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Adaptive IMM Algorithm Based on Variational Inference for Multiple Maneuvering Extended Targets Tracking

Advances in Astronautics 2025年 1-15页

作者： Wang, Shenghua Li, Renxian Men, Chenkai Cao, Yunhe Yeo, Tat-Soon School of Communications and Information Engineering and School of Artificial Intelligence Xi’an University of Posts and Telecommunications Xi’an China National Lab of Radar Signal Processing Xidian University Xi’an China The Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

In order to track multiple maneuvering extended targets accurately, an adaptive interacting multiple model algorithm based on variational inference (AIMM-VI) is proposed. An augmented state is constructed to cater for time-varying orientation angle and track realistic shape changes, resulting in better elliptical shape estimation and tracking accuracy. Multiple measurements from multiple extended targets are effectively assigned to corresponding targets through the marginal association probability distribution criterion, and the variational inference is used to accurately estimate the augmented state and shape information, which greatly improves the parameters estimation performance. The residual and likelihood functions are updated in real-time according to the results of variational inference, allowing for the updating of the model probability in real-time. The Markov probability transfer matrix is subsequently adaptively updated by the compression ratio, which makes the algorithm more adaptable to maneuvering target and significantly improves the adaptability and robustness of the algorithm. The final simulation and experiment results show that the proposed algorithm can effectively improve the tracking performance of multiple maneuvering extended targets.

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Nonvolatile electrical switching of optical and valleytronic properties of interlayer excitons

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Light(Science & Applications) 2022年第2期11卷 221-229页

作者： Tong Ye Yongzhuo Li Junze Li Hongzhi Shen Junwen Ren Cun-Zheng Ning Dehui Li School of Optical and Electronic Information Huazhong University of Science and Technology430074 WuhanChina Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology430074 WuhanChina Department of Electronic Engineering Tsinghua University100084 BeijingChina Frontier Science Center for Quantum Information 100084 BeijingChina School of Electrical Computerand Energy EngineeringArizona State UniversityTempeAZ 85287USA

Long-lived interlayer excitons(IXs)in van der Waals heterostructures(HSs)stacked by monolayer transition metal dichalcogenides(TMDs)carry valley-polarized information and thus could find promising applications in valleytronic *** manipulation approaches for valley polarization of IXs are mainly limited in electrical field/doping,magnetic field or twist-angle ***,we demonstrate an electrochemical-doping method,which is efficient,in-situ and *** find the emission characteristics of IXs in WS2/WSe2 HSs exhibit a large excitonic/valley-polarized hysteresis upon cyclic-voltage sweeping,which is ascribed to the chemical-doping of O2/H2O redox couple trapped between WSe2 and *** advantage of the large hysteresis,a nonvolatile valley-addressable memory is successfully *** valley-polarized information can be non-volatilely switched by electrical gating with retention time exceeding 60 *** findings open up an avenue for nonvolatile valley-addressable memory and could stimulate more investigations on valleytronic devices.

关键词： nonvolatile valley electrical

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Federated Learning Based Integrated Sensing, Communications, and Powering Over 6G Massive-MIMO Mobile Networks

Federated Learning Based Integrated Sensing, Communications,...

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IEEE Conference on computer Communications Workshops, INFOCOM Wksps

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

ISBN: (数字)9798350384475

ISBN: (纸本)9798350384482

To sense mobile users' positions and channel states while simultaneously conveying information for supporting the 6G traffic, the integrated sensing and communication (ISAC) has been proposed as a key technique for sensing and communicating using the same radio frequency and hardware. Moreover, to sup-port energy-constrained and battery-limited wireless networks, simultaneous wireless information and power transfer (SWIPT) has also emerged to simultaneously deliver information and energy to a receiver. To integrate these two techniques, integrated sensing, communications, and powering (ISACP) has been developed to simultaneously sense the targeted mobile users, transmit the information, and deliver the power. However, how to efficiently optimize the power allocation in ISACP schemes to support the 6G traffic has imposed many new challenges not encountered before. To overcome these challenges, in this paper we propose a federated-learning (FL) enabled ISACP scheme to maximize the energy-efficiency over 6G massive MIMO wireless networks. First, we establish the system models for our proposed ISACP and FL schemes. Second, we design the training data set collection in the FL algorithm by sending the pilot signal from mobile users to the massive MIMO base station, and formulate an energy-efficiency maximization problem for the developed ISACP scheme. Third, To solve the formulated energy-efficiency maxi-mization problem, we propose an actorcritic enabled multi-agent based FL mechanism. Finally, we use the numerical analyses to validate and evaluate our developed schemes.

关键词： 6G mobile communication Wireless sensor networks Federated learning Wireless networks Training data Massive MIMO Integrated sensing and communication

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Integrated Sensing, Communications, and Powering for Statistical-QoS Provisioning Over Next-Generation Massive-MIMO Mobile Networks

Integrated Sensing, Communications, and Powering for Statist...

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Annual Conference on information Sciences and Systems (CISS)

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

The integrated sensing and communication (ISAC) has been proposed as a key technique to support the next generation traffic with stringent quality-of-service (QoS) requirements through sensing and communicating using the same radio frequency and hardware. Simultaneous wireless information and power transfer (SWIPT) has also emerged to simultaneously deliver information and energy to a receiver. However, how to integrate ISAC with SWIPT to support the stringent QoS traffic has imposed many new challenges not encountered before. To overcome these challenges, in this paper we propose an integrated sensing, communications, and powering (ISACP) technique for supporting both sensing and communication QoS provisioning while delivering the power over the next-generation wireless networks using massive multiple-input and multiple-output (massive MIMO) communications. First, we develop the system models for the ISACP scheme to simultaneously sense the targeted mobile users (MUs), transmit the information, and deliver the power. Second, we propose a hypothesis testing based scheme to estimate the MU’s angle-of-arrival using the sensing signal. Third, we employ the Cramér-Rao bound (CRB) to measure the performance of sensing and maximize the energy-efficiency with satisfying requirements of both sensing and communication performances. Finally, we use numerical analyses to validate and evaluate our proposed ISACP scheme.

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Smart Multi-Building Energy Monitoring System

Smart Multi-Building Energy Monitoring System

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IEEE International Conference on Electro-information Technology

作者： Saurabh Saluja Colin Prochnow Grant Couper Filip Zivko Xinrui Yu Mikhail Gromov Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A.

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

This paper presents an intelligent system for monitoring energy usage in smart buildings. It functions as a bridge between the smart grid and smart buildings. A web-based platform is designed to monitor sensor data and track power consumption on the grid. AI technology provides tips for energy conservation based on factors such as power usage patterns and weather conditions. The adaptability of our approach allows for the tuning of automated protocols based on evolving power usage patterns and grid conditions. Data is transmitted between the client devices and the central server via a Zigbee network organized in a star formation, allowing for mutual communication. Our implementation results in the improvement of the overall energy efficiency of supported infrastructure while ensuring continuous and optimized operation in case of a bulk grid blackout.

关键词： Smart buildings Energy conservation Zigbee Stars Smart homes Energy efficiency Smart grids

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A Self-Adjustable Blanking Time Short Circuit Protection Circuit for SiC Power MOSFETs 20

A Self-Adjustable Blanking Time Short Circuit Protection Cir...

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20th China International Forum on Solid State Lighting and 9th International Forum on Wide Bandgap Semiconductors, SSLCHINA: IFWS 2023

作者： Liu, Tiantian Cheng, XinHong Ng, Wai Tung Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences National Key Laboratory of Materials for Integrated Circuits China University of Toronto The Edward S. Rogers Sr. Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350385373

This paper proposed a self-adjustable blanking time short circuit protection circuit for SiC power MOSFETs. This circuit consists of a variable blanking time module and a short circuit (SC) detection module. It can automatically set the detection delay for hard switching fault (HSF) and respond quickly to shut down the SiC MOSFET under SC situations. The proposed SC protection circuit does not require a blanking capacitor and can be integrated into the gate driver IC. The proposed SC protection circuit is designed using X-FAB's 0.35 μm BCD technology and is verified using Spectre simulations. HSF and fault under load (FUL) conditions can be quickly detected by the proposed SC protection circuit. With a 600 V bus, the default detection delay is 133 ns for the HSF occurring in the first switching cycle. The detection delay can be varied from 76 to 111 ns by changing the gate resistance $R_{G}$ from 5 to 25 Ω for the subsequent occurrence of HSF. The detection delay for FUL is 52 ns, and it is not affected by $R_{G}$. © 2023 IEEE.

关键词： Silicon carbide

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Statistical Security-QoS Provisioning for mURLLC Over Massive-MIMO Based 6G Mobile Wireless Networks Using FBC

Statistical Security-QoS Provisioning for mURLLC Over Massiv...

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MILCOM, Military Communications Conference

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

ISBN: (数字)9798350374230

ISBN: (纸本)9798350374247

The 6G mobile wireless networks are expected to support massive ultra-reliable and low-latency communications (mURLLC) with stringent requirements on transmission-delay and error-rate bounded quality-of-service (QoS). Correspondingly, the finite blocklength coding (FBC) has developed as the effective technique to implement small-packet communications for the statistical QoS provisioning over mURLLC-based 6G mobile networks. On the other hand, guaranteeing the security for 6G networks services imposes another new dimension of statistical QoS requirements. However, how to efficiently upper-bound the statistical delay and the error probability over time-varying wireless fading channels while guaranteeing the security QoS using FBC remain a challenging problem. To overcome these difficulties, in this paper we propose and develop the new concept of secrecy ϵ-effective capacity as a statistical security QoS scheme to guarantee the performance of statistical delay-bounded QoS, error-rate bounded QoS, and the secrecy-information leak-probability bounded QoS by using the FBC technique. First, we establish the wireless channel model of massive multiple-input-multiple-output (MIMO) for supporting the communications between the base station and multiple mobile users with the existence of an eavesdropper. Second, we define and derive the eavesdropping rate and secrecy rate under the massive MIMO communication. Third, we derive the secrecy-information leak probability and integrate it with statistical delay and error-rate bounded QoS to define the new wireless network communications performance metrics of secrecy ϵ-effective capacity. Finally, we use the numerical analyses to validate and evaluate our developed schemes for supporting statistical delay and error-rate bounded QoS provisioning while upper-bounding the secrecy-information leak probability over 6G mobile networks using massive-MIMO/FBC.

关键词： 6G mobile communication Military communication Measurement Numerical analysis Wireless networks Quality of service Delays Security Communication system security Capacity planning

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ISAC-Driven Channel-State-Estimation for Statistical-QoS Based MURLLC Over 6G M-MIMO Mobile Networks Using FBC

ISAC-Driven Channel-State-Estimation for Statistical-QoS Bas...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Xi Zhang Qixuan Zhu Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas A&M University College Station TX USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The massive ultra-reliable and low-latency communications (mURLLC) services are emerging as a new traffic type to support communications among massive numbers of mobile users (MUs) demanding the stringent delay and error-rate bounded quality-of-services (QoS) requirements in 6G. Correspondingly, the integrated sensing and communications (ISAC) technique can improve various QoS performances through spectrum/hardware sharing between target-sensing and data-communications. In addition, the massive multiple-input multiple-output (massive MIMO) and finite blocklength coding (FBC) have been also widely recognized as the powerful 6G techniques to efficiently support mURLLC. However, how to apply the ISAC technique to accurately sense and estimate the wireless channel state while transmitting the information from the base station to MUs to support mURLLC using massive MIMO and FBC has imposed many new difficulties not encountered before. To conquer these challenges, in this paper we propose the new ISAC performance metrics for statistical-QoS guaranteed mURLLC over 6G massive MIMO mobile networks using FBC. First, we establish system models for ISAC-based architectures. Second, we detect targeted MUs and estimate the channel state using the radar sensing echo. Third, we develop a new ISAC performance metric as a function of the data-communication rate and channel state estimation distortion. Finally, we use the numerical analyses to validate and evaluate our developed ISAC performances in supporting mURLLC-oriented QoS requirements.

关键词： 6G mobile communication Measurement Wireless sensor networks Wireless networks Channel estimation Quality of service Massive MIMO Integrated sensing and communication Distortion Testing

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AI-Based Security Surveillance and Hazard Detection for Train Platform Safety

AI-Based Security Surveillance and Hazard Detection for Trai...

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IEEE International Conference on Electro-information Technology

作者： Alvaro Aparicio Serna Xinrui Yu Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A

ISBN: (数字)9798350330649

ISBN: (纸本)9798350330656

Safety in train platforms is a common concern in railway systems around the world. There are grave risks associated with the tracks and the crowds that often end up in injuries or deaths. Traditional approaches for ensuring safety in train transport networks rely on passive closed-circuit television (CCTV) monitorization that needs constant human attention. This paper proposes an AI-based alternative for detecting anomalies in surveillance videos, that is more efficient and cost-effective than traditional methods. Through Video Instance Segmentation (VIS), this work detects common risks such as overcrowding on the platform, people or objects standing on the edge of the platform, individuals or objects falling onto the tracks, the presence of firearms, and the presence of unattended baggage. The proposed algorithm combines state-of-the-art models like YOLOv8, ByteTrack, and Segment Anything Model (SAM) to classify, track, and segment object detections respectively. Additionally, this paper presents a custom-trained YOLOv8 model for gun detection. The results show that the system can successfully analyze video, create surveillance annotations, detect hazardous situations to alert authorities, and help prevent accidents and incidents on train platforms.

关键词： Instance segmentation Annotations Surveillance Image edge detection Rail transportation Hazards Classification algorithms

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Combining Relative and Absolute Learning Formulations to Predict Emotional Attributes From Speech

Combining Relative and Absolute Learning Formulations to Pre...

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IEEE Workshop on Automatic Speech Recognition and Understanding

作者： Abinay Reddy Naini Shruthi Subramanium Seong-Gyun Leem Carlos Busso Department of Electrical and Computer Engineering Multimodal Signal Processing (MSP) Laboratory The University of Texas at Dallas Richardson TX USA

Predicting absolute scores is the most common speech-emotion recognition (SER) task when predicting emotional attributes (i.e., valence, arousal, and dominance). However, studies have shown that emotion has an ordinal nature where it is more reliable to establish a preference between speech samples (e.g., one sample is more positive than the other). This paper pursues a novel direction to combine absolute and relative learning formulations for SER. The proposed multitask formulation can simultaneously estimate preference between speech samples and predict their absolute score, providing a flexible tool to analyze emotional content in speech. Both tasks mutually complement each other, allowing the model to outperform SER systems that are exclusively trained to either predict absolute scores or estimate preferences. The multitask weights can be set according to the intended applications, prioritizing one task while slightly compromising the performance of the other task.

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