Pub Date : 2026-02-11DOI: 10.1109/tsp.2026.3663357
Danish Nisar, Saif Khan Mohammed, Ronny Hadani, Ananthanarayanan Chockalingam, Robert Calderbank
{"title":"Zak-OTFS for Identification of Linear Time-Varying Systems","authors":"Danish Nisar, Saif Khan Mohammed, Ronny Hadani, Ananthanarayanan Chockalingam, Robert Calderbank","doi":"10.1109/tsp.2026.3663357","DOIUrl":"https://doi.org/10.1109/tsp.2026.3663357","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"34 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161193","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}
Pub Date : 2026-02-11DOI: 10.1109/tsp.2026.3663449
Stephan Weiss, Sebastian J. Schlecht, Marc Moonen
{"title":"Best Least Squares Paraunitary Approximation: Analytic Procrustes Problem","authors":"Stephan Weiss, Sebastian J. Schlecht, Marc Moonen","doi":"10.1109/tsp.2026.3663449","DOIUrl":"https://doi.org/10.1109/tsp.2026.3663449","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"46 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161192","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}
Pub Date : 2026-02-09DOI: 10.1109/tsp.2026.3662488
Kaito Nitani, Seisuke Kyochi
{"title":"A Design of Denser-Graph-Frequency Graph Fourier Frames for Graph Signal Analysis","authors":"Kaito Nitani, Seisuke Kyochi","doi":"10.1109/tsp.2026.3662488","DOIUrl":"https://doi.org/10.1109/tsp.2026.3662488","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"63 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146090","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}
Pub Date : 2026-02-06DOI: 10.1109/tsp.2026.3661556
Yumeng Zhang, Huayan Guo, Vincent K. N. Lau
{"title":"A Novel Pilot Scheme for Uplink Channel Estimation for Sub–array Structured ELAA in XL–MIMO systems","authors":"Yumeng Zhang, Huayan Guo, Vincent K. N. Lau","doi":"10.1109/tsp.2026.3661556","DOIUrl":"https://doi.org/10.1109/tsp.2026.3661556","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"75 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134872","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}
Pub Date : 2026-02-06DOI: 10.1109/tsp.2026.3661988
Hancheng Zhu, Zongze Li, Yik-Chung Wu, H. Vincent Poor
{"title":"Countering Collaborative Eavesdroppers under Imperfect CSI: Outage Probability Constraint Transformation and Zeroth-Order Optimization","authors":"Hancheng Zhu, Zongze Li, Yik-Chung Wu, H. Vincent Poor","doi":"10.1109/tsp.2026.3661988","DOIUrl":"https://doi.org/10.1109/tsp.2026.3661988","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"293 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134873","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}
Pub Date : 2026-01-30DOI: 10.1109/TSP.2026.3657450
Charlotte Lacoquelle;Xavier Pucel;Louise Travé Massuyès;Axel Reymonet;Benoît Enaux
This paper addresses the problem of detecting time series outliers, focusing on systems with repetitive behavior, such as industrial robots operating on production lines. Notable challenges arise from the fact that a task performed multiple times may exhibit different duration in each repetition and that the time series reported by the sensors are irregularly sampled because of data gaps. Given the targeted industrial context, there is a strong requirement for frugality both in terms of input data and method parametrization. Consequently, the proposed approach remains lightweight, robust, and largely self-sufficient to ensure practical deployment and ease of maintenance. The overall approach, named WarpEd Time Series ANomaly Detection (wetsand), makes use of the Dynamic Time Warping algorithm and its variants because they are suited to the distorted nature of the time series. The experiments show that wetsand scales to large signals, computes human-friendly prototypes, works with very little data, and outperforms some general purpose anomaly detection approaches such as autoencoders.
{"title":"Warped Time Series Anomaly Detection","authors":"Charlotte Lacoquelle;Xavier Pucel;Louise Travé Massuyès;Axel Reymonet;Benoît Enaux","doi":"10.1109/TSP.2026.3657450","DOIUrl":"10.1109/TSP.2026.3657450","url":null,"abstract":"This paper addresses the problem of detecting time series outliers, focusing on systems with repetitive behavior, such as industrial robots operating on production lines. Notable challenges arise from the fact that a task performed multiple times may exhibit different duration in each repetition and that the time series reported by the sensors are irregularly sampled because of data gaps. Given the targeted industrial context, there is a strong requirement for frugality both in terms of input data and method parametrization. Consequently, the proposed approach remains lightweight, robust, and largely self-sufficient to ensure practical deployment and ease of maintenance. The overall approach, named WarpEd Time Series ANomaly Detection (<sc>wetsand</small>), makes use of the Dynamic Time Warping algorithm and its variants because they are suited to the distorted nature of the time series. The experiments show that <sc>wetsand</small> scales to large signals, computes human-friendly prototypes, works with very little data, and outperforms some general purpose anomaly detection approaches such as autoencoders.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"74 ","pages":"439-452"},"PeriodicalIF":5.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089994","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}
Pub Date : 2026-01-30DOI: 10.1109/tsp.2026.3659742
Thomas Kropfreiter, Jason L. Williams, Florian Meyer
{"title":"Association-Based Track-Before-Detect with Object Contribution Probabilities","authors":"Thomas Kropfreiter, Jason L. Williams, Florian Meyer","doi":"10.1109/tsp.2026.3659742","DOIUrl":"https://doi.org/10.1109/tsp.2026.3659742","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"184 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089997","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}
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