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Human Body Micro-Doppler signal Detection Technology based on CW Doppler Radar 4

Human Body Micro-Doppler Signal Detection Technology based o...

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4th ieee international conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Xu, Xiaoqian Zeng, Shijie Liu, Jingping Nanjing University of Science and Technology School of Electronic and Optical Engineering Nanjing China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

As a method of non-contact life sign detection, life detection radar is widely used in post-disaster rescue and patient monitoring. How to detect the human heartbeat and respiration signals from the complex environment and further improve the signal-to-noise ratio of the signals is a difficult problem. In this paper, under the CW Doppler radar system, a life detection radar signal processing algorithm based on LMS adaptive filtering is proposed. On the basis of the traditional IIR filtering processing, the LMS adaptive filtering algorithm is further used for processing. The MATLAB simulation results show that the algorithm can extract and separate the heartbeat signal and respiration signal of the human target from the echo signal. The software and hardware are designed on the Micro-Doppler signal processing platform with FPGA as the core, and the human cardiopulmonary signal detection experiment is curried out by using the CW Doppler radar. The simulation and experimental results demonstrate the effectiveness of the signal processing algorithm and the correctness of the related design. © 2022 ieee.

关键词： Field programmable gate arrays (FPGA)

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Application of Deep Learning in signal Modulation Recognition System for Wireless Communication

Application of Deep Learning in Signal Modulation Recognitio...

引用

2023 international conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Zhou, Chuansong Gao, Xiaoxia Qi, Jinsheng Xu, Hongliang Changchun Automobile Industry Institute College of Electrical Engineering Changchun China

ISBN: (纸本)9798350313413

The development of Industrial Internet has promoted broad connections between people, machines, objects and systems, among others,and build a new manufacturing and service system covering the entire industrial chain and the entire value chain, providing a way to realize the digitization, networking and intelligent development of industry and even *** system in the high reliability and ultra-high capacity requirements at the same time, but also more and more complex, modulation methods are diverse, how to quickly and efficiently identify the signal type in order to make a deeper degree of processing becomes very meaningful, this paper introduces the relevant content of deep learning, mainly using convolutional neural network algorithm for signal modulation recognition, through Matlab simulation, the signal recognition accuracy is close to 87% and the stability is good under high SNR. © 2023 ieee.

关键词： deep learning machine learning neural network wireless communication

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A PARAMETRIC APPROACH OF COMPUTING TAGUCHI signal-TO-NOISE RATIO FROM INCOMPLETE LIFE DATA 14

A PARAMETRIC APPROACH OF COMPUTING TAGUCHI SIGNAL-TO-NOISE R...

引用

14th international conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Jiang, Renyan Xue, Wei Cao, Yu China International Science & Technology Cooperation Base for Laser Processing Robotics Wenzhou University Wenzhou China Zhejiang Provincial Innovation Center of Laser Intelligent Equipment Technology Wenzhou China

ISBN: (纸本)9781837242672

The Taguchi method for experimental design is widely utilized to improve product reliability through the systematic arrangement of multiple runs or treatments, each representing a unique combination of factor levels. In such experiments, lifetime data of sample units are gathered via life tests, which are typically monitored periodically and terminated at a pre-determined endpoint. The resultant data, characterized by small sample sizes, high censorship, and heterogeneity, preclude direct computation of the Taguchi signal-to-noise ratio (SNR), a crucial measure of robustness used to evaluate the performance of a run. This paper addresses this issue by introducing a parametric approach that begins by constructing a life distribution model for each run through a three-step parameter estimation procedure. It then calculates the SNR from the fitted distribution using SNR expressions derived from typical life distributions discussed herein. The effectiveness and superiority of the proposed method are demonstrated through two real-world examples, underscoring its applicability and potential benefits in enhancing the reliability analysis of complex products. © The Institution of Engineering & Technology 2024.

关键词： Taguchi methods

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Analysis of Knocking Potential Based on Vibration on a Gasoline Engine for Pertalite and Pertamax Turbo Using signal processing Methods 1

引用

international conference on Innovative Technologies in intelligent systems and Industrial Applications, CITISIA 2022

作者： Qadri, Munzir Astuti, Winda Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Knocking is one of the problems in internal combustion engines with many influencing factors, one of which is the use of fuel octane values that are not in accordance with the recommended use or engine specifications. Knocking can lead to poor performance of an engine and shorten its lifetime. To prevent this from happening, a study was conducted on how the octane rating can affect the knocking of an engine by comparing two types of fuel that have different octane rating levels. The most appropriate signal processing method was also determined to carry out this research. The engine speed was predetermined in each experiment. The achieved results prove that the engine has the potential of knocking to occur when using Pertalite-type fuel, caused by misfires. signal processing is carried out using the Fast Fourier Transform (FFT) and Low Pass Filter (LPF) methods to obtain clear data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Gasoline

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Design of MIMO CSI Feedback with Deep Learning 2

Design of MIMO CSI Feedback with Deep Learning

引用

2nd international conference on Artificial Intelligence and intelligent Information processing, AIIIP 2023

作者： Xie, Bin Dai, Bangqiang College of Information Engineering Jiangxi University of Science and Technology Ganzhou China

ISBN: (纸本)9798350371451

In MIMO systems, effective channel state information (CSI) feedback is crucial for optimizing signal transmission and improving system performance. However, with the increasing complexity of CSI, traditional CSI feedback methods are limited in terms of computational error and complexity, making the feedback performance has become a bottleneck. In this paper, we propose a new CSI feedback network based on deep learning approach, which aims to utilize the powerful properties of neural networks to achieve better feedback performance in a more accurate and efficient manner. The network is divided into two parts: encoder and decoder. In the encoding part, it utilizes the coordinated attention mechanism to extract richer CSI features;in the decoding part, it achieves better CSI recovery through different numbers of convolutional channels with multiple receptive fields. Experimental results show that the feedback method proposed in this paper achieves better CSI feedback performance in different scenarios and at different compression rates. © 2023 ieee.

关键词： MIMO systems

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Proceedings - 2023 11th ieee international conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2023

Proceedings - 2023 11th IEEE International Conference on Mob...

引用

11th ieee international conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2023

ISBN: (纸本)9798350322798

The proceedings contain 8 papers. The topics discussed include: a fault detection mechanism for database management systems on mobile edge computing;distress signal recognition using pose estimation and neural networks;intelligent emergency notification mobile service via multi-task BERT models;surveillance drone cloud and intelligence service;aqua colony for fully automated aquaculture;TransScale: combined-approach elasticity for stream processing in fog environments;efficient cloud-based video summarization using deep learning and cloud computing for reduced storage costs and improved accessibility;and enhancing virtual sensors to deal with missing values and low sampling rates.

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Machine Learning Algorithm Comparison for Traffic signal: A Design Approach 8

Machine Learning Algorithm Comparison for Traffic Signal: A ...

引用

8th international conference on Communication and Electronics systems, ICCES 2023

作者： Deshmukh, Saloni Parwekar, Aishwarya Danej, Bhagyashri Chavhan, N.A. Agrawal, Rahul Dhule, Chetan G H Raisoni College of Engineering Department of Data Science IOT Cyber Security Nagpur India

ISBN: (纸本)9798350396638

The number of vehicles is increasing significantly every day, especially in major cities. To control traffic flow on extensive road networks and facilitate crossing traffic flow on extensive road networks and facilitate crossing crossings, intersection n traffic signal coordination is required. It is therefore a new technology in the present world for intelligent traffic control and administration systems due to the number of vehicles with so many communication restrictions in arrays. The traffic signal strives to boost the effectiveness of transportation networks, increase safety, and reduce congestion. Technological advances enable better monitoring and management of traffic flow, and traffic signal design and operation are continually developing. The employment of some algorithms for traffic light control has improved the intelligence of traffic light controllers. This research study has developed data instruction strategies using data mining and image processing techniques. By comparing the analysis of several machine learning algorithms for predicting traffic flow and patterns, such as KNN, SVM, DNN, and Random Forest, the accuracy can be increased by lowering the overfitting. © 2023 ieee.

关键词： Support vector machines

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Active Disturbance Rejection Control of Gait For Coupled System of Biped Robot 7

Active Disturbance Rejection Control of Gait For Coupled Sys...

引用

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

作者： Zhao, Yongyong Cao, Guohua Yuan, Yi Wang, Jinghua Changchun University of Science and Technology College of Mechanical and Electric Engineering Changchun China Changchun University of Science and Technology Chongqing Research Institute Chongqing China

ISBN: (纸本)9781665478571

Footed robots have a wide range of application scenarios, in bipedal robots have strongly coupled, nonlinear, and complex dynamical systems. In this paper, we use the proper function of the joint angle variation of the lower limb motion of a bipedal robot as the dynamic gait law input of the system, which can better simulate the movement of the robot's more inadequate limb system. For the representation of the dynamical system obtained based on the Lagrangian method, according to the coupled system decoupling and self-anti-disturbance control theory, this paper derives the decoupling process. The design of the self-anti-disturbance controller to realise the step-stable tracking of the joint angle of the biped robot is similar to the human gait in the presence of sinusoidal and step perturbations. The simulation results verify the validity of the theoretical analysis and provide experimental simulation support and a theoretical basis for the design of decoupling and self-anti-disturbance control of robot lower limb motion. © 2022 ieee.

关键词： Dynamical systems

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Simulation Method for Generating Phase Noise Based on Frequency Range Merging 7

Simulation Method for Generating Phase Noise Based on Freque...

引用

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

作者： Sun, Tianwei Zhong, Xingwang Zong, Nianke Academy of Space Information Systems Xi'an China

ISBN: (纸本)9781665478571

As an important indicator to measure the stability of frequency standard sources such as crystal oscillators, phase noise is an important factor affecting the accuracy of electronic systems. In this paper, the common simulation methods of phase noise are summarized, and the method of frequency range merging is proposed. This method generates the power-law spectral noise of the divided frequency range through the FIR filter, and then merges it to generate the phase noise of the whole frequency range. Through the simulation verification in time domain and frequency domain, this method greatly reduces the time of generating simulation data, and improves the fitting degree of power spectral density of phase noise between the actual generated value and the theoretical value. In addition, this method reduces the difference between the actual standard deviation of phase noise and theoretical root mean square jitter to the magnitude of 10-4. In conclusion, this paper proposes an accurate and efficient simulation method of phase noise, which provides a basis for analyzing its effects. © 2022 ieee.

关键词： Merging

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Interpretable analysis of feature importance and implicit correlation based on sEMG grayscale images 6

Interpretable analysis of feature importance and implicit co...

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ieee 6th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Ao, Xiaohu Wang, Feng Zhao, Juan She, Jinhua China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Peoples R China Minist Educ Engn Res Ctr Intelligent Technol Geoexplorat Wuhan 430074 Peoples R China Tokyo Univ Technol Sch Engn Hachioji Tokyo 1920982 Japan

ISBN: (纸本)9798350311259

For patients requiring upper limb rehabilitation, the hand rehabilitation robot assists the patient in completing movements within a certain training trajectory to achieve therapeutic results. There have been studies based on deep learning to convert surface electromyography (sEMG) signals into sEMG images for motion intention analysis. Although good recognition accuracy has been achieved, the working principle of neural networks and the processing of image features by the networks are not well explained. The interpretability of deep neural networks determines human confidence in neural network decisions. In this paper, we design a method based on feature importance and implicit correlation for hand motion intention recognition, experimentally explored that convolutional neural networks have implicit definitions for sEMG grayscale images of the same hand gesture action, and verified the effectiveness of the designed method.

关键词： sEMG signal grayscale images implicit correlation interpretability

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