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Two-dimensional regularized inversion of AMT data based on rotation invariant of Central impedance tensor 认领 引用 被引量：5
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作者 XiaoZhong Tong JianXin Liu AiYong Li 《Earth and Planetary Physics》 CAS 2018年第5期430-437,共8页
Considering the uncertainty of the electrical axis for two-dimensional audo-magnetotelluric(AMT) data processing, an AMT inversion method with the Central impedance tensor was presented. First, we present a calculatio... Considering the uncertainty of the electrical axis for two-dimensional audo-magnetotelluric(AMT) data processing, an AMT inversion method with the Central impedance tensor was presented. First, we present a calculation expression of the Central impedance tensor in AMT, which can be considered as the arithmetic mean of TE-polarization mode and TM-polarization mode in the twodimensional geo-electrical model. Second, a least-squares iterative inversion algorithm is established, based on a smoothnessconstrained model, and an improved L-curve method is adopted to determine the best regularization parameters. We then test the above inversion method with synthetic data and field data. The test results show that this two-dimensional AMT inversion scheme for the responses of Central impedance is effective and can reconstruct reasonable two-dimensional subsurface resistivity structures. We conclude that the Central impedance tensor is a useful tool for two-dimensional inversion of AMT data. 展开更多
关键词 audio-magnetotelluric/AMT impedance tensor rotation invariants two-dimensional geo-electrical model regularized inversion
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A Secure Rotation Invariant LBP Feature Computation in Cloud Environment 认领 引用
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作者 Shiqi Wang Mingfang Jiang +2 位作者 Jiaohua Qin Hengfu Yang Zhichen Gao 《Computers, Materials & Continua》 SCIE EI 2021年第9期2979-2993,共15页
In the era of big data,outsourcing massive data to a remote cloud server is a promising approach.Outsourcing storage and computation services can reduce storage costs and computational burdens.However,public cloud sto... In the era of big data,outsourcing massive data to a remote cloud server is a promising approach.Outsourcing storage and computation services can reduce storage costs and computational burdens.However,public cloud storage brings about new privacy and security concerns since the cloud servers can be shared by multiple users.Privacy-preserving feature extraction techniques are an effective solution to this issue.Because the Rotation Invariant Local Binary Pattern(RILBP)has been widely used in various image processing fields,we propose a new privacy-preserving outsourcing computation of RILBP over encrypted images in this paper(called PPRILBP).To protect image content,original images are encrypted using block scrambling,pixel circular shift,and pixel diffusion when uploaded to the cloud server.It is proved that RILBP features remain unchanged before and after encryption.Moreover,the server can directly extract RILBP features from encrypted images.Analyses and experiments confirm that the proposed scheme is secure and effective,and outperforms previous secure LBP feature computing methods. 展开更多
关键词 Privacy-preserving rotation invariant local binary pattern cloud computing image encryption
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RoCoNet:Rotational Contrastive Network for Semi-Supervised Cervical Cell Image Object Detection 认领 引用
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作者 HUANG Qiubo GONG Runze CHEN Dehua 《Journal of Donghua University(English Edition)》 CAS 2026年第2期82-93,共12页
A semi-supervised learning framework integrating rotational invariance,contrastive learning,and adaptive hybrid thresholds,named rotational contrastive network(RoCoNet),is proposed to enhance the applicability of semi... A semi-supervised learning framework integrating rotational invariance,contrastive learning,and adaptive hybrid thresholds,named rotational contrastive network(RoCoNet),is proposed to enhance the applicability of semisupervised learning for medical cell datasets.Due to the unique sampling approach of cell datasets,input images often contain uncertain rotation angles,which render traditional convolution kernels ineffective in existing semi-supervised detectors.To address this challenge,rotational attention convolution is introduced,offering robustness to rotational transformations.Additionally,cross-feature contrastive loss is proposed to improve upon the contrastive loss used in supervised learning,tackling issues of poor classification performance caused by cell overlap and clustering.An adaptive hybrid threshold is also introduced to stabilize pseudo-label generation during early training.A global threshold,computed by using Gaussian mixture models(GMMs),is applied to refine the local threshold,which helps balance the quantity and quality of pseudo-labels.Experiments on the ThinPrep cytology test(TCT)dataset for cervical cytopathology show that RoCoNet achieves a mean average precision(mAP)of 31.6%with only 10%labeled data,outperforming the baseline method by 8.4%in mAP. 展开更多
关键词 semi-supervised learning rotational invariance contrastive learning object detection cervical cell
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Rotation Scaling and Translation Invariants of 3D Radial Shifted Legendre Moments 认领 引用 被引量：2
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作者 Mostafa El Mallahi Jaouad E1Mekkaoui +2 位作者 Areal Zouhri Hicham Amakdouf Hassan Qjidaa 《International Journal of Automation and computing》 CSCD 2018年第2期169-180,共12页
This paper proposes a new set of 3D rotation scaling and translation invariants of 3D radially shifted Legendre moments. We aim to develop two kinds of transformed shifted Legendre moments： a 3D substituted radial sh... This paper proposes a new set of 3D rotation scaling and translation invariants of 3D radially shifted Legendre moments. We aim to develop two kinds of transformed shifted Legendre moments： a 3D substituted radial shifted Legendre moments （3DSRSLMs） and a 3D weighted radial one （3DWRSLMs）. Both are centered on two types of polynomials. In the first case, a new 3D ra- dial complex moment is proposed. In the second case, new 3D substituted/weighted radial shifted Legendremoments （3DSRSLMs/3DWRSLMs） are introduced using a spherical representation of volumetric image. 3D invariants as derived from the sug- gested 3D radial shifted Legendre moments will appear in the third case. To confirm the proposed approach, we have resolved three is- sues. To confirm the proposed approach, we have resolved three issues： rotation, scaling and translation invariants. The result of experi- ments shows that the 3DSRSLMs and 3DWRSLMs have done better than the 3D radial complex moments with and without noise. Sim- ultaneously, the reconstruction converges rapidly to the original image using 3D radial 3DSRSLMs and 3DWRSLMs, and the test of 3D images are clearly recognized from a set of images that are available in Princeton shape benchmark （PSB） database for 3D image. 展开更多
关键词 3D radial complex moments 3D radial shifted Legendre radial moments radial shifted Legendre polynomials 3D imagereconstruction 3D rotation scaling translation invariants 3D image recognition computational complexities.
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Radial Hahn Moment Invariants for 2D and 3D Image Recognition 认领 引用 被引量：4
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作者 Mostafa El Mallahi Amal Zouhri +2 位作者 Anass El Affar Ahmed Tahiri Hassan Qjidaa 《International Journal of Automation and computing》 CSCD 2018年第3期277-289,共13页
Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional（2D and 3D） image not only in pattern recognition, image vision, but also in image processing and applications engine... Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional（2D and 3D） image not only in pattern recognition, image vision, but also in image processing and applications engineering. Yet, there is still a major difficulty in 3D rotation invariants. In this paper, we propose new sets of invariants for 2D and 3D rotation, scaling and translation based on orthogonal radial Hahn moments. We also present theoretical mathematics to derive them. Thus, this paper introduces in the first case new 2D radial Hahn moments based on polar representation of an object by one-dimensional orthogonal discrete Hahn polynomials, and a circular function. In the second case, we present new 3D radial Hahn moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Hahn polynomials and a spherical function. Further 2D and 3D invariants are derived from the proposed 2D and 3D radial Hahn moments respectively, which appear as the third case. In order to test the proposed approach, we have resolved three issues： the image reconstruction, the invariance of rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Hahn moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges quickly to the original image using 2D and 3D radial Hahn moments, and the test images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and Princeton shape benchmark（PSB） database for 3D image. 展开更多
关键词 Orthogonal moments two-dimensional and three-dimensional （2D and 3D） radial Hahn moments Hahn polynomials image reconstruction 2D and 3D rotation invariants.
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Content-Based Image Retrieval with Feature Extraction and Rotation Invariance 认领 引用
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作者 Nathanael Okoe Larsey Raphael Mawufemor Kofi Ahiaklo-Kuz Joseph Ncube 《Journal of Computer and Communications》 2022年第4期24-31,共8页
Over recent years, Convolutional Neural Networks (CNN) has improved performance on practically every image-based task, including Content-Based Image Retrieval (CBIR). Nevertheless, since features of CNN have altered o... Over recent years, Convolutional Neural Networks (CNN) has improved performance on practically every image-based task, including Content-Based Image Retrieval (CBIR). Nevertheless, since features of CNN have altered orientation, training a CBIR system to detect and correct the angle is complex. While it is possible to construct rotation-invariant features by hand, retrieval accuracy will be low because hand engineering only creates low-level features, while deep learning methods build high-level and low-level features simultaneously. This paper presents a novel approach that combines a deep learning orientation angle detection model with the CBIR feature extraction model to correct the rotation angle of any image. This offers a unique construction of a rotation-invariant CBIR system that handles the CNN features that are not rotation invariant. This research also proposes a further study on how a rotation-invariant deep CBIR can recover images from the dataset in real-time. The final results of this system show significant improvement as compared to a default CNN feature extraction model without the OAD. 展开更多
关键词 Rotation Invariant CBIR Image Orientation Angle Detection Convolutional Neural Network Deep Learning Real-Time CBIR Information Retrieval
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GGF:Global Geometric Feature for Rotation-Invariant Point Cloud Understanding 认领 引用
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作者 Yun-Zhe Xiao Fu Li +1 位作者 Hao-Tian Wang Shao-Wu Yang 《Journal of Computer Science & Technology》 SCIE EI CSCD 2025年第2期572-587,共16页
Most 3D vision tasks related to point cloud understanding require rotation-invariant solutions. However, existing deep learning techniques for point clouds do not always ensure rotation invariance, and achieving rotat... Most 3D vision tasks related to point cloud understanding require rotation-invariant solutions. However, existing deep learning techniques for point clouds do not always ensure rotation invariance, and achieving rotation invariance necessitates data augmentation or professional networks, which is not feasible for generic point cloud understandingtasks. To address this issue, we propose a plug-and-play feature called Global Geometric Feature (GGF), as an effectiveand efficient solution achieving rotation invariance for generic point cloud understanding networks. GGF extracts a distributed global description by capturing geometric relationships between points and projecting the point cloud into a rotation-invariant feature space. We find that GGF can be directly integrated into a variety of point cloud understandingtasks without network modification. Our experimental evaluation shows that GGF can improve the performance of generic point cloud networks for rotation-invariant understanding without data augmentation and is comparable to dedicatedrotation-invariant methods. 展开更多
关键词 point cloud rotation invariance point cloud understanding
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Low-complexity method for DOA estimation based on ESPRIT 认领 引用 被引量：10
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作者 Xuebin Zhuang Xiaowei Cui +1 位作者 Mingquan Lu Zhenming Feng 《Journal of Systems Engineering and Electronics》 SCIE EI 2010年第5期729-733,共5页
A low-complexity method for direction of arrival(DOA)estimation based on estimation signal parameters via rotational invariance technique(ESPRIT)is proposed.Instead of using the cross-correlation vectors in multistage... A low-complexity method for direction of arrival(DOA)estimation based on estimation signal parameters via rotational invariance technique(ESPRIT)is proposed.Instead of using the cross-correlation vectors in multistage Wiener filter(MSWF),the orthogonal residual vectors obtained in conjugate gradient(CG)method span the signal subspace used by ESPRIT.The computational complexity of the proposed method is significantly reduced,since the signal subspace estimation mainly needs two matrixvector complex multiplications at the iteration of data level.Furthermore,the prior training data are not needed in the proposed method.To overcome performance degradation at low signal to noise ratio(SNR),the expanded signal subspace spanned by more basis vectors is used and simultaneously renders ESPRIT yield redundant DOAs,which can be excluded by performing ESPRIT once more using the unexpanded signal subspace.Compared with the traditional ESPRIT methods by MSWF and eigenvalue decomposition(EVD),numerical results demonstrate the satisfactory performance of the proposed method. 展开更多
关键词 direction of arrival(DOA) multistage Wiener filter(MSWF) conjugate gradient(CG) estimation signal parameters via rotational invariance technique(ESPRIT) eigenvalue decomposition(EVD).
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Temporal-spatial subspaces modern combination method for 2D-DOA estimation in MIMO radar 认领 引用 被引量：10
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作者 Youssef Fayad Caiyun Wang Qunsheng Cao 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2017年第4期697-702,共6页
A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method ... A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance. 展开更多
关键词 direction of arrival estimation (DOAE) temporal subspace spatial subspace estimating signal parameters via rotational invariance technique (ESPRIT)
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Fast BSC-based algorithm for near-field signal localization via uniform circular array 认领 引用 被引量：2
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作者 SU Xiaolong LIU Zhen +3 位作者 SUN Bin WANG Yang CHEN Xin LI Xiang 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2022年第2期269-278,共10页
In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC ... In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC to extract the two-dimensional(2-D)angles of near-field signal in the Van-dermonde form,which allows for azimuth and elevation angle estimation by utilizing the improved estimation of signal para-meters via rotational invariance techniques(ESPRIT)algorithm.By substituting the calculated 2-D angles into the direction vec-tor of near-field signal,the range parameter can be conse-quently obtained by the 1-D multiple signal classification(MU-SIC)method.Simulations demonstrate that the proposed al-gorithm can achieve a single near-field signal localization,which can provide satisfactory performance and reduce computational complexity. 展开更多
关键词 near-field signal uniform circular array(UCA) beam space conversion(BSC) improved estimation of signal parame-ters via rotational invariance techniques(ESPRIT) 1-D multiple signal classification(MUSIC) parameter estimation
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High Resolution Multipath Time Delay Estimation Based on FLOCCS-ESPRIT 认领 引用 被引量：3
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作者 LIU Wen-hong QIU Tian-shuang +1 位作者 HU Ting-ting TANG Hong 《Journal of China University of Mining and Technology》 2007年第1期30-34,共5页
The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two rec... The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment. 展开更多
关键词 signal processing multipath time delay estimation α-stable distribution FLOCC FLOCCS estimation signal parameter via rotational invariance techniques （ESPRIT）
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Complex-Valued Valuations on Lp Spaces 认领 引用 被引量：1
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作者 LIU Lijuan 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2022年第1期35-41,共7页
All continuous translation invariant complex-valued valuations on Lebesgue measurable functions are completely classified.And all continuous rotation invariant complex-valued valuations on spherical Lebesgue measurabl... All continuous translation invariant complex-valued valuations on Lebesgue measurable functions are completely classified.And all continuous rotation invariant complex-valued valuations on spherical Lebesgue measurable functions are also completely classified. 展开更多
关键词 convex body valuation translation invariance rotation invariance
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MULTI-INVARIANCE ESPRIT-LIKE ALGORITHMS FOR COHERENT DOA ESTIMATION 认领 引用 被引量：2
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作者 Zhang Xiaofei Xu Dazhuan 《Journal of Electronics(China)》 2010年第1期24-28,共5页
Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the re... Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the received signal to form data model with multi-invariance property,and multi-invariance ESPRIT algorithm for coherent DOA estimation is proposed in this paper.The proposed algorithm can resolve the DOAs of coherent signals and performs better in DOA estimation than that of ESPRIT-like algorithm.Meanwhile,it identifies more DOAs than ESPRIT-like algorithm.The simulation results demonstrate its validity. 展开更多
关键词 Coherent signals Direction-Of-Arrival(DOA) estimation Multi-invariance Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT)
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Early Analogue Modeling Experiments and Related Studies to Today's Problems of Geo-electromagnetic Exploration 认领 引用 被引量：1
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作者 László Szarka 《Journal of China University of Geosciences》 2009年第3期618-625,共8页
As I learned it from extensive geo-electromagnetic analogue modeling experiments, some specific nonconventional interpretation parameters, in certain conditions, give more detailed information about the geometry of su... As I learned it from extensive geo-electromagnetic analogue modeling experiments, some specific nonconventional interpretation parameters, in certain conditions, give more detailed information about the geometry of subsurface resistivity inhomogeneities than the routinely used parameters. In this article, I show several examples, and I present how these early results influenced our later research. An enhanced geometric sensitivity may be due to special array geometry （as we call it ＂null array＂）, or it may be due to a narrow and very special frequency range （i.e., the so-called ＂keyhole＂ range）. Nonconventional but physically based interpretation parameters （like the Poynting vector） or higher order invariants of resistivity or impedance tensors may also give useful additional information about the shape of subsurface bodies. One should be very careful in their application because a large part of these nontraditional approaches are strongly constrained by measuring errors and geological noise. 展开更多
关键词 electromagnetic method analogue modeling null component rotational invariant.
Rotational invariants constructed by the products of three spherical harmonic polynomials 认领 引用
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作者 马中骐 严宗朝 《Chinese Physics C》 SCIE CAS CSCD 2015年第6期21-29,共9页
The rotational invariants constructed by the products of three spherical harmonic polynomials are expressed generally as homogeneous polynomials with respect to the three coordinate vectors in the compact form, where ... The rotational invariants constructed by the products of three spherical harmonic polynomials are expressed generally as homogeneous polynomials with respect to the three coordinate vectors in the compact form, where the coefficients are calculated explicitly in this paper. 展开更多
关键词 the rotational invariant the spherical harmonic polynomial the homogeneous polynomial
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Application of PRO-ESPRIT algorithm in identification of surface acoustic wave identification-tags 认领 引用
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作者 朱华 韩韬 施文康 《Journal of Shanghai University(English Edition)》 2008年第4期347-351,共5页
The surface acoustic wave （SAW） identification （ID）-tags have great potential for application in radio frequency identification （RFID） due to their characteristics of wireless sensing and passive operation. In t... The surface acoustic wave （SAW） identification （ID）-tags have great potential for application in radio frequency identification （RFID） due to their characteristics of wireless sensing and passive operation. In the measurements based on the frequency domain sampling （FDS）, to expand the range of detection and allow the system work in harsh environments, it is necessary to enhance the identification capability at low SNR. In addition, to identify the tags in real time, it is important to reduce identification time. Therefore, estimation of signal parameters based on the Procrustes rotations via the rotational invariance technique （PRO-ESPRIT） is adopted. Experimental results show that good identification capability is achieved with a relatively faster measurement speed. 展开更多
关键词 surface acoustic wave （SAW） identification （ID）-tags radio frequency identification （RFID） frequency domainsampling （FDS） procrustes rotations via the rotational invariance technique （PRO-ESPRIT）
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Fingerprint singular points extraction based on orientation tensor field and Laurent series 认领 引用 被引量：3
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作者 刘琴 彭可 +4 位作者 刘巍 谢琴 李仲阳 兰浩 金耀 《Journal of Central South University》 SCIE EI CAS 2014年第5期1927-1934,共8页
Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent s... Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent series.First,fingerprint orientation flow field was obtained,using the gradient of fingerprint image.With these gradients,fingerprint orientation tensor field was calculated.Then,candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space.The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model.As a global descriptor,the Laurent polynomial coefficients were allowed for rotational invariance.Furthermore,a support vector machine(SVM)classifier was trained to remove spurious SPs,using cross-correlation coefficient as a feature vector.Finally,experiments were performed on Singular Point Detection Competition 2010(SPD2010)database.Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%,the accuracy of proposed algorithm is 45.34%.The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin,and the detection is invariant to rotational transformations. 展开更多
关键词 fingerprint extraction singular point fingerprint orientation tensor field Laurent series rotational invariance supportvector machine （SVM）
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Frequency domain polarization weighted ESPRIT method for bearing angle 认领 引用 被引量：2
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作者 Wei Liu Shengchun Piao +2 位作者 Junyuan Guo Qingxin Meng Hanhao Zhu 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第5期769-775,共7页
The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization... The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information. 展开更多
关键词 vector seismic signal frequency domain polarizationweight bearing angle estimation estimation of signal parametersvia rotational invariance techniques （ESPRIT）.
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Local sum uncertainty relations for angular momentum operators of bipartite permutation symmetric systems 认领 引用 被引量：1
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作者 I Reena H S Karthik +3 位作者 J Prabhu Tej Sudha A R Usha Devi A K Rajagopal 《Chinese Physics B》 SCIE EI CAS CSCD 2022年第6期163-169,共7页
We show that violation of the variance based local sum uncertainty relation(LSUR)for angular momentum operators of a bipartite system,proposed by Hofmann and Takeuchi[Phys.Rev.A 68032103(2003)],reflects entanglement i... We show that violation of the variance based local sum uncertainty relation(LSUR)for angular momentum operators of a bipartite system,proposed by Hofmann and Takeuchi[Phys.Rev.A 68032103(2003)],reflects entanglement in the equal bipartitions of an N-qubit symmetric state with even qubits.We establish the one-to-one connection with the violation of LSUR with negativity of covariance matrix[Phys.Lett.A 364203(2007)]of the two-qubit reduced system of a permutation symmetric N-qubit state. 展开更多
关键词 sum uncertainty relations permutation symmetry rotational invariance
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Low-Complexity DOA Estimation of Noncircular Signals for Coprime Sensor Arrays 认领 引用 被引量：1
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作者 ZHAI Hui CHEN Weiyang +1 位作者 ZHANG Xiaofei ZHENG Wang 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2019年第4期599-608,共10页
This paper presents a low?complexity method for the direction?of?arrival(DOA)estimation of noncircular signals for coprime sensor arrays.The noncircular property is exploited to improve the performance of DOA estimati... This paper presents a low?complexity method for the direction?of?arrival(DOA)estimation of noncircular signals for coprime sensor arrays.The noncircular property is exploited to improve the performance of DOA estimation.To reduce the computational complexity,the rotational invariance propagator method(RIPM)is included in the algorithm.First,the extended array output is reconstructed by combining the array output and its conjugated counterpart.Then,the RIPM is utilized to obtain two sets of DOA estimates for two subarrays.Finally,the true DOAs are estimated by combining the consistent results of the two subarrays.This illustrates the potential gain that both noncircularity and coprime arrays provide when considered together.The proposed algorithm has a lower computational complexity and a better DOA estimation performance than the standard estimation of signal parameters by the rotational invariance technique and Capon algorithm.Numerical simulation results illustrate the effectiveness and superiority of the proposed algorithm. 展开更多
关键词 sensor array direction of arrival estimation coprime sensor arrays noncircular signals rotational invariance propagator method
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