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arXiv 2025年

作者： Stevens, Tristan S.W. Overdevest, Jeroen Nolan, Oisín van Nierop, Wessel L. van Sloun, Ruud J.G. Eldar, Yonina C. Department of Electrical Engineering University of Technology Eindhoven Netherlands Signal Processing Algorithms NXP Semiconductors Netherlands Faculty of Mathematics and Computer Science Weizmann institute of Science Israel

Deep generative models have been studied and developed primarily in the context of natural images and computer vision. This has spurred the development of (Bayesian) methods that use these generative models for inverse problems in image restoration, such as denoising, inpainting, and super-resolution. In recent years, generative modeling for Bayesian inference on sensory data has also gained traction. Nevertheless, the direct application of generative modeling techniques initially designed for natural images on raw sensory data is not straightforward, requiring solutions that deal with high dynamic range signals acquired from multiple sensors or arrays of sensors that interfere with each other, and that typically acquire data at a very high rate. Moreover, the exact physical data-generating process is often complex or unknown. As a consequence, approximate models are used, resulting in discrepancies between model predictions and the observations that are non-Gaussian, in turn complicating the Bayesian inverse problem. Finally, sensor data is often used in real-time processing or decision-making systems, imposing stringent requirements on, e.g., latency and throughput. In this paper, we will discuss some of these challenges and offer approaches to address them, all in the context of high-rate real-time sensing applications in automotive radar and medical imaging. © The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://***/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. © 2025, CC BY-SA.

关键词： Inverse problems

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A hybrid renewable energy system for Hassi Messaoud region of Algeria: Modeling and optimal sizing

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Energy Storage and Saving 2025年第1期4卷 56-69页

作者： Bourek, Yacine Messini, El Mouatez Billah Ammari, Chouaib Guenoune, Mohamed Chabira, Boulerbah Saha, Bipul Krishna Department of Electrical Engineering Faculty of Applied Sciences University of Ouargla Ouargla30000 Algeria Laboratoire LAGE Faculty of Applied Sciences University of Ouargla Ouargla30000 Algeria School of Production Engineering and Management Technical University of Crete Chania73100 Greece Sonatrach - Algerian Petroleum Institute - Hassi Messaoud School Hassi Messaoud30001 Algeria Department of Renewable Energy Faculty of Hydrocarbons Renewable Energy Science Earth and Universe University Kasdi Merbah-Ouargla Ouargla30000 Algeria Laboratory of Image Processing and Radiation University of Sciences and Technology Houari Boumediene Algiers 16111 Algeria Indian Institute of Science Bangalore560012 India

The growing global energy demand and the need to mitigate greenhouse gas emissions have driven the exploration of sustainable and efficient energy solutions. In Algeria, where the energy sector relies heavily on fossil fuels, integrating renewable energy systems is essential for enhancing energy security and reducing environmental impacts. This study focuses on optimizing a hybrid renewable energy system (HRES) for off-grid applications in the Hassi Messaoud region of Algeria to balance technical performance, economic viability, and environmental sustainability. A hybrid system consisting of photovoltaic (PV) panels, wind turbines (WTs), fuel cells (FCs), and diesel generators (DGs) was modeled and optimized using a genetic algorithm (GA). The optimization process aims to minimize the annual cost of the system while ensuring high reliability, as measured by the loss of power supply probability, and maximizing the use of renewable energy. A particle swarm optimization (PSO) approach was also implemented for comparison, highlighting the advantages of the GA in terms of cost distribution and system reliability. The optimized HRES demonstrated that renewable sources (PV and WT) provided 77% of the total energy demand, with an overall system cost of 0.18080 $·kWh−1, significantly lower than recent studies, which reported costs between 0.213 and 0.609 $·kWh−1. FCs contributed 14% to the load, whereas DGs were limited to 8% to minimize emissions, resulting in annual CO2 emissions of 10,865 kg and a relative emission rate of 3.608 gCO2eq·kWh−1. Economic analysis showed that DGs and FCs accounted for 44% and 24% of the annual cost, respectively, highlighting the impact of backup systems in ensuring reliability. Sensitivity analysis under varying load demands and renewable energy availability confirmed the robustness of the system, and the GA approach was found to be more effective than PSO in maintaining cost efficiency and reliability. Additionally, the social analysis high

关键词： Clean energy

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Recursive Subproduct Codes with Reed-Muller-like Structure

arXiv

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arXiv 2024年

作者： Siddheshwar, Aditya Natarajan, Lakshmi Prasad Krishnan, Prasad The Signal Processing and Communications Research Center International Institute of Information Technology Hyderabad500032 India The Department of Electrical Engineering Indian Institute of Technology Hyderabad Sangareddy502284 India

We study a family of subcodes of the m-dimensional product code C⊗m (‘subproduct codes’) that have a recursive Plotkin-like structure, and which include Reed-Muller (RM) codes and Dual Berman codes as special cases. We denote the codes in this family as C⊗[r,m], where 0 ≤ r ≤ m is the ‘order’ of the code. These codes allow a ‘projection’ operation that can be exploited in iterative decoding, viz., the sum of two carefully chosen subvectors of any codeword in C⊗[r,m] belongs to C⊗[r−1,m−1]. Recursive subproduct codes provide a wide range of rates and block lengths compared to RM codes while possessing several of their structural properties, such as the Plotkin-like design, the projection property, and fast ML decoding of first-order codes. Our simulation results for first-order and second-order codes, that are based on a belief propagation decoder and a local graph search algorithm, show instances of subproduct codes that perform either better than or within 0.5 dB of comparable RM codes and CRC-aided Polar codes. Copyright © 2024, The Authors. All rights reserved.

关键词： Iterative decoding

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Exponential Stability Criterion for State-space Interfered Discrete System through External Disturbance

Exponential Stability Criterion for State-space Interfered D...

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International Conference on Power, Control and Embedded Systems (ICPCES)

作者： Pulikonda Mounika Priyanka Kokil Department of Electronics and Communication Engineering Advanced Signal and Image Processing (ASIP) Lab Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai India

ISBN: (数字)9798350310252

ISBN: (纸本)9798350310269

This article deals with stability investigation of state-space fixed-point discrete system using saturation nonlinearity and external interference. A criterion for exponential stability is proposed via a passivity-based approach for an externally interfered nonlinear discrete system. For the discrete system with saturation overflow nonlinearity, we have analyzed the passive behaviour under the effects of external interference and asymptotic stability with zero interference. A comparative study is made available with the previously reported result to highlight the worth and relaxed nature of the proposed work. The criterion developed is in linear matrix inequality (LMI) settings and therefore, numerically less complex. Numerical simulations are made available to showcase the productiveness of the obtained criterion.

关键词： Asymptotic stability Stability criteria Limit-cycles Interference Numerical simulation Control theory Linear matrix inequalities

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Highly efficient near-infrared thermally activated delayed fluorescence organic light-emitting diodes with emission beyond 800 nm

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Journal of Materials Chemistry C 2023年第21期11卷 6981-6988页

作者： Liang, Jing-Xing Tang, Yukun Wang, Xiaofei Zhang, Kai Shih, Yu-Wei Chen, Chia-Hsun Chiu, Tien-Lung Li, Pei Jin Lee, Jiun-Haw Wang, Chuan-Kui Wu, Chung-Chih Fan, Jian Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices Soochow University Jiangsu Suzhou215123 China Department of Electrical Engineering Graduate Institute of Electronics Engineering and Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei10617 Taiwan Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China Department of Chemistry National Taiwan University Taipei10617 Taiwan Department of Electrical Engineering Yuan Ze University Taoyuan32003 Taiwan Graduate Institute of Photonics and Optoelectronics and Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan State Key Laboratory of Structural Chemistry Fujian Institute of Research on Structure of Matter Chinese Academy of Sciences Fujian Fuzhou35002 China

Near-infrared (NIR) emitters are employed in a wide range of applications such as bio-sensors, optical communication devices, and organic light-emitting diodes (OLEDs). The development of NIR thermally activated delayed-fluorescence (TADF) materials lags significantly behind that of platinum complexes and quantum dots. To achieve cost reduction and environmental sustainability, TADF OLEDs have attracted extensive attention in both the academic community and industry in recent years. Herein, a conjugated planar acceptor was applied in a TADF emitter (TCN-TPA) to enhance the intermolecular through-space electronic coupling and redshift the emission spectra at high doping levels. In addition, multiple sub-acceptor units were integrated into a rigid acceptor to narrow the band gap. Importantly, the overall robust configuration of the TCN-TPA molecule led to high photoluminescence quantum yield (PLQY). Consequently, TCN-TPA demonstrated a record-high external quantum efficiency (EQE) of 2.4% at 802 nm and 1.1% at 841 nm among TADF OLEDs in this spectral range. © 2023 The Royal Society of Chemistry

关键词： Energy gap

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Adaptive Kernel Kalman Filter for Magnetic Anomaly Detection-based Metallic Target Tracking

Adaptive Kernel Kalman Filter for Magnetic Anomaly Detection...

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Sensor signal processing for Defence (SSPD)

作者： Mengwei Sun Richard Hodgskin-Brown Mike E. Davies Ian K. Proudler James R. Hopgood Institute of Digital Communications University of Edinburgh Edinburgh U.K. Department of Electronics & Electrical Engineering Electromagnetic Sensing Group University of Manchester Manchester UK Department of Electronic & Electrical Engineering Centre for Signal & Image Processing (CeSIP) University of Strathclyde Glasgow UK

This paper proposes the use of the adaptive kernel Kalman filter (AKKF) to track metallic targets using magnetic anomaly detection (MAD). The proposed AKKF-based approach enables accurate tracking of moving metallic targets using magnetometer sensors, even in the presence of dynamic and unknown magnetic moments. The experimental results demonstrate that the proposed method exhibits favourable tracking and estimation performance with reduced computational complexity compared with the bootstrap particle filter (PF). For example, in magnetic moment strength estimation, the relative root mean square error (RRMSE) of the proposed algorithm using 50 particles can approach 2.5% with a computation time of 0.18 seconds, whereas the RRMSE of the PF using 2000 particles is 4.5% with a computation time of 1.4 seconds. This study highlights the potential of AKKF in MAD for metallic target tracking using magnetometer sensors.

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Cellular Metaverse: Enhancing Real-Time Communications in Virtual World

Cellular Metaverse: Enhancing Real-Time Communications in Vi...

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2023 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2023

作者： Munir, Aisha Siddiqi, Muhammad Zain Jeravongtakul, Siwanart Shah, Shashi Bajpai, Ambar Kovintavewat, Piya Wittisittikulkij, Lunchakorn Chulalongkorn University Wireless Communication Ecosystem Research Unit Department of Electrical Engineering Bangkok Thailand Atria Institute of Technology Bangalore India Advanced Signal Processing for Disruptive Innovation Research Center Nakhon Pathom Rajabhat University Faculty of Science and Technology Nakhon Pathom Thailand

ISBN: (纸本)9798350326413

In the next few years, various technologies including artificial intelligence, the Internet of Things, virtual reality, and augmented reality will coexist to realize the objectives of 6G wireless systems. In this paper, we propose a digital twin (DT) prototype of conventional wireless communication systems in a metaverse/virtual environment. We develop the modelling scenario of a cellular communications set-up in the Unity platform at first. Then, we establish the real-time communication between BS/s and user/s' in a metaverse environment after introducing some features such as cell coverage area, operating frequency, and global positioning system (GPS). With the aid of GPS, we continuously monitor the user/s' position in the metaverse environment. Moreover, we use the C# scripting tool in the metaverse environment to make all the modelling units functional and interconnected. The experiment results show that the user/s' location can be localized in the digital world, creating the DT of the real cellular communications set-up. © 2023 IEEE.

关键词： Virtual reality

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Transclaw U-Net: Claw U-Net With Transformers for Medical image Segmentation 5

Transclaw U-Net: Claw U-Net With Transformers for Medical Im...

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5th International Conference on Information Communication and signal processing, ICICSP 2022

作者： Yao, Chang Hu, Menghan Li, Qingli Zhai, Guangtao Zhang, Xiao-Ping East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing Shanghai China Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai China Ryerson University Department of Electrical Computer and Biomedical Engineering Toronto Canada

ISBN: (纸本)9781665485890

In medical image analysis, the long-range spatial features are often not accurately obtained by the traditional convolutional neural networks. Hence, we propose a TransClaw U-Net network structure. The transformer part is added after three convolution operations to fuse shallow features extracted by convolution operations for maximally encoding the long-range spatial features between patches. The 'Claw' in TransClaw U-net means that we add the bottom upsampling part to retain the deepest feature information for detail segmentation. In addition, the modified three-channel global attention mechanism to blend the outputs of three channels (the encoding part, the bottom upsampling part and the decoding part) to effectively extract image contours. The experimental results on Synapse Multi-organ Segmentation Dataset show that TransClaw U-Net performs better than other networks. The results of ablation experiments prove the effectiveness of the three improved components of the network and influence of input image size and skip-connection numbers on network performance. The source code will be publicly available once the paper is accepted. © 2022 IEEE.

关键词： Convolution

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Audio-Visual Quality Assessment for User Generated Content: Database and Method

Audio-Visual Quality Assessment for User Generated Content: ...

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IEEE International Conference on image processing

作者： Yuqin Cao Xiongkuo Min Wei Sun Xiaoping Zhang Guangtao Zhai Institute of Image Communication and Information Processing Shanghai Jiao Tong University Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University

With the explosive increase of User Generated Content (UGC), UGC video quality assessment (VQA) becomes more and more important for improving users’ Quality of Experience (QoE). However, most existing UGC VQA studies only focus on the visual distortions of videos, ignoring that the user’s QoE also depends on the accompanying audio signals. In this paper, we conduct the first study to address the problem of UGC audio and video quality assessment (AVQA). Specifically, we construct the first UGC AVQA database named the SJTU-UAV database, which includes 520 in-the-wild UGC audio and video (A/V) sequences, and conduct a user study to obtain the mean opinion scores of the A/V sequences. The content of the SJTU-UAV database is then analyzed from both the audio and video aspects to show the database characteristics. We also design a family of AVQA models, which fuse the popular VQA methods and audio features via support vector regressor (SVR). We validate the effectiveness of the proposed models on the three databases. The experimental results show that with the help of audio signals, the VQA models can evaluate the perceptual quality more accurately. The database will be released to facilitate further research.

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Enhancing Fault Diagnosis of Uncertain Grid-Connected Photovoltaic Systems using Deep GRU-based Bayesian optimization

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IFAC-PapersOnLine 2024年第4期58卷 449-454页

作者： Zahra Yahyaoui Mansour Hajji Majdi Mansouri Abdelmalek Kouadri Kais Bouzrara Hazem Nounou Research Unit Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine 1200 Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Signals and Systems Laboratory Institute of Electrical and Electronics Engineering University M Hamed Bougara of Boumerdes Boumerdes Algeria Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir Tunisia

The efficacy of photovoltaic systems is significantly impacted by electrical production losses attributed to faults. Ensuring the rapid and cost-effective restoration of system efficiency necessitates robust fault detection and diagnosis (FDD) procedures. This study introduces a novel interval-gated recurrent unit (I-GRU) based Bayesian optimization framework for FDD in grid-connected photovoltaic (GCPV) systems. The utilization of an interval-valued representation is proposed to address uncertainties inherent in the systems, the GRU is employed for fault classification, while the Bayesian algorithm optimizes its hyperparameters. Addressing uncertainties through the proposed approach enhances monitoring capabilities, mitigating computational and storage costs associated with sensor uncertainties. The effectiveness of the proposed approach for FDD in GCPV systems is demonstrated using experimental application.

关键词： Bayesian optimization fault detection fault diagnosis gated recurrent units grid-connected PV systems interval-data representation uncertainties

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