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共 7159 条记录，以下是571-580 订阅

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Neural Network Method of Directing Finder signals processing in Perimeter Protection systems 13

Neural Network Method of Directing Finder Signals Processing...

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13th international conference on Advanced Computer Information Technologies, ACIT 2023

作者： Polikarovskykh, Oleksiy Boiko, Juliy Tkachuk, Vitalii Yehoshyna, Hanna Daus, Yurii Odessa National Maritime University Department of Technical Cybernetics and Information Technologies Odessa Ukraine Khmelnytskyi National University Department of Telecommunications Media and Intelligent Technologies Khmelnytskyi Ukraine Khmelnytskyi National University Department of Mechanical Engineering Technology Khmelnytskyi Ukraine National University 'Odessa Polytechnic' Department of Information Technologies Odessa Ukraine

A method for neural network processing of direction finder signals based on a correlation reflectometer is presented. It is proposed to use an artificial neural network to determine the location of signal sources based on the analysis of data from a specially shaped antenna. The solver is based on a multilayer perceptron. The main theoretical foundations and simulation results are presented. © 2023 ieee.

关键词： Neural networks

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Efficient Real Time Stator Inter-Turn Short Circuit Fault Detection of Inverter-Fed Induction Motors: A Hybrid Approach Utilizing Wavelet Transform and Digital signal processing

Efficient Real Time Stator Inter-Turn Short Circuit Fault De...

引用

2023 Annual international conference on Emerging Research Areas: international conference on intelligent systems, AICERA/ICIS 2023

作者： Singh, Shantanu Kumar Jagadanand, G. National Institute of Technology Calicut Electrical Engineering Department Bihar Gopalganj India

ISBN: (纸本)9798350303452

In induction motors faults in the stator winding can significantly impact their performance and reliability. This research investigates the analysis of inter-turn short circuit faults by varying the switching frequency of the sine pulse-width modulation (PWM) inverter under different loading conditions. A faulty condition of the motor is modeled in MATLAB/Simulink blocks, and stator currents are simulated for different fault percentages. First, the wavelet transform is applied to decompose the stator current signals into different frequency sub bands. Next, statistical parameters are computed from the wavelet coefficients to quantify the characteristics of the stator current signals. These statistical parameters can include mean, standard deviation, variance, skewness, kurtosis, or other measures that capture the statistical properties of the wavelet coefficients. This Statical data is used to train the SVM model and find a optimal decision boundary to classify Healthy or Faulty Condition. © 2023 ieee.

关键词： Wavelet transforms

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Bi-directional Deep Transfer Learning for RIS-enhanced Multi-cell OFDMA systems 14

Bi-directional Deep Transfer Learning for RIS-enhanced Multi...

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14th ieee international conference on Wireless Communications and signal processing (WCSP)

作者： Sun, Gaoxiang Wang, Xiaoming Jiang, Rui Liu, Ting Xu, Youyun Nanjing Univ Posts & Telecommun Sch Commun & Informat Engn Nanjing 210003 Peoples R China Nanjing Univ Informat Sci & Technol Sch Artificial Intelligence Sch Future Technol Nanjing 210044 Peoples R China Southeast Univ Natl Mobile Communicat Res Lab Nanjing 210096 Peoples R China

ISBN: (纸本)9781665450850

In this paper, we investigate the dynamic optimization on resource allocation and reconfigurable intelligent surface (RIS) control in RIS-enhanced multi-cell orthogonal frequency division multiple access (OFDMA) systems. Specifically, we jointly optimize the subcarrier and power allocation strategies, and control the amplitude and phase shift of the reflection elements of RIS. We propose a multi-agent deep reinforcement learning (MADRL) method to solve this optimization problem. We design a multi-agent double deep q-network (MADDQN) algorithm to generate the subcarrier allocation policy, and adopt the multi-agent deep deterministic policy gradient (MADDPG) algorithm for power allocation and RIS control. Furthermore, a bi-directional transfer learning (BDTL) framework is proposed to enhance the adaptability of neural networks in different environments by leveraging the common configurations of these environments. Simulation results illustrate that the proposed algorithms have higher sum-rate and faster training speed than the baseline algorithms. Moreover, the BDTL framework further accelerates the convergence speed of neural networks under different environments.

关键词： OFDMA resource allocation reconfigurable intelligent surface MADRL bi-directional transfer learning

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Channel Estimation for IRS-Aided Single-User MIMO systems Based on Core Tensor 23

Channel Estimation for IRS-Aided Single-User MIMO Systems Ba...

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2023 Asia conference on Artificial Intelligence, Machine Learning and robotics, AIMLR 2023

作者： Xu, Zhihao Li, Cong Li, Yan Anhui University of Technology Maanshan City Maanshan Anhui China

ISBN: (纸本)9798400708312

intelligent reflective surface (IRS), comprised of numerous low-cost passive components, is a vital technology for the future sixth-generation wireless system. However, the inability of the IRS to handle signals independently poses challenges in estimating channels in fully passive IRS-Aided systems. This paper investigates the channel estimation for an IRS-Aided single-user multiple-input multiple-output (SU-MIMO) system and specifically focuses on the scenario where the large-dimensional received signals processed at the base station prove inconvenient for memory-based processing. To tackle this issue, this paper suggests a non-blind receiver that relies on a core tensor of the signals received, while also considering the quasi-static channel characteristic between the IRS and BS. Simulation results demonstrate the proposed receiver has superior performance in high-dimensional data processing, i.e., a lower normalized mean square error (NMSE) and computational complexity over the uncompressed received signal tensor-Assisted receiver. © 2023 ACM.

关键词： Channel estimation

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A PAE-Controlled Wideband Power Amplifier for Sub-6GHz 5G Applications in 28nm FDSOI Technology 29

A PAE-Controlled Wideband Power Amplifier for Sub-6GHz 5G Ap...

引用

29th ieee international conference on Electronics, Circuits and systems (ieee ICECS)

作者： Queheille, Remi Fellmann, Maxandre Deval, Yann Kerherve, Eric Rivet, Francois Deltimple, Nathalie Univ Bordeaux IMS Bordeaux INP CNRSUMR 5218 F-33400 Talence France

ISBN: (数字)9781665488235

ISBN: (纸本)9781665488235

A wideband Power Amplifier (PA) with controlled efficiency based on the second harmonic matching and designed in 28nm FDSOI technology is proposed in this paper. The output network uses the harmonic processing techniques, especially the class-J one to control the Power Added Efficiency (PAE) over the Bandwidth (BW). The gain is between 16 and 19dB, P-sat is between 18.5 and 20.9dBm and the PAE is 45% in the 3dB small signal BW from 2.4 to 5.1GHz. In this paper, we investigate the efficiency control principle.

关键词： CMOS FDSOI power amplifier second harmonic processing wideband

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Automatic Identification Of Birds Using Speech signal processing And Neural Networks 4

Automatic Identification Of Birds Using Speech Signal Proces...

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4th international conference on Emerging systems and intelligent Computing, ESIC 2024

作者： Reshma, Pothuri Meghana, Rongala Sree, Sarepalli Divya Sravanam, Roshan Rishi Surya, Rajanala Sr Gudlavalleru Engineering College Dept. of Cse Andhra Pradesh Gudlavalleru521356 India

ISBN: (纸本)9798350349856

The ecosystem might suffer irreparable damage if we don't keep an eye on the impacts of our actions. Monitoring biodiversity, population dynamics, and animal breeding behaviour is one way to keep an eye on these consequences. Because they are the most vulnerable to environmental changes like deforestation and forest fires, birds are among the best creatures to study. An estimated 1,370 bird species, or around 13% of all bird species, are under threat of going extinct. Despite their ubiquity, many species of birds elude human identification. Up until recently, professionals had to manually monitor the birds, which was both inefficient and *** help ecologists with this problem, we suggest using deep learning to determine the species of a bird from an audio clip. In order to do this, we want to employ the most recent Artificial Neural Network (ANN) model for automatic identification of bird species using audio inputs. Our goal in this effort was to develop a more accurate method of classifying bird species. A 100% training accuracy and a 97% validation accuracy are displayed in this data. Since ANN is able to identify the bird species with high accuracy, we can say that it is superior to the current implementation approach. © 2024 ieee.

关键词： Deforestation

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Graph Neural Networks for Natural Language processing in Human-Robot Interaction 26

Graph Neural Networks for Natural Language Processing in Hum...

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26th ieee signal processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Swietlicka, Aleksandra Haczyk, Dagmara Haczyk, Marcel Poznan University of Technology Institute of Automatic Control and Robotics Poznań Poland Poznan University of Technology Poznań Poland

ISBN: (纸本)9798350304985

Human-robot interaction (HRI) has become a promising field that focuses on developing intelligent systems that are capable of understanding human language. Natural Language processing (NLP) plays a huge role in enabling robots to interpret and generate natural language, making it easier to effectively communicate. However, traditional NLP approaches sometimes struggle to capture the right structural dependencies and contextual *** overcome these limitations, Graph Neural Networks (GNNs) have emerged as a powerful model for NLP tasks in the context of human-robot interaction. GNNs extend traditional neural network architectures to effectively model and reason about structured data, such as graphs. In the context of NLP, these graphs can represent semantic relationships between words or *** this study, we model human-robot conversations as graphs. The aim of the research is to conduct a test using GNNs to predict personality traits based on conversations between human and robot. Presented results, despite a very small training set, show that GNNs can be effective in capturing the dynamics and context of conversations. GNNs lead then to improved performance in tasks such as predicting personality and estimating engagement levels. These findings suggest that GNNs have the potential to enhance the quality of HRI and improve the overall user experience. © 2023 Division of signal processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： Human robot interaction

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Wireless Ranging and Smelting Driving Location based on Moore Voting Method 2

Wireless Ranging and Smelting Driving Location based on Moor...

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2nd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2023

作者： Liu, Jinhao Lv, Zhiyong Xu, Jiahui Hu, Yiting Wuhan University of Technology Intelligent Transportation Systems Research Center Wuhan China Wuhan University of Technology Guangdong Inland Port and Shipping Research Co. Ltd. Wuhan China Wuhan University of Technology School of Automation Wuhan China

ISBN: (纸本)9798350345575

In order to explore the reasons for the insufficient positioning accuracy of the crane, to ensure the personal safety of the staff, and to improve the reliability of production operations and work efficiency. Focus on building a set of practical, easy-To-operate, concise and efficient real-Time positioning system based on TOF wireless ranging technology and laser radar technology measurement principle. Analyze the principle of the TOF wireless ranging data error, and use the extended Kalman filter method to perform error analysis and noise reduction processing on the distance data collected by the TOF wireless ranging sensor on site. After the extended Kalman filtering data, the average error is less than 0.1 cm, to improve the reliability and robustness of real-Time positioning systems for on-site operations in steel mills. The Moore voting method is used to locate the smelting crane laterally, combined with the distance data of the laser radar sensor to determine the longitudinal positioning of the wireless smelting crane, and realize the all-round real-Time positioning function of the smelting crane during operation. © 2023 ieee.

关键词： Optical radar

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Magnetic Fluxgate Based Insulation Testing Solution for DC systems 7

Magnetic Fluxgate Based Insulation Testing Solution for DC S...

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7th international conference on intelligent Computing and signal processing, ICSP 2022

作者： Wang, Xiaoming Zhou, Ke Lin, Xiangyu Song, Yi Electric Power Research Institute Guangxi Power Grid Co. Ltd. China Southern Power Grid Nanming China

ISBN: (纸本)9781665478571

Traditional insulation detection schemes are based on Hall sensors, which have large zero drift and temperature drift, are difficult to maintain accuracy in outdoor new energy scenarios. This paper designs a DC system insulation detection scheme based on the fluxgate. The fluxgate sensing module is developed using a single magnetic ring and single-coil structure, which suppresses the zero drift;an offset coil input is introduced to build a closed-loop detection system to solve the temperature drift. The solution has been proven to achieve low zero drift and high accuracy over the full temperature range. © 2022 ieee.

关键词： Hall effect transducers

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A Novel Semantic-Web Based Technology for Control Logic Rapid Reconfiguration of CPPS 7

A Novel Semantic-Web Based Technology for Control Logic Rapi...

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7th international conference on intelligent Computing and signal processing, ICSP 2022

作者： Wang, Peng Wang, Zhongfeng Wang, Chu Hu, Kunyuan Li, Ligang Song, Chunhe Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665478571

Aiming at solving the problem that the traditional production control system cannot support rapid logical reconfiguration of CPPS, a semantic-web based technology consisting of an overall research framework and three key methods are proposed. Within this overall research framework, product process can be first matched against production resource capabilities, then transformed into the production process of production system, and finally into the control logic of production control system. All the transformations can be done automatically by the help of the proposed semantic-web based methods, namely unified ontology model and related reasoning methods, so that when product process changes, control logic of production can be adjusted efficiently, which enables rapid logical reconfiguration of CPPS. In this paper, the overall framework is first introduced with emphasis on background and technical characteristics of CPPS, analysis of research gaps and overall methods. Then, the three key methods are introduced in detail, namely the unified ontological modelling method of product-process-resources, and the rule-based reasoning methods to automatically transform the production process and control logic, are described in detail. Furthermore, concerning the shortcoming of existing Product-Process-Resource ontological modeling, the description of production system's control behavior is extended within the resource domain, so that key information related to PLC programming such as action sequence and control variable can be integrated and leveraged during the transformation of control logic. Finally, a reconfigurable CPPS prototype is developed based on the proposed framework, and the advantages of the methods are tested and verified. © 2022 ieee.

关键词： Production control

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