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共 7145 条记录，以下是131-140 订阅

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Advanced Control Strategy for Mitigating Imbalances in Centralized Microgrids Using Grid-Forming Converters 4

Advanced Control Strategy for Mitigating Imbalances in Centr...

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4th international conference on robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Hannan, Nasif Hossain, Md Ismail Shufian, Abu Alam, Sadman Shahriar Tanvir Hassan Shovon, S.M. Sheikh, Protik Parvez American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798331530938

Power instability in centralized microgrids remains a critical challenge due to fluctuating load demands and the dynamic nature of renewable energy sources. Traditional voltage and frequency control techniques often fail to tackle imbalances arising from uneven load distribution and dynamic generation patterns. To overcome this, the study introduces an advanced control strategy incorporating a novel centralized secondary control mechanism. This mechanism optimizes power management by factoring in intermittent levels, load-effective impedance, and voltage fluctuations, ensuring efficient voltage regulation and stability. The proposed approach aims to improve overall microgrid performance by dynamically balancing power distribution and enhancing control parameters. The effectiveness of the strategy is validated through simulation and experimental methods, demonstrating its ability to stabilize voltage and address power imbalances in centralized microgrids. The findings provide valuable insights for improving the reliability and efficiency of modern energy systems, particularly in dealing with voltage instability and variable load conditions in microgrid applications. © 2025 ieee.

关键词： Microgrids

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NoSQL Database Selection Process: An Integrated Proof of Concept and Comparison for Targeted Document Store Databases 4

NoSQL Database Selection Process: An Integrated Proof of Con...

引用

4th international conference on robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Sakib, Fahim Faysal Roy, Shuva Dev Rahman, Zahid Saha, Shoumik Salam, Abdus American International University-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798331530938

The study offers an analysis of NoSQL document store databases focusing on MongoDB, Couchbase, and CouchDB and includes an integrated Proof of Concept (POC) along with a research-based comparison. It begins with an overview of the evolving landscape of Database Management systems (DBMS) highlighting the role of NoSQL databases in overcoming the limitations of traditional relational databases. The research includes a contextual evaluation and qualitative comparison of the three databases incorporating performance metrics to gauge their suitability for various applications. MongoDB is identified as the best in query performance (1.5 ms), transaction support, and integration with cloud platforms. Couchbase shows competitive scalability and good query performance (2.6ms) while CouchDB lacks ACID transactions, optimization, and support barriers and shows query time (6 ms), This analysis highlights each database's strengths and weaknesses providing key insights for real-world deployment. © 2025 ieee.

关键词： Scalability

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Neuromorphic Computing Architectures for Enhanced signal processing in Autonomous systems 5

Neuromorphic Computing Architectures for Enhanced Signal Pro...

引用

5th international conference on Emerging systems and intelligent Computing, ESIC 2025

作者： Chendhuran, R. Arun Jayanthi, T. Shasidhar, Rampalli Yamsani, Nagendar Chandrasekhar, Sankepally Athiraja, A. Bannari Amman Institute of Technology Department of Eee Sathyangalam Erode India Dr. N.G.P Institute of Technology Department of Ece Tamilnadu Coimbatore India Military College of Electronics and Mechanical Engineering Department of Mechanical Engineering Telangana Secunderabad India Sr University School of Computer Science and Artificial Intelligence Warangal India Department of Mechanical Engineering Medchal-Malkajigiri Telangana Maisammaguda India Telangana Hyderabad India

ISBN: (纸本)9798331522100

Innovative computing techniques that strike a balance between speed, efficiency, and adaptability are required due to the growing complexity of signal processing in autonomous systems. Neuromorphic computing, which draws inspiration from the structure of the human brain, offers a workable method for enhancing signal processing in real-time analysis and decision-making devices, including robotic systems, drones, and driverless cars. The integration of neuromorphic architectures for sophisticated signal processing in robotic systems, drones, and autonomous cars is examined in this research. The application of event-driven processing and spiking neural networks (SNNs) for real-time analysis and decision-making is the main emphasis of the research. The approach involves developing a scalable neuromorphic framework that makes use of cutting-edge hardware, including neuromorphic chips, and evaluating its reaction time, energy efficiency, and processing speed in comparison to traditional von Neumann architectures. Neuromorphic systems demonstrate their potential for continuous real-time data handling by reducing latency by 30% and improving energy efficiency by up to 50%. The system's resilience in handling intricate environmental signals and adjusting to changing inputs is highlighted by important findings. According to the paper's conclusion, incorporating neuromorphic designs greatly improves autonomous systems' efficiency and real-time processing capabilities, opening the door to more responsive and energy-efficient operations. Improving hardware compatibility and broadening applications across various autonomous technologies are two areas of future research. © 2025 ieee.

关键词： Sorting

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Compact Design and Analysis of Microwave Band Pass Filter using Coupled Lines with Four Reflection Zeros for 5G Communication

Compact Design and Analysis of Microwave Band Pass Filter us...

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2024 ieee international conference on intelligent signal processing and Effective Communication Technologies, INSPECT 2024

作者： Indra Kumar, A. Yaswanth, K.N.G.B. IIITDM Department of ECE Kurnool India

ISBN: (纸本)9798350379525

This paper demonstrates the compact design and study of a microwave band-pass filter (BPF) consisting of two transmission and four reflection zeros for modern 5G communication systems. The demonstrated BPF is structured with three coupled lines. The filter's circuit and electromagnetic (EM) simulations were conducted using Ansys Electronics Desktop. The S-parameters of the filter were derived using the even-odd mode method to extract mathematical equations for the transmission and reflection zeros of the presented BPF. This compact BPF, consisting of center frequency 2.5 GHz, was developed and simulated, achieving an optimal 3-dB fractional bandwidth (FBW) of 68.76%, a fall-off rate of 87.2 dB/GHz, an insertion loss of greater than 60 dB in its stop band, return losses greater than 12dB in its passband and a selectivity factor (SF) of 0.91. The circuit and HFSS design simulated results are in acceptable match. © 2024 ieee.

关键词： 5G mobile communication systems

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Adaptive Filtering Strategies for ECG signal Enhancement: A Comparative Study 6

Adaptive Filtering Strategies for ECG Signal Enhancement: A ...

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6th international conference on Pattern Analysis and intelligent systems, PAIS 2024

作者： Menaceur, Nadjem Eddine Kouah, Sofia Derdour, Makhlouf University of Oum El Bouaghi Algeria Liaoa Laboratory Oum El Bouaghi Algeria

ISBN: (纸本)9798350350265

The Electrocardiogram (ECG) is a critical clinical record for diagnosing Arrhythmia and elucidating various cardiovascular diseases. Achieving a clear morphology and denoised signal is pivotal for physicians. In this context, our paper provides a comparative study of filtering techniques tailored for ECG signal enhancement. We investigate three distinct kinds of filters: Linear, non-linear, and adaptive filters. A comparative analysis is conducted, considering key performance metrics such as signal-to-Noise Ratio (SNR) and MSE. The study underscores that the Adaptive Median filter, with a parameter of 5, overtakes others, highlighting its adaptability in handling dynamic ECG signal characteristics and contributing to exceptional noise reduction and signal fidelity. The outcomes furnish valuable insights into the strengths and limitations of each filtering approach, assisting researchers and practitioners in selecting the most suitable technique for their specific ECG signal processing needs. © 2024 ieee.

关键词： Electrocardiograms

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Study on test architecture about frequency characteristics of control loop 8

Study on test architecture about frequency characteristics o...

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8th international conference on intelligent Computing and signal processing, ICSP 2023

作者： Guo, Junming Li, ChunYan Wang, Chao Zhengzhou Electromechanical Engineering Research Zhengzhou China

ISBN: (纸本)9798350302455

In order to test frequency characteristics on different types of control loop effectively, two kinds of architecture about four types of control loops are analysed respectively, and key testing components and signal connection are proposed. The experimental results and actual application effect accord with the theoretical analysis perfectly. © 2023 ieee.

关键词： Closed loop control systems

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Photovoltaic systems: Analytic Comparison of Fuzzy Logic and ML Methods for Applying Maximum Power Tracking systems 4

Photovoltaic Systems: Analytic Comparison of Fuzzy Logic and...

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4th international conference on robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Ahmed, Minhaz Uddin Qays, Ohirul Lachowicz, Stefan Thundiyil, Nishanth Titus Hossain, Md. Liton Amin, Uzma Shahjalal, Md. Hasan, Rasedul Yasmin, Farhana School of Engineering Edith Cowan University JoondalupWA6027 Australia Federation University Centre for New Energy Transition Research Australia School of Elec Eng Comp and Math Sci Curtin University BentleyWA6102 Australia University of Liberal Arts Dept of Eee Bangladesh Aurecon Australasia Power Systems Engineer North SydneyNSW2060 Australia

ISBN: (纸本)9798331530938

Integration of artificial intelligence (AI) in solar power systems for maximum power point tracking (MPPT) is increasingly popular due to the limitations of traditional MPPT methods in locating the global maximum power point (GMPP) under partial shading conditions. Unlike conventional techniques, AI-based algorithms excel at identifying the GMPP even when multiple local maximum power points (MPPs) exist. Compared to traditional methods, AI-based MPPT techniques like reinforcement learning and fuzzy logic typically offer higher efficiency, reduced steady-state oscillation, and faster convergence but require significant resources and investment. This paper compares two AI-based MPPT methods-Fuzzy Logic and Reinforcement Learning using simulation. Each AI approached its strengths and weaknesses, complicating on optimal method selection. It provided a detailed efficiency comparison of these AI methods by implementing them in a solar power grid system under various environmental conditions. © 2025 ieee.

关键词： Reinforcement learning

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Techno-Economic Benefits of Grid-Connected Photovoltaic systems 3

Techno-Economic Benefits of Grid-Connected Photovoltaic Syst...

引用

3rd ieee international conference on intelligent Techniques in Control, Optimization and signal processing, INCOS 2024

作者： Alarfaj, Mohammed Sumsudeen, Rajamohamed Aboulnaga, Aly Hassan, Mohamed College of Engineering King Faisal University Department of Electrical Engineeting Al-Ahsa31982 Saudi Arabia College of Engineering University of Bahrain Department of Electrical Engineering Zallaq1054 Bahrain

ISBN: (纸本)9798350361186

Energy resources that offer substantial environmental benefits while also producing minimal economic impact are highly valued. Photovoltaic (PV) energy is an infinite, non-polluting energy resource that can be economically utilized to meet energy requirements. The study examines the technical and economic viability of a grid-connected PV system. To explore the influence of photovoltaic benefits on grid voltage support, a seven-bus power system model is created and analyzed using simulation software. Furthermore, the benefits of grid-connected solar PV systems in transmission and distribution, as well as line extension in rural areas of developing countries and consumers, are highlighted using literature reviews. The study concludes with an assessment of the technical and economic feasibility of the examined PV system profitability depending on the system site location, household load size, consumer energy cost, and existing PV subsidies. © 2024 ieee.

关键词： Distributed power generation

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Multi-target tracking technology of phased array radar based on data processing resource scheduling algorithm 6

Multi-target tracking technology of phased array radar based...

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6th international conference on intelligent Control, Measurement and signal processing, ICMSP 2024

作者： Liu, Duo The 20th Research Institute of China Electronics Technology Group Corporation Xi'an China

ISBN: (纸本)9798331516550

In the process of radar multi-target radar tracking, a variety of multiple targets will lead to a large amount of data to be processed, which increases the complexity of data processing and the computational load. At the same time, the motion characteristics and importance of different targets are different, and it is necessary to allocate data processing resources reasonably to achieve priority tracking of key targets. Aiming at the above problems, this paper proposes a technology that uses advanced data processing algorithms and resource scheduling strategies to achieve efficient tracking of multiple targets by phased array radar systems. The technology determines the priority of different targets according to the importance and mobility of the target, and then changes in real time according to the number of targets and the state of motion. The situation dynamically adjusts the allocation of data processing resources, so that the radar system can process the reflected signals of a large number of targets in real time. Experiments show that the algorithm can accurately estimate the dynamic parameters such as position, velocity and acceleration of the target, and improve the monitoring ability and target recognition accuracy of the radar system. © 2024 ieee.

关键词： Radar target recognition

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intelligent Near-Infrared Spectroscopy for Blood Glucose Level Classification 32

Intelligent Near-Infrared Spectroscopy for Blood Glucose Lev...

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32nd international conference on Electrical Engineering (ICEE)

作者： Sharifi, Shahrooz Maddah-T, Amirhoseein Akbarzadeh-T, Mohammad-R. Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Razavi Khorasan Iran Ferdowsi Univ Mashhad Ctr Excellence Soft Comp & Intelligent Informat P Mashhad Razavi Khorasan Iran

ISBN: (纸本)9798350376357;9798350376340

Diabetes Mellitus is a disease characterized by inadequate control of blood glucose levels, and it ranks among the leading causes of human mortality, the measurement of which, requires fingertip pricking. Nowadays, non-invasive healthcare monitoring systems based on wearable sensors and machine learning models hold the future of smart health. However, the nature of these methods is such that they get affected by internal physiological and external parameters, which is one of the obstacles to this path. This study aims to introduce a non-invasive blood glucose level classification method based on machine learning analysis. The device's sensor consists of an optical finger sensor that transmits near-infrared light, filtering, and amplification to reduce the noise of the extracted photoplethysmography signal. Moreover, we have adopted the four-stage framework of biomedical signal processing to analyze the acquired PPG signal. Before using the Savitzky-Golay derivation to pre-filter the signal and prepare it for feature extraction, it was normalized using Standard Normal Variate (SNV). In addition, four different machine learning models, including Support Vector Machine (SVM), Weighted K-Nearest Neighbors (KNN), Wide Neural Network, and Decision Tree were used for blood glucose level classification. For this study, a dataset was created consisting of 106 data, gathered from 27 subjects. Findings revealed that the Weighted KNN exhibited the best performance among other classification models, having 90.5% accuracy.

关键词： Blood Glucose Photoplethysmography signal NIR Spectroscopy Biomedical signal processing Feature Extraction Machine Learning Classification Confusion Matrix

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