Pub Date : 2025-03-07DOI: 10.1109/tsp.2025.3549222
Meiyi Zhu, Matteo Zecchin, Sangwoo Park, Caili Guo, Chunyan Feng, Petar Popovski, Osvaldo Simeone
{"title":"Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints","authors":"Meiyi Zhu, Matteo Zecchin, Sangwoo Park, Caili Guo, Chunyan Feng, Petar Popovski, Osvaldo Simeone","doi":"10.1109/tsp.2025.3549222","DOIUrl":"https://doi.org/10.1109/tsp.2025.3549222","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"35 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575097","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 : 2025-03-04DOI: 10.1109/tsp.2025.3546574
Siyuan Yu, Wei Chen, H. Vincent Poor
{"title":"Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework","authors":"Siyuan Yu, Wei Chen, H. Vincent Poor","doi":"10.1109/tsp.2025.3546574","DOIUrl":"https://doi.org/10.1109/tsp.2025.3546574","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"15 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546460","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 : 2025-02-28DOI: 10.1109/tsp.2025.3546169
James Z. Hare, Yuchen Liang, Lance Kaplan, Venugopal V. Veeravalli
{"title":"Bayesian Two-Sample Hypothesis Testing using the Uncertain Likelihood Ratio: Improving the Generalized Likelihood Ratio Test","authors":"James Z. Hare, Yuchen Liang, Lance Kaplan, Venugopal V. Veeravalli","doi":"10.1109/tsp.2025.3546169","DOIUrl":"https://doi.org/10.1109/tsp.2025.3546169","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"32 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526157","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 : 2025-02-26DOI: 10.1109/tsp.2025.3546328
Sihua Wang, Huayan Guo, Xu Zhu, Changchuan Yin, Vincent K. N. Lau
{"title":"Communication-Efficient Distributed Bayesian Federated Learning over Arbitrary Graphs","authors":"Sihua Wang, Huayan Guo, Xu Zhu, Changchuan Yin, Vincent K. N. Lau","doi":"10.1109/tsp.2025.3546328","DOIUrl":"https://doi.org/10.1109/tsp.2025.3546328","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"90 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143507268","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 : 2025-02-26DOI: 10.1109/tsp.2025.3546484
Charles Hovine, Alexander Bertrand
{"title":"Distributed Adaptive Spatial Filtering with Inexact Local Solvers","authors":"Charles Hovine, Alexander Bertrand","doi":"10.1109/tsp.2025.3546484","DOIUrl":"https://doi.org/10.1109/tsp.2025.3546484","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"2 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143507269","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 : 2025-02-26DOI: 10.1109/TSP.2025.3546458
Tal Vol;Loai Danial;Nir Shlezinger
The ability to process signals in digital form depends on analog-to-digital converters (ADCs). Traditionally, ADCs are designed to ensure that the digital representation closely matches the analog signal. However, recent studies have shown that significant power and memory savings can be achieved through task-based acquisition, where the acquisition process is tailored to the downstream processing task. An emerging technology for task-based acquisition involves the use of memristors, which are considered key enablers for neuromorphic computing. Memristors can implement ADCs with tunable mappings, allowing adaptation to specific system tasks or power constraints. In this work, we study task-based acquisition for a generic classification task using memristive ADCs. We consider the unique characteristics of this such neuromorphic ADCs, including their power consumption and noisy read-write behavior, and propose a physically compliant model based on resistive successive approximation register ADCs integrated with memristor components, enabling the adjustment of quantization regions. To optimize performance, we introduce a data-driven algorithm that jointly tunes task-based memristive ADCs alongside both digital and analog processing. Our design addresses the inherent stochasticity of memristors through power-aware distillation, complemented by a specialized learning algorithm that adapts to their unique analog-to-digital mapping. The proposed approach is shown to enhance accuracy by up to 27% and reduce power consumption by up to 66% compared to uniform ADCs. Even under noisy conditions, our method achieves substantial gains, with accuracy improvements of up to 19% and power reductions of up to 57%. These results highlight the effectiveness of our power-aware neuromorphic ADCs in improving system performance across diverse tasks.
{"title":"Learning Task-Based Trainable Neuromorphic ADCs via Power-Aware Distillation","authors":"Tal Vol;Loai Danial;Nir Shlezinger","doi":"10.1109/TSP.2025.3546458","DOIUrl":"10.1109/TSP.2025.3546458","url":null,"abstract":"The ability to process signals in digital form depends on analog-to-digital converters (ADCs). Traditionally, ADCs are designed to ensure that the digital representation closely matches the analog signal. However, recent studies have shown that significant power and memory savings can be achieved through <italic>task-based acquisition</i>, where the acquisition process is tailored to the downstream processing task. An emerging technology for task-based acquisition involves the use of memristors, which are considered key enablers for neuromorphic computing. Memristors can implement ADCs with tunable mappings, allowing adaptation to specific system tasks or power constraints. In this work, we study task-based acquisition for a generic classification task using memristive ADCs. We consider the unique characteristics of this such neuromorphic ADCs, including their power consumption and noisy read-write behavior, and propose a physically compliant model based on resistive successive approximation register ADCs integrated with memristor components, enabling the adjustment of quantization regions. To optimize performance, we introduce a data-driven algorithm that jointly tunes task-based memristive ADCs alongside both digital and analog processing. Our design addresses the inherent stochasticity of memristors through power-aware distillation, complemented by a specialized learning algorithm that adapts to their unique analog-to-digital mapping. The proposed approach is shown to enhance accuracy by up to 27% and reduce power consumption by up to 66% compared to uniform ADCs. Even under noisy conditions, our method achieves substantial gains, with accuracy improvements of up to 19% and power reductions of up to 57%. These results highlight the effectiveness of our power-aware neuromorphic ADCs in improving system performance across diverse tasks.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"1246-1261"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143507278","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 : 2025-02-25DOI: 10.1109/tsp.2025.3543721
Wei Liu
{"title":"Event-Triggered State Estimation Through Confidence Level","authors":"Wei Liu","doi":"10.1109/tsp.2025.3543721","DOIUrl":"https://doi.org/10.1109/tsp.2025.3543721","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"24 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495420","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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