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In distributed target-tracking sensor networks, efficient data gathering methods are necessary to save communication resources and assure information accuracy. This paper proposes a Feedback (FB) distributed data-gathering method which lets…

系统与控制 · 电气工程与系统科学 2025-08-07 Hyeongmin Choe , SooJean Han

Semantic communication has emerged as a promising approach for improving efficient transmission in the next generation of wireless networks. Inspired by the success of semantic communication in different areas, we aim to provide a new…

图像与视频处理 · 电气工程与系统科学 2023-12-11 Zhenguo Zhang , Qianqian Yang , Shibo He , Jiming Chen

Haptic teleoperation typically demands sub-millisecond latency and ultra-high reliability (99.999%) in Tactile Internet. At a 1 kHz haptic signal sampling rate, this translates into an extremely high packet transmission rate, posing…

信号处理 · 电气工程与系统科学 2026-03-25 Georgios Kokkinis , Alexandros Iosifidis , Qi Zhang

This paper considers target tracking based on a beacon signal's time-difference-of-arrival (TDOA) to a group of cooperating sensors. The sensors receive a reflected signal from the target where the time-of-arrival (TOA) renders the distance…

系统与控制 · 电气工程与系统科学 2024-12-24 Mohammadreza Doostmohammadian , Themistoklis Charalambous

Sensor-based human activity recognition is a key technology for many human-centered intelligent applications. However, this research is still in its infancy and faces many unresolved challenges. To address these, we propose a comprehensive…

信号处理 · 电气工程与系统科学 2025-04-08 Hanyu Liu , Ying Yu , Hang Xiao , Siyao Li , Xuze Li , Jiarui Li , Haotian Tang

This paper investigates task-oriented communication for multi-device cooperative edge inference, where a group of distributed low-end edge devices transmit the extracted features of local samples to a powerful edge server for inference.…

信号处理 · 电气工程与系统科学 2023-09-13 Jiawei Shao , Yuyi Mao , Jun Zhang

In convolutional neural networks (CNNs), downsampling operations are crucial to model performance. Although traditional downsampling methods (such as maximum pooling and cross-row convolution) perform well in feature aggregation, receptive…

计算机视觉与模式识别 · 计算机科学 2025-07-22 Wenbo Yue , Chang Li , Guoping Xu

Although wireless and IP-based access to video content gives a new degree of freedom to the viewers, the risk of severe block losses caused by transmission errors is always present. The purpose of this paper is to present a new method for…

图像与视频处理 · 电气工程与系统科学 2022-07-04 Jürgen Seiler , André Kaup

The purpose of this paper is to introduce a very efficient algorithm for signal extrapolation. It can widely be used in many applications in image and video communication, e. g. for concealment of block errors caused by transmission errors…

图像与视频处理 · 电气工程与系统科学 2022-07-05 Jürgen Seiler , André Kaup

In teleradiology, medical images are transmitted to offsite radiologists for interpretation and the dictation report is sent back to the original site to aid timely diagnosis and proper patient care. Although teleradiology offers great…

We consider how to most efficiently leverage teleoperator time to collect data for learning robust image-based value functions and policies for sparse reward robotic tasks. To accomplish this goal, we modify the process of data collection…

机器人学 · 计算机科学 2022-10-06 David Brandfonbrener , Stephen Tu , Avi Singh , Stefan Welker , Chad Boodoo , Nikolai Matni , Jake Varley

This contribution introduces a novel signal extrapolation algorithm and its application to image error concealment. The signal extrapolation is carried out by iteratively generating a model of the signal suffering from distortion. Thereby,…

图像与视频处理 · 电气工程与系统科学 2022-07-15 Jürgen Seiler , André Kaup

This paper studies distributed resource block (RB) allocation in wideband orthogonal frequency-division multiplexing (OFDM) cell-free systems. We propose a novel distributed sequential algorithm and its two variants, which optimize RB…

信号处理 · 电气工程与系统科学 2025-03-11 Yang Ma , Shengqian Han , Chenyang Yang

The widespread adoption of mobile communication technology has led to a severe shortage of spectrum resources, driving the development of cognitive radio technologies aimed at improving spectrum utilization, with spectrum sensing being the…

信号处理 · 电气工程与系统科学 2025-04-11 Shilian Zheng , Zhihao Ye , Luxin Zhang , Keqiang Yue , Zhijin Zhao

This article considers the problem of delay optimal bundling of the input symbols into transmit packets in the entry point of a wireless sensor network such that the link delay is minimized under an arbitrary arrival rate and a given…

网络与互联网体系结构 · 计算机科学 2016-11-15 Abolfazl Razi , Fatemeh Afghah , Ali Abedi

Digital backpropagation (DBP) is one of the most effective techniques for compensating nonlinear distortions in coherent optical fiber communication systems. However, its practical application to wideband transmission remains limited by…

This work considers distributed sensing and transmission of sporadic random samples. Lower bounds are derived for the reconstruction error of a single normally or uniformly-distributed finite-dimensional vector imperfectly measured by a…

信息论 · 计算机科学 2015-11-20 Ayşe Ünsal , Raymond Knopp

This letter proposes a Message Passing (MP) based algorithm for demodulating the time-encoded digital modulation signal. The proposed algorithm processes the spikes generated by the Time-Encoding Machine (TEM) directly on a per-spike basis,…

信号处理 · 电气工程与系统科学 2025-12-09 Yuan Xu , Wenhui Xiong

In this paper, we propose feature-based federated transfer learning as a novel approach to improve communication efficiency by reducing the uplink payload by multiple orders of magnitude compared to that of existing approaches in federated…

机器学习 · 计算机科学 2024-05-16 Feng Wang , M. Cenk Gursoy , Senem Velipasalar

Although Federated Learning has been widely studied in recent years, there are still high overhead expenses in each communication round for large-scale models such as Vision Transformer. To lower the communication complexity, we propose a…

机器学习 · 计算机科学 2026-04-21 Junkang Liu , Fanhua Shang , Yuanyuan Liu , Hongying Liu , Yuangang Li , YunXiang Gong
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