Signal Processing最新文献_第4页

A simple method for secret-key generation between mobile users across networks 跨网络移动用户之间密匙生成的简单方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-22 DOI: 10.1016/j.sigpro.2024.109744

Yingbo Hua

引用次数: 0

Exploiting high-precision AoA estimation method using CSI from a single WiFi station 利用单个 WiFi 站的 CSI 探索高精度 AoA 估算方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-21 DOI: 10.1016/j.sigpro.2024.109750

Jingxue Bi , Meiqi Zhao , Guoqiang Zheng , Taoyi Chen , Hongji Cao , Guobiao Yao , Fei Su , Teng Wang , Wanqiu Li , Guojian Zhang

{"title":"Exploiting high-precision AoA estimation method using CSI from a single WiFi station","authors":"Jingxue Bi , Meiqi Zhao , Guoqiang Zheng , Taoyi Chen , Hongji Cao , Guobiao Yao , Fei Su , Teng Wang , Wanqiu Li , Guojian Zhang","doi":"10.1016/j.sigpro.2024.109750","DOIUrl":"10.1016/j.sigpro.2024.109750","url":null,"abstract":"<div><div>The accuracy of estimating the angle of arrival (AoA) using wireless fidelity (WiFi) channel state information (CSI) has been a topic of intense interest in the fields of the Internet of Things, location-based services, etc. We propose a high-precision method of AoA estimation of the direct path (DP) using WiFi CSI from a single station. It contains three stages: data preprocessing, AoA-time of flight (ToF) joint estimation for all paths, and the DP's AoA estimation. Firstly, phase calibration, linear transform, and multiple-layer filtering are accordingly conducted after CSI collection in the preprocessing stage to output the denoised CSI. Then, the AoA and ToF values for all paths are simultaneously obtained utilizing a spatial smoothing multiple signal classification (MUSIC) algorithm. Finally, the density-based spatial clustering for noise applications (DBSCAN) algorithm divides all the AoA and ToF values into several clusters. The target cluster that meets the requirements of maximum counts and minimum mean ToF is subsequently selected. The weighted centroid AoA value of the target cluster is regarded as the AoA of the DP. AoA estimation experiments using different sampling packets are conducted in a small conference room with an Intel 5300 network interface card along a straight line. The proposed method could recognize the DP with a rate of 100 percent and estimate the AoA of the DP with a mean absolute error of 2° and root mean square error of 2.82° Compared with SpotFi and hierarchical clustering–logistic regression systems, the proposed method improves AoA estimation accuracy by at least 75 %. Therefore, the proposed method could achieve a high-precision estimation of the AoA of the DP in the case 26 of different short distances.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109750"},"PeriodicalIF":3.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predictive modeling using Copula Particle Filter and Adaptive Network-Based Fuzzy Inference 使用 Copula 粒子过滤器和基于自适应网络的模糊推理进行预测建模

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-20 DOI: 10.1016/j.sigpro.2024.109747

Mohsen Abedini, Hamid Jazayeriy, Javad Kazemitabar

{"title":"Predictive modeling using Copula Particle Filter and Adaptive Network-Based Fuzzy Inference","authors":"Mohsen Abedini, Hamid Jazayeriy, Javad Kazemitabar","doi":"10.1016/j.sigpro.2024.109747","DOIUrl":"10.1016/j.sigpro.2024.109747","url":null,"abstract":"<div><div>This paper introduces a novel prediction algorithm, CPF-ANFIS, designed to overcome the challenges posed by high-dimensional input data in Adaptive Neuro-Fuzzy Inference Systems (ANFIS). ANFIS's performance deteriorates with increasing input dimensionality due to the distortion of its membership functions. To address this limitation, CPF-ANFIS leverages a two-stage approach: A Copula Particle Filter (CPF) for robust state estimation and ANFIS for nonlinear mapping. By incorporating copulas, CPF effectively addresses the impoverishment and degeneracy problems commonly encountered in traditional particle filters. This enhanced robustness allows for more accurate state estimation, which in turn improves the overall performance of the CPF-ANFIS algorithm. By decoupling state estimation from nonlinear modeling, CPF-ANFIS effectively mitigates the curse of dimensionality. The proposed method is evaluated on real-world applications, such as hybrid PV-wind systems and SLAM. Experimental results demonstrate that CPF-ANFIS consistently outperforms ANFIS and the Copula Particle Filter individually, as well as previously proposed methods such as ANFIS-PF, highlighting its effectiveness in achieving accurate predictions under challenging conditions. The results show that the CPF-ANFIS algorithm increases prediction accuracy by at least 5% compared to using each algorithm separately.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109747"},"PeriodicalIF":3.4,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive compressed learning boosts both efficiency and utility of differentially private federated learning 自适应压缩学习提高了差异化私人联合学习的效率和效用

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-19 DOI: 10.1016/j.sigpro.2024.109742

Min Li, Di Xiao, Lvjun Chen

{"title":"Adaptive compressed learning boosts both efficiency and utility of differentially private federated learning","authors":"Min Li, Di Xiao, Lvjun Chen","doi":"10.1016/j.sigpro.2024.109742","DOIUrl":"10.1016/j.sigpro.2024.109742","url":null,"abstract":"<div><div>In the federated learning (FL) research field, current research is confronted with several pivotal challenges, e.g., data privacy, model utility and communication efficiency. Furthermore, these challenges are further amplified by statistical data heterogeneous in the FL system. Thus, a novel <strong>C</strong>ommunication-efficient and <strong>U</strong>tility-assured <strong>G</strong>aussian differential privacy-based <strong>P</strong>ersonalized <strong>F</strong>ederated <strong>A</strong>daptive <strong>C</strong>ompressed <strong>L</strong>earning method, called CUG-PFACL, is proposed. Specifically, an end-to-end local adaptive compressed learning strategy is designed, including three crucial modules, namely the measurement matrix, the personalized compressed data transformation and the local model. Especially, jointly training the measurement matrix module and the personalized compressed data transformation module can mitigate the inherent statistical heterogeneity while preserving all important characteristics of the compressed private data of each local client, and alleviate the additional heterogeneity induced by Gaussian differential privacy in each global communication round. Numerous experimental simulation and comparisons demonstrate that CUG-PFACL has three notable advantages: data privacy guarantee, enhanced personalized model utility and high-efficient communication.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109742"},"PeriodicalIF":3.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An augmented complex-valued gradient-descent total least-squares algorithm for noncircular signals 非环形信号的增强复值梯度后移全最小二乘算法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-17 DOI: 10.1016/j.sigpro.2024.109740

Qi Zhang, Zhe Li, Honglei Jin, Xiaoping Chen

{"title":"An augmented complex-valued gradient-descent total least-squares algorithm for noncircular signals","authors":"Qi Zhang, Zhe Li, Honglei Jin, Xiaoping Chen","doi":"10.1016/j.sigpro.2024.109740","DOIUrl":"10.1016/j.sigpro.2024.109740","url":null,"abstract":"<div><div>In this paper, we propose a novel augmented complex-valued gradient-descent total least-squares (ACGDTLS) adaptive filter for processing noisy input and output noncircular complex-valued signals. First, a Rayleigh quotient cost function is formulated by incorporating augmented complex-valued statistics and the output-to-input-noise-ratio within the widely linear error-in-variable model, whereby the ACGDTLS is developed using the gradient-descent approach. Next, rigorous analysis is conducted to establish a conservative step-size bound guaranteeing mean convergence, a closed-form expression for the steady-state mean-squared deviation, and the algorithm’s computational complexity. Finally, through simulations conducted in system identification, wind/speech prediction, and stereophonic acoustic echo cancellation, the analytical findings are validated, and the proposed ACGDTLS filter demonstrates superior estimation accuracy compared to the augmented complex-valued least-mean-square algorithm and two state-of-the-art bias-compensated methods. Remarkably, this performance advantage persists across a wide range of step-sizes, input noise variances, and output noise variances.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109740"},"PeriodicalIF":3.4,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stable successive Neural Image Compression via coherent demodulation-based transformation 通过基于相干解调的变换实现稳定的连续神经图像压缩

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-16 DOI: 10.1016/j.sigpro.2024.109741

Youneng Bao , Wen Tan , Mu Li , Fanyang Meng , Yongsheng Liang

{"title":"Stable successive Neural Image Compression via coherent demodulation-based transformation","authors":"Youneng Bao , Wen Tan , Mu Li , Fanyang Meng , Yongsheng Liang","doi":"10.1016/j.sigpro.2024.109741","DOIUrl":"10.1016/j.sigpro.2024.109741","url":null,"abstract":"<div><div>Neural Image Compression (NIC) has made significant strides in recent years. However, the existing NIC methods demonstrate instability issues during iterative re-compression cycles, which can degrade image quality with each cycle. This paper introduces a novel framework aimed at enhancing the stability of NIC methods. We first conducted a theoretical analysis and identified that the instability in current NIC methods stems from a lack of idempotency in transformations. Drawing from the domain of signal processing, we then examined the principles of idempotency in coherent demodulation techniques. This examination led to the identification of three foundational principles that inform the design of stable transformations: the cosine function, parameter sharing, and low-pass filtering. Leveraging these insights, we propose the innovative Coherent Demodulation-based Transformation (CDT), which is designed to address the stability challenges in NIC by incorporating these principles into its architecture. The experimental results suggest that CDT not only significantly improve the re-compression stability but also preserves the codec’s rate–distortion performance. Furthermore, it can be broadly applied in current NIC structures. The effectiveness of the module endorses the viability of designing transformation networks based on Coherent Demodulation principles, playing a crucial role in enhancing stability of NIC. The code will be available at <span><span>https://github.com/baoyu2020/Stable_SuccessiveNIC</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109741"},"PeriodicalIF":3.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An index of effective number of variables for uncertainty and reliability analysis in model selection problems 用于模型选择问题中不确定性和可靠性分析的有效变量数量指标

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-16 DOI: 10.1016/j.sigpro.2024.109735

Luca Martino, Eduardo Morgado, Roberto San Millán Castillo

引用次数: 0

Content adaptive JND profile by leveraging HVS inspired channel modeling and perception oriented energy allocation optimization 利用受 HVS 启发的信道建模和以感知为导向的能量分配优化，实现内容自适应 JND 配置文件

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-15 DOI: 10.1016/j.sigpro.2024.109734

Haibing Yin , Xia Wang , Guangtao Zhai , Xiaofei Zhou , Chenggang Yan

{"title":"Content adaptive JND profile by leveraging HVS inspired channel modeling and perception oriented energy allocation optimization","authors":"Haibing Yin , Xia Wang , Guangtao Zhai , Xiaofei Zhou , Chenggang Yan","doi":"10.1016/j.sigpro.2024.109734","DOIUrl":"10.1016/j.sigpro.2024.109734","url":null,"abstract":"<div><div>The existing just noticeable difference (JND) models consider the effects of various covariates, however, they rarely account for the fusion relationship between the covariates, i.e., they lack a holistic understanding of the mechanisms of visual perception and disregarding the significant impact of energy consumption on visual perception. In fact, visual perception is no exception to the rule that nerve activities and energy supply are inextricably linked. Based on this insight, this paper proposes a novel JND estimation model employing content-adaptive energy allocation. Primarily, the information theory is applied to the visual perception system by conceptualizing human visual system (HVS) as an information communication framework. Then, leveraging the relationship between energy consumption and information perception, this paper quantitatively measures the HVS energy consumption as uniform metric to describe the complicated and heterogeneous HVS perception process, and then construct JND model by fusing low-level and Semantic-level features. Numerous simulation results verify that the proposed JND model is significantly competitive with other frontier models and highly compatible with HVS.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109734"},"PeriodicalIF":3.4,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalized sidelobe canceller based adaptive multiple-input multiple-output radar array beamforming under scenario mismatches 场景错配下基于广义侧叶消除器的自适应多输入多输出雷达阵列波束成形

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-15 DOI: 10.1016/j.sigpro.2024.109739

Cheng-Jie Wang , Ju-Hong Lee

{"title":"Generalized sidelobe canceller based adaptive multiple-input multiple-output radar array beamforming under scenario mismatches","authors":"Cheng-Jie Wang , Ju-Hong Lee","doi":"10.1016/j.sigpro.2024.109739","DOIUrl":"10.1016/j.sigpro.2024.109739","url":null,"abstract":"<div><div>It is well known that the performance of an adaptive MIMO radar array fully depends on the precise steering control and is deteriorated by even a small scenario mismatch. This paper presents an advanced generalized sidelobe canceller (AGSC) based adaptive MIMO radar array beamformer with robustness against the effect due to scenario mismatches. A new signal blocking matrix is developed for effectively blocking the desired signal when the adaptive beamforming is performed under multiple scenario mismatches. The novelty of the new signal blocking matrix is that it contains two additional matrix components in addition to the conventional blocking matrix. The first one is a matrix made up of the basis orthogonal to some appropriately designed derivative constraint vector. It avoids the possible leakage of the desired signal due to scenario mismatches. The other one is a matrix made up of the dominant eigenvectors associated with the correlation matrix of the blocked data vector at the output of the first matrix component. It is employed to preserve all of the interference signals. As a result, the whole blocking operation can delete the desired signal and save the interference signals under multiple scenario mismatches. Hence, the AGSC based adaptive MIMO radar beamformer effectively deals with the performance degradation caused by scenario mismatches without resorting to any robust optimization algorithms. Performance analysis and complexity evaluation regarding the AGSC based adaptive MIMO radar beamformer are presented. Simulation results are also provided for confirmation and comparison.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"227 ","pages":"Article 109739"},"PeriodicalIF":3.4,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interacting multiple model adaptive robust Kalman filter for process and measurement modeling errors simultaneously 同时处理过程和测量建模误差的交互式多模型自适应鲁棒卡尔曼滤波器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-10-15 DOI: 10.1016/j.sigpro.2024.109743

Baojian Yang, Huaiguang Wang, Zhiyong Shi

引用次数: 0