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IET Signal Process.最新文献

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An order insensitive optimal generalised sequential fusion estimation for stochastic uncertain multi-sensor systems with correlated noise 具有相关噪声的随机不确定多传感器系统的阶不敏感最优广义序列融合估计
Pub Date : 2023-05-01 DOI: 10.2139/ssrn.4217581
Dejin Wang, Zhongxin Liu, Zengqiang Chen
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引用次数: 0
Spatial Multiplexing in Near Field MIMO Channels with Reconfigurable Intelligent Surfaces 基于可重构智能曲面的近场MIMO信道空间复用
Pub Date : 2022-12-21 DOI: 10.48550/arXiv.2212.11057
G. Bartoli, A. Abrardo, Nicoló Decarli, D. Dardari, M. D. Renzo
We consider a multiple-input multiple-output (MIMO) channel in the presence of a reconfigurable intelligent surface (RIS). Specifically, our focus is on analyzing the spatial multiplexing gains in line-of-sight and low-scattering MIMO channels in the near field. We prove that the channel capacity is achieved by diagonalizing the end-to-end transmitter-RIS-receiver channel, and applying the water-filling power allocation to the ordered product of the singular values of the transmitter-RIS and RIS-receiver channels. The obtained capacity-achieving solution requires an RIS with a non-diagonal matrix of reflection coefficients. Under the assumption of nearly-passive RIS, i.e., no power amplification is needed at the RIS, the water-filling power allocation is necessary only at the transmitter. We refer to this design of RIS as a linear, nearly-passive, reconfigurable electromagnetic object (EMO). In addition, we introduce a closed-form and low-complexity design for RIS, whose matrix of reflection coefficients is diagonal with unit-modulus entries. The reflection coefficients are given by the product of two focusing functions: one steering the RIS-aided signal towards the mid-point of the MIMO transmitter and one steering the RIS-aided signal towards the mid-point of the MIMO receiver. We prove that this solution is exact in line-of-sight channels under the paraxial setup. With the aid of extensive numerical simulations in line-of-sight (free-space) channels, we show that the proposed approach offers performance (rate and degrees of freedom) close to that obtained by numerically solving non-convex optimization problems at a high computational complexity. Also, we show that it provides performance close to that achieved by the EMO (non-diagonal RIS) in most of the considered case studies.
我们考虑了在可重构智能表面(RIS)存在下的多输入多输出(MIMO)通道。具体来说,我们的重点是分析近场视距和低散射MIMO信道的空间复用增益。通过对角化端到端发送端- ris -接收端信道,并对发送端- ris和ris -接收端信道奇异值的有序积应用充水功率分配,证明了信道容量的实现。所得的容量实现解需要RIS具有反射系数的非对角矩阵。在近无源RIS的假设下,即RIS处不需要功率放大,则只需要在发射机处进行充水功率分配。我们将RIS的这种设计称为线性、几乎无源、可重构的电磁对象(EMO)。此外,我们还介绍了RIS的一种封闭形式和低复杂度设计,其反射系数矩阵是对角的,具有单位模项。反射系数由两个聚焦函数的乘积给出:一个聚焦函数将ris辅助信号指向MIMO发射器的中点,另一个聚焦函数将ris辅助信号指向MIMO接收器的中点。我们证明了该解在近轴设置下的视距通道中是精确的。借助视距(自由空间)通道中的大量数值模拟,我们表明所提出的方法提供的性能(速率和自由度)接近于在高计算复杂度下通过数值解决非凸优化问题获得的性能。此外,我们还表明,在大多数考虑的案例研究中,它提供的性能接近EMO(非对角RIS)所达到的性能。
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引用次数: 12
An improved segmentation technique for multilevel thresholding of crop image using cuckoo search algorithm based on recursive minimum cross entropy 基于递推最小交叉熵的杜鹃搜索算法改进农作物图像多级阈值分割技术
Pub Date : 2022-08-08 DOI: 10.1049/sil2.12148
Arun Kumar, Adarsh Kumar, A. Vishwakarma, H. Lee
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引用次数: 4
Advances in image processing using machine learning techniques 使用机器学习技术的图像处理进展
Pub Date : 2022-08-03 DOI: 10.1049/sil2.12146
G. Jovanovic-Dolecek, Nam-Hyung Cho
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引用次数: 3
An unsupervised monocular image depth prediction algorithm using Fourier domain analysis 基于傅里叶域分析的无监督单眼图像深度预测算法
Pub Date : 2022-05-14 DOI: 10.1049/sil2.12135
Lifang Chen, Xiaojiao Tang
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引用次数: 0
On theoretical justification of the forward-backward algorithm for the variational learning of Bayesian hidden Markov models 贝叶斯隐马尔可夫模型变分学习正反向算法的理论论证
Pub Date : 2022-04-26 DOI: 10.1049/sil2.12129
Tao Li, Jinwen Ma
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引用次数: 3
Convolutional neural network and Bi-directional long short memory hybrid deep network aided infrared image classification framework for non-contact monitoring of overhead insulators 基于卷积神经网络和双向长短记忆混合深度网络的架空绝缘子非接触监测红外图像分类框架
Pub Date : 2022-04-21 DOI: 10.1049/sil2.12130
A. K. Das, Suhas Deb, Soumya Chatterjee, B. Chatterjee, S. Dalai
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引用次数: 1
Multi-graph convolutional clustering network 多图卷积聚类网络
Pub Date : 2022-03-18 DOI: 10.1049/sil2.12116
Boyue Wang, Yifan Wang, Xiaxia He, Yongli Hu, Baocai Yin
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引用次数: 2
The analysis of completely perturbed model based on RIP via orthogonal least squares 基于RIP的完全摄动模型的正交最小二乘分析
Pub Date : 2022-03-17 DOI: 10.1049/sil2.12115
Haifeng Li, Hao Ying
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引用次数: 0
Ship images detection and classification based on convolutional neural network with multiple feature regions 基于多特征区域卷积神经网络的船舶图像检测与分类
Pub Date : 2022-02-08 DOI: 10.1049/sil2.12104
Zhijing Xu, Jiu-Hou Sun, Yuhao Huo
{"title":"Ship images detection and classification based on convolutional neural network with multiple feature regions","authors":"Zhijing Xu, Jiu-Hou Sun, Yuhao Huo","doi":"10.1049/sil2.12104","DOIUrl":"https://doi.org/10.1049/sil2.12104","url":null,"abstract":"","PeriodicalId":272888,"journal":{"name":"IET Signal Process.","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127258908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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