performed on the echo signals.During the transformation process,the variation trend of window of the generalized S-transform is adjusted according to the frequency distribution characteristics of the material level echo signal,achieving the purpose of detecting the signal.Secondly,the SVD is used to reconstruct the time-frequency coefficient matrix.At last,the reconstructed time-frequency matrix performs an inverse transform.The experimental results show that the method can accurately detect the material level echo signal,and it can reserve the detailed characteristics of the signal while suppressing the noise,and reduce the false echo interference.Compared with other methods,the material level measurement error does not exceed 4.01%,and the material level measurement accuracy can reach 0.40%F.S. 展开更多
关键词 echo signal false echo generalized S-transform singular value decomposition(SVD) level measurement
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基于EMD-SVD飞机轮胎滑水动态信号降噪研究 认领 引用
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作者 李岳 位润泽 蔡靖 《振动与冲击》 EI CSCD 北大核心 2026年第11期58-65,共8页
飞机轮胎滑水动态信号受到外部噪声干扰,影响滑水状态判定与特征规律总结。对此,提出一种基于经验模态分解与奇异值分解的组合降噪算法,剔除由噪声主导的低相关系数固有模态函数分量,结合滑水信号特征通过试算合理确定比例系数,依据信... 飞机轮胎滑水动态信号受到外部噪声干扰,影响滑水状态判定与特征规律总结。对此,提出一种基于经验模态分解与奇异值分解的组合降噪算法,剔除由噪声主导的低相关系数固有模态函数分量,结合滑水信号特征通过试算合理确定比例系数,依据信噪比和均方根误差指标评价降噪效果。针对不同飞机着陆滑行条件、滑水数据类型及滑水信号来源开展降噪实例分析,验证降噪算法的有效性与适用性。分析结果表明:该算法对积水对轮胎附加阻力信号降噪效果良好,信噪比大于15.0且均方根误差小于1.0,优于经验公式拟合结果,适用于常规飞机着陆滑行参数情况;对道面与轮胎接触面积、道面对轮胎竖向支撑力信号,该算法可在保留主体特征前提下实现降噪处理,降噪曲线清晰平滑,滑水极限状态明确,避免了传统判据主观性偏差;对试验实测水滑力动态信号降噪效果突出,有助于分辨水滑力特征值及其随路面状态的演变规律,可为该领域相关研究和数据后处理提供借鉴。 展开更多
关键词 轮胎滑水 经验模态分解(EMD) 奇异值分解(SVD) 信号降噪 临界滑水速度
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基于NSST4-SVD-DBN的带式输送机托辊轴承故障诊断方法 认领 引用
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作者 胡坤 陈卓 +2 位作者 韩信 蒋浩 牛杰 《中国机械工程》 EI CAS CSCD 北大核心 2026年第3期656-667,共12页
针对带式输送机托辊轴承故障所产生的特征信息难以提取,以及故障诊断识别准确率低、鲁棒性差的问题,将二重四阶同步压缩变换(NSST4)、奇异值分解(SVD)与深度置信网络(DBN)相结合,提出一种带式输送机托辊轴承声信号故障诊断方法。利用逐... 针对带式输送机托辊轴承故障所产生的特征信息难以提取,以及故障诊断识别准确率低、鲁棒性差的问题,将二重四阶同步压缩变换(NSST4)、奇异值分解(SVD)与深度置信网络(DBN)相结合,提出一种带式输送机托辊轴承声信号故障诊断方法。利用逐次变分模态分解(SVMD)对声信号进行处理以增强故障特征的可辨识度。通过NSST4将处理后的一维信号转换为二维时频矩阵,并将该矩阵作为特征矩阵输入。采用SVD技术对特征矩阵进行降维处理,提取出能够表征托辊轴承状态的关键奇异值向量。这些奇异值向量随后被输入DBN中,DBN核心参数通过改进的麻雀搜索算法(ISSA)进行优化,以提高模型的识别性能。通过模拟故障实验和现场实验进行了测试,验证了所提方法的有效性。在托辊轴承的模拟故障实验中,所提方法实现了97.91%的准确率。与其他5种方法对比发现,所提方法准确率最高,且平均绝对误差(MAE)最低。在现场实验中,识别准确率可达96.57%。 展开更多
关键词 故障诊断 声信号 二重四阶同步压缩变换 奇异值分解 深度置信网络
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The Singular Value Decomposition Analysis between Summer Precipitation in the Dongting Lake Region and the Global Sea Surface Temperature 认领 引用 被引量：1
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作者 彭莉莉 罗伯良 张超 《Meteorological and Environmental Research》 2010年第11期28-32,共5页
By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation... By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation and their correlations with SST are analyzed.The coupling relationship between the anomalous distribution in summer precipitation and the variation of SST has between studied with the Singular Value Decomposition(SVD) analysis.The increase or decrease of summer precipitation in the Dongting Lake region is closely associated with the SST anomalies in three key regions.The variation of SST in the three key regions has been proved to be a significant previous signal to anomaly of summer rainfall in Dongting region. 展开更多
关键词 Summer precipitation Sea surface temperature(SST) Singular Value Decomposition(SVD) analysis Dongting Lake China
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The Singular Value Decomposition as a Tool of Investigating Central MHD Instabilities in the HL-1M Tokamak 认领 引用
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作者 董云波 潘传红 +1 位作者 刘仪 付炳忠 《Plasma Science and Technology》 SCIE EI CAS 2004年第3期2307-2312,共6页
A variety of strong MHD instabilities are always resulted from MHD activity of Tokamak plasmas. Central MHD instabilities can be observed with pinhole cameras to record soft x-ray (SXR) emission from the plasma along ... A variety of strong MHD instabilities are always resulted from MHD activity of Tokamak plasmas. Central MHD instabilities can be observed with pinhole cameras to record soft x-ray (SXR) emission from the plasma along many chords with a high temporal resolution. The investigation of MHD instabilities often necessitates an analysis on spatial-temporal signals. The method of Singular Value Decomposition (SVD) can split such signals into orthogonal spatial and temporal vectors. By this means, the repetition time and the characteristic radius of various MHD phenomena such as sawteeth and snake-like perturbation can be obtained. Moreover, the (1,1) MHD mode is analyzed in great detail by SVD and used to determine the radius of the q = 1 surface. 展开更多
关键词 MHD instabilities soft x-ray (SXR) Singular Value Decomposition (SVD)
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融合VMD和改进M-SVD的行星齿轮箱故障特征提取 认领 引用
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作者 郝中波 叶宁 郝心煜 《昆明冶金高等专科学校学报》 CAS 2026年第1期43-53,共11页
针对行星齿轮箱微弱点蚀故障特征提取时故障分量和噪声分量难以有效分离,导致噪声毛刺抑制不足和故障特征信息保留不完全的问题,提出一种融合变分模态分解(Variational Mode Decomposition,VMD)和改进多尺度奇异值分解(multiscale singu... 针对行星齿轮箱微弱点蚀故障特征提取时故障分量和噪声分量难以有效分离,导致噪声毛刺抑制不足和故障特征信息保留不完全的问题,提出一种融合变分模态分解(Variational Mode Decomposition,VMD)和改进多尺度奇异值分解(multiscale singular value decomposition,M-SVD)的特征提取方法。首先,构建基于最小包络熵的目标优化函数,提出融合麻雀搜索算法(Sparrow Search Algorithm,SSA)的VMD信号分解方法,完成原始信号的自适应分解;其次,选取平方包络谱峭度作为度量指标,完成VMD分解分量的筛选与重构,去除原始信号中的大部分噪声毛刺;然后,考虑均值对振动信号整体趋势变化的敏感性,融合奇异值均值和样本熵,设计基于改进M-SVD的信号处理方法;最后,对改进M-SVD处理后的信号进行包络解调,进而提取到行星齿轮箱微弱故障特征。结合信噪比和均方根误差两个量化指标,通过与单一SSA-VMD、改进M-SVD方法及原M-SVD方法的点蚀故障特征提取实验进行对比分析,所提方法最大程度保留故障特征信息的同时,能有效地抑制噪声分量。 展开更多
关键词 行星齿轮箱 变分模态分解(VMD) 多尺度奇异值分解(M-SVD) 二次分解 故障特征提取
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Randomized Generalized Singular Value Decomposition 认领 引用 被引量：3
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作者 Wei Wei Hui Zhang +1 位作者 Xi Yang Xiaoping Chen 《Communications on Applied Mathematics and Computation》 EI 2021年第1期137-156,共20页
The generalized singular value decomposition(GSVD)of two matrices with the same number of columns is a very useful tool in many practical applications.However,the GSVD may suffer from heavy computational time and memo... The generalized singular value decomposition(GSVD)of two matrices with the same number of columns is a very useful tool in many practical applications.However,the GSVD may suffer from heavy computational time and memory requirement when the scale of the matrices is quite large.In this paper,we use random projections to capture the most of the action of the matrices and propose randomized algorithms for computing a low-rank approximation of the GSVD.Serval error bounds of the approximation are also presented for the proposed randomized algorithms.Finally,some experimental results show that the proposed randomized algorithms can achieve a good accuracy with less computational cost and storage requirement. 展开更多
关键词 Generalized singular value decomposition Randomized algorithm Low-rank approximation Error analysis
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基于频域结构化K-SVD的轴承故障识别方法 认领 引用
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作者 董柯 王送来 +1 位作者 卫芬 沈意平 《自动化与仪表》 2026年第5期90-93,126,共4页
针对轴承故障声发射(AE)信号采样率高导致诊断效率低,以及基于共享字典的传统K奇异值分解(K-SVD)方法不能直接进行故障分类的问题,该文提出一种基于频域结构化K-SVD的轴承故障分类识别方法。该方法利用频域特征构建AE信号的字典学习样本... 针对轴承故障声发射(AE)信号采样率高导致诊断效率低,以及基于共享字典的传统K奇异值分解(K-SVD)方法不能直接进行故障分类的问题,该文提出一种基于频域结构化K-SVD的轴承故障分类识别方法。该方法利用频域特征构建AE信号的字典学习样本,针对轴承不同故障类型,分别训练对应的子字典以构建结构化字典,以各子字典的重构残差为判别依据,开展AE信号的稀疏分解与分类识别。搭建了轴承故障模拟实验台,采集了健康、外圈、内圈及滚动体故障的AE信号。研究结果表明,该文方法分类识别准确率可达99%,计算效率相比传统K-SVD结合分类器的方法提高约50%。 展开更多
关键词 声发射信号 K奇异值分解 稀疏表示 字典学习 故障诊断
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基于热力图和SVD的数字媒体抗摄屏水印技术研究 认领 引用
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作者 龙凤 《徐州工程学院学报（自然科学版）》 CAS 2026年第1期46-53,共8页
针对已有水印技术存在的水印嵌入强度固定、峰值信噪比(PSNR)过低等问题,提出了一种基于SVD和热力图的数字媒体抗摄屏水印技术.采用FineReport收集用户在数字媒体上的行为数据,提取用户行为数据特征,计算用户关注度,绘制数字媒体热力图... 针对已有水印技术存在的水印嵌入强度固定、峰值信噪比(PSNR)过低等问题,提出了一种基于SVD和热力图的数字媒体抗摄屏水印技术.采用FineReport收集用户在数字媒体上的行为数据,提取用户行为数据特征,计算用户关注度,绘制数字媒体热力图,从而确定抗摄屏水印嵌入区域,并计算抗摄屏水印嵌入强度.应用改进SVD算法分解水印嵌入区域,联合编码后水印信息与水印嵌入强度,通过增量相加方式进行水印嵌入操作,经过重构即可获得嵌入抗摄屏水印后的数字媒体.测试结果显示:设计技术确定的抗摄屏水印嵌入区域与最佳嵌入区域一致,抗摄屏水印嵌入强度与真实数据相同,平均峰值信噪比最大值达到了98. 展开更多
关键词 热力图 数字媒体 水印嵌入强度 SVD 抗摄屏水印 水印隐蔽性
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Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition 认领 引用 被引量：6
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作者 王宏伟 刘涛 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第Z1期1268-1273,共6页
In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are co... In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of state measurement, an identification algorithm based on the singular value decomposition(SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method. 展开更多
关键词 Non-uniformly sampling system State-space model identification Singular value decomposition Recursive algorithm
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SVD-TLS extending Prony algorithm for extracting UWB radar target feature 认领 引用 被引量：4
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作者 Liu Donghong Hu Wenlong Chen Zhijie 《Journal of Systems Engineering and Electronics》 SCIE EI 2008年第2期286-291,共6页
A new method, SVD-TLS extending Prony algorithm, is introduced for extracting UWB radar target features. The method is a modified classical Prony method based on singular value decomposition and total least squares th... A new method, SVD-TLS extending Prony algorithm, is introduced for extracting UWB radar target features. The method is a modified classical Prony method based on singular value decomposition and total least squares that can improve robust for spectrum estimation. Simulation results show that poles and residuum of target echo can be extracted effectively using this method, and at the same time, random noises can be restrained to some degree. It is applicable for target feature extraction such as UWB radar or other high resolution range radars. 展开更多
关键词 UWB radar Prony algorithm radar target feature singular value decomposition.
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A Blind Watermarking Algorithm Resisting to Geometric Transforms Based on SVD 认领 引用 被引量：2
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作者 LI Xiuguang YANG Xiaoyuan 《Wuhan University Journal of Natural Sciences》 CAS 2011年第6期487-492,共6页
A new watermarking algorithm resisting to geometric transformation based on singular value decomposition （SVD） in logarithm polar coordinate is proposed. The log-polar mapping （LPM） is used to resist rotation and ... A new watermarking algorithm resisting to geometric transformation based on singular value decomposition （SVD） in logarithm polar coordinate is proposed. The log-polar mapping （LPM） is used to resist rotation and scaling attacks, and the odd-even quantization algorithm is used to embed watermark so it can be extracted without the original host image. The experiments show that the proposed algorithm not only resists various geomet- ric attacks but also is robust enough to the common signal processing. 展开更多
关键词 blind watermarking singular value decomposition（SVD） logarithm polar coordinate resist to geometric transform
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应用奇异值分解(SVD)-主成分分析(PCA)组合模型定量圈定与评价腾冲地块锡钨和铅锌多金属找矿靶区 认领 引用 被引量：8
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作者 郑澳月 费金娜 +3 位作者 陈永清 宁妍云 曹一琳 赵鹏大 《地学前缘》 EI CAS CSCD 北大核心 2025年第1期283-301,共19页
成矿元素或元素组在一个地质单元中的富集是成岩和成矿地质过程多阶段作用的产物。基于水系沉积物地球化学数据,主成分分析(principal component analysis,PCA)可识别成矿元素组。奇异值分解(singular value decomposition,SVD)可将成... 成矿元素或元素组在一个地质单元中的富集是成岩和成矿地质过程多阶段作用的产物。基于水系沉积物地球化学数据,主成分分析(principal component analysis,PCA)可识别成矿元素组。奇异值分解(singular value decomposition,SVD)可将成矿元素组主成分得分进一步分解为两个部分:(1)成矿元素组合区域异常分量,能够表征在地壳演化过程中,由各种地质作用(岩浆作用、沉积作用和/或变质作用)形成的有利于成矿的高背景区域;(2)成矿元素组合局部异常分量,能够表征成矿作用引起的,叠加在成矿元素组合区域异常分量之上的成矿元素组合局部异常分量,应用局部异常分量能够识别找矿靶区。本次研究,首先基于国家1∶200000水系沉积物地球化学数据,应用主成分分析建立不同类型的成矿元素组;其次,利用SVD从成矿元素组的主成分得分中识别出不同类型成矿过程引起的成矿元素组合局部异常分量;最后,应用局部异常分量识别找矿靶区。最终在腾冲地块圈定15处找矿靶区,其中Sn-W找矿靶区8处,Pb-Zn-Ag找矿靶区7处。预测Sn-W潜在资源量915 Mt,Pb-Zn-Ag潜在资源量792 Mt。 展开更多
关键词 SVD PCA 成矿元素组合异常分量 地球化学块体 锡钨和铅锌多金属矿 腾冲地块 西南地区
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鹈鹕算法参数优化VMD联合SVDS的电机轴承故障诊断 认领 引用 被引量：8
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作者 孙姿姣 周湘贞 李松洋 《机械设计》 CSCD 北大核心 2025年第4期150-155,共6页
为减小噪声的干扰,增强轴承故障特征频率,实现轴承故障有效诊断,文中提出了鹈鹕算法(POA)优化变分模态分解(VMD)参数联合奇异值差分谱(SVDS)的轴承故障诊断新方法。针对VMD分解时模态层数k和平衡因子α难确定的问题,以本征模态分量(IMF... 为减小噪声的干扰,增强轴承故障特征频率,实现轴承故障有效诊断,文中提出了鹈鹕算法(POA)优化变分模态分解(VMD)参数联合奇异值差分谱(SVDS)的轴承故障诊断新方法。针对VMD分解时模态层数k和平衡因子α难确定的问题,以本征模态分量(IMF)包络熵最小为评价指标,通过POA进行参数优化;利用包络熵最小指标选取最优IMF模态,并对最优模态构建Hankel矩阵进行SVDS分析;通过SVDS确定信号重构阶数完成信号重构,并以Hilbert解调对重构信号进行包络分析。通过轴承仿真信号和实测信号对方法的有效性进行了验证,结果表明:所提方法增强了轴承故障特征频率,更容易实现故障的判别。 展开更多
关键词 变分模态分解 鹈鹕算法 奇异值差分谱 轴承 故障诊断
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Hand-eye calibration with a new linear decomposition algorithm 认领 引用
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作者 Rong-hua LIANG Jian-fei MAO 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2008年第10期1363-1368,共6页
To solve the homogeneous transformation equation of the form AX=XB in hand-eye calibration, where X represents an unknown transformation from the camera to the robot hand, and A and B denote the known movement transfo... To solve the homogeneous transformation equation of the form AX=XB in hand-eye calibration, where X represents an unknown transformation from the camera to the robot hand, and A and B denote the known movement transformations associated with the robot hand and the camera, respectively, this paper introduces a new linear decomposition algorithm which consists of singular value decomposition followed by the estimation of the optimal rotation matrix and the least squares equation to solve the rotation matrix of X. Without the requirements of traditional methods that A and B be rigid transformations with the same rotation angle, it enables the extension to non-rigid transformations for A and B. The details of our method are given, together with a short discussion of experimental results, showing that more precision and robustness can be achieved. 展开更多
关键词 Homogeneous transformation equation Singular value decomposition （SVD） Optimal rotation matrix Rigid transformations
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