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Design of H-Bridge Circuit for CMOS Stimulator and its Application Analysis

Design of H-Bridge Circuit for CMOS Stimulator and its Appli...

引用

2023 ieee International conference on Image Processing and Computer applications, ICIPCA 2023

作者： Liu, Luchang School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798350314670

The relationship between nerve signals and electrical signals promotes the develop of neural stimulators. The Complementary Metal Oxide Semiconductor (CMOS) technology brings benefits to the development of implantable nerve stimulators. This paper reviews the theoretical basis of neural stimulator as well as its common structure. In part 3, an experiment based on software simulation is conducted to study the behavior of 'H' bridge. Some optimization of digital to analog converter is discussed in part 4. Experiment shows that the 'H' bridge has stale control to produce biphasic current. Studies show that current mirrors widely used in the design of neural stimulator which is included in DAC and also used in the output driver to increase output resistance. Blocking capacitors and optimized DAC are equipped in the stimulators to address the safety issues. CMOS technology, with its excellent characteristics such as low power consumption, provides the possibility of optimal design scheme for neurostimulators and neurostimulators have great potential for development. © 2023 ieee.

关键词： CMOS integrated circuits

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Convolutional Neural Network Based Feature Fusion for Fault Diagnosis of Chemical Dynamic Equipment 7

Convolutional Neural Network Based Feature Fusion for Fault ...

引用

7th ieee Information technology, Networking, Electronic and Automation control conference, ITNEC 2024

作者： Li, Hongyu Wang, SanMing College of Safety Science and Engineering Nanjing Tech University Nanjing China Graduate Workstation Nanjing Anyuan Technology Company Limited Nanjing China

ISBN: (纸本)9798350370782

Chemical power equipment operates under harsh conditions such as high temperatures, high pressures, or corrosive environments, making them susceptible to wear, fatigue, and corrosion. These issues can lead to performance deterioration or even catastrophic failures, posing significant risks to the safety of individuals, their property, and overall social stability. Addressing this critical concern, the study delves into the use of deep learning technologies for the safety diagnosis of chemical and dynamic equipment. A convolutional neural network-based diagnostic model is proposed, capable of extracting one-dimensional signal attributes and two-dimensional features from wavelet time-frequency diagrams. The model innovatively fuses these two feature types, markedly enhancing the accuracy of fault diagnosis in chemical dynamic equipment. Such an improvement in safety diagnostics is critical for preventing accidents and ensuring operational integrity. Furthermore, the intelligent design of the pooling and global average pooling layers substantially reduces the model's parameter count, mitigating the risk of overfitting. This strategic reduction optimizes the model's ability to generalize, solidifying its utility and reliability in real-world applications within the chemical industry. © 2024 ieee.

关键词： High temperature corrosion

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Research on 'Qilu' Cultural Inheritance Algorithm Based on Deep Neural Network 7

Research on 'Qilu' Cultural Inheritance Algorithm Based on D...

引用

7th ieee Information technology, Networking, Electronic and Automation control conference, ITNEC 2024

作者： Zheng, Jian Sun, Chao Liu, Ranran Shandong University of Engineering and Vocational Technology No.6196 Jingshidong Road Jinan250200 China

ISBN: (纸本)9798350370782

The important content of cultural inheritance is cultural identity. Deep Neural Network (DNN) performance and accuracy have been extensively tested and validated in various real-world applications. For instance, it has been successfully applied in sentiment analysis, which involves analyzing and understanding emotions, opinions, and attitudes expressed in text data. DNN has demonstrated its capability to effectively classify and analyze sentiment, allowing for a deeper understanding of people's reactions and opinions. By means of DNN, this paper studies the influencing factors of cultural identity, which is innovative. The model first introduces the TCN layer as the input layer and treats the input sequence as a whole in the network layer, which can obtain a more stable gradient, effectively solve the problem of gradient disappearance and gradient explosion, and avoid the long-term dependence loss of the sequence. By comparing the experimental data with the predicted data, it is found that the proposed algorithm is more accurate. © 2024 ieee.

关键词： Artificial intelligence Cultural inheritance Deep neural networks Time series decomposition

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Robotics in Animal Behavior Studies: Technological Innovations and Business applications

Robotics in Animal Behavior Studies: Technological Innovatio...

引用

2024 ieee International conference on Computing, applications and Systems, COMPAS 2024

作者： Tiwari, Anamika Saha, Sanchita Johora, Fatema Tuz Imran, Md Ahsan Ullah Al Mahmud, Md Abdullah Aziz, Mustakim Bin Westcliff University Department of Business Administration 17877 Von Karman Ave 4th Floor IrvineCA92614 United States International American University Department of Business Administration 3440 Wilshire Blvd STE 1000 Los AngelesCA90010 United States

ISBN: (纸本)9798331529765

Robotics and the study of animal behavior are complementary fields that cannot be separated. Animals have acquired inherent benefits in movement, thinking, processing information, and managing tasks as a result of extensive evolutionary processes. Biomimetic robots, designed with biological traits, significantly enhance their motor skills, cognitive functions, and control mechanisms, outperforming traditional robots. The progress in biomimetic technology, coupled with the unique interactive features of these robots, advances the study of animal behaviors. This research aims to offer a detailed review of the use of artificial intelligence and robotics, highlighting the intersection between robotics technology and animal behavior studies. The importance of mimicking animal behaviors in creating biomimetic robots is emphasized, with a focus on three key areas: movement behaviors, cognitive behaviors, and neural processes. The study explains the advantages of using biomimetic robots to understand animal behaviors, considering the animals' behavioral responses, group behavior patterns, and cognitive neurological activities. Additionally, the paper examines the potential applications of robotics in evaluating animal behavior and discusses the future developments in biomimetic robots and animal behavior research. © 2024 ieee.

关键词： Invertebrates

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Nonparametric Sliding Mode Predictive Current control for Linear Induction Motor

Nonparametric Sliding Mode Predictive Current Control for Li...

引用

2024 ieee China International Youth conference on Electrical Engineering, CIYCEE 2024

作者： Guo, Yingcong Xu, Wei Xiao, Han Ge, Jian School of Electrical Engineering Southwest Jiaotong University Chengdu610031 China Institute of Electrical Engineering Key Laboratory of High Density Electromagnetic Power and Systems Chinese Academy of Sciences Beijing100190 China School of Electrical and Electronic Engineering Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan430074 China

ISBN: (纸本)9798331530174

Model predictive control (MPC) enables the linear induction motor (LIM) drive system to maintain good performance despite large distortions in the input voltage waveform, and is particularly suitable for applications with lower converter switching frequencies, such as urban rail transit. However, the parameters of the LIM vary dramatically due to the end effect, which reduces the control performance of the MPC. This paper presents a nonparametric sliding mode predictive current control method to enhance the parametric robustness of MPC. The cost function of nonparametric current control is constructed to overcome the limitation of model predictive control, which is greatly affected by parameter accuracy. The simulation results show that the proposed method can maintain the good control performance of the LIM drive system under the condition of inaccurate parameters, effectively improve the robustness of the system, and has certain engineering significance. © 2024 ieee.

关键词： Cost functions

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Sliding Mode control for Helicopter Systems Based on Fully Actuated Method 3

Sliding Mode Control for Helicopter Systems Based on Fully A...

引用

3rd conference on Fully Actuated System Theory and applications (FASTA)

作者： Li, Yankai Xu, Jinyu Xue, Xiaohui Lie, Dongping Yi, Yingmin Shao, Shuyi Xian Univ Technol Sch Automat & Informat Engn Xian 710048 Peoples R China Xian Technol Univ Sch Sci Xian 710021 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Peoples R China

ISBN: (纸本)9798350373707;9798350373691

Based on fully actuated technology, a sliding mode control approach is suggested for helicopter systems with all degrees of freedom. First, the degree of nonlinearity and coupling is lessened by applying the feedback linearization technique. And the helicopter systems transform into fully actuated systems. Secondly, a sliding mode controller is built with the assumption of system stability in order to achieve the intended tracking task. Third, the reliability of complete closed-loop structures is investigated using Lyapunov theory. Finally, this work presents simulation data to validate the effectiveness of the designed control technique.

关键词： Helicopter systems Feedback linearization Sliding mode control Fully actuated method

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Cloud Data Deduplication Methods Supporting Popularity-Based Partitioning and Access control 24

Cloud Data Deduplication Methods Supporting Popularity-Based...

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24th ieee International conference on Communication technology, ICCT 2024

作者： Chen, Minshi Liu, Jia Ni, Ningning Zhang, Chen China Mobile Communications Group Co. Ltd. Beijing China China Mobile Group Design Institute Co. Ltd. Beijing China

ISBN: (纸本)9798350363760

Data deduplication technologies have widespread applications in cloud storage systems. They can effectively save network bandwidth during file uploads and downloads, improving the storage efficiency of cloud servers. However, data in cloud servers is often stored in encrypted form, and differing encryption keys can result in the same file data generating different ciphertexts. Therefore, efficient data security deduplication techniques have become a research hotspot in the field of cloud *** address the issues existing in current cloud storage encrypted data deduplication, this paper proposes a cloud data deduplication method that supports popularity-based partitioning and access control. In this method, data is partitioned based on its popularity. For high-privacy non-popular data, an encryption deduplication protection scheme with access control and key updates is employed. By combining access control with Proof of Ownership, the method effectively prevents unauthorized data access and ownership deception attacks by adversaries. For low-privacy popular data, simple and efficient convergent encryption is *** evaluation results indicate that the proposed method achieves efficient data encryption, decryption, and key updating. © 2024 ieee.

关键词： Ciphertext

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MEC-assisted Low Latency Communication for Autonomous Flight control of 5G-Connected UAV 97

MEC-assisted Low Latency Communication for Autonomous Flight...

引用

97th ieee Vehicular technology conference (VTC-Spring)

作者： Solanki, Sourabh Mahmood, Asad Singh, Vibhum Gautam, Sumit Querol, Jorge Chatzinotas, Symeon Univ Luxembourg Interdisciplinary Ctr Secur Reliabil & Trust SnT Luxembourg Luxembourg Indian Inst Technol Indore Dept Elect Engn Indore India

ISBN: (纸本)9798350311143

Proliferating applications of unmanned aerial vehicles (UAVs) impose new service requirements, leading to several challenges. One of the crucial challenges in this vein is to facilitate the autonomous navigation of UAVs. Concretely, the UAV needs to individually process the visual data and subsequently plan its trajectories. Since the UAV has limited onboard storage constraints, its computational capabilities are often restricted and it may not be viable to process the data locally for trajectory planning. Alternatively, the UAV can send the visual inputs to the ground controller which, in turn, feeds back the command and control signals to the UAV for its safe navigation. However, this process may introduce some delays, which is not desirable for autonomous UAVs' safe and reliable navigation. Thus, it is essential to devise techniques and approaches that can potentially offer low-latency solutions for planning the UAV's flight. To this end, this paper analyzes a multi-access edge computing aided UAV and aims to minimize the latency of the task processing. More specifically, we propose an offloading strategy for a UAV by optimally designing the offloading parameter, local computational resources, and altitude of the UAV. The numerical and simulation results are presented to offer various design insights, and the benefits of the proposed strategy are also illustrated in contrast to the other baseline approaches.

关键词： Unmanned aerial vehicles (UAV)

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Design, Implementation and Demonstration of Vector controlled Permanent Magnet Synchronous Motor Drive in EV applications 4

Design, Implementation and Demonstration of Vector Controlle...

引用

4th ieee International conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Kumar Ch, S.V.S. Phani Dewangan, Himani Sonti, Venu Jain, Sachin Transportation Vertical L&t Technology Services Bangalore India Nit Raipur Electrical Engineering Department Raipur India

ISBN: (纸本)9798350383997

The paper presents an overview of the design and constructional features of vector control technique implemented in Permanent Magnet Synchronous Motor (PMSM) to achieve efficient speed-torque control in Electric Vehicle (EV) applications. Several key aspects are involved in the design of a PMSM, which includes selection of material for permanent magnet, geometry of stator and rotor, and optimization of the winding configuration. The choice of permanent magnet material affects the motor's magnetic properties, such as coercivity and remanence, which has direct impact on its performance. The impact of geometry design of the stator and rotor are to maximize the magnetic coupling between the stator windings and permanent magnet, ensuring efficient energy conversion. Additionally, the winding configuration is carefully engineered to achieve the desired torque characteristics and minimize losses. The paper considers all the above aspect and demonstrates the design and implementation of vector control based PMSM in both Ansys EM Suite and MATLAB/Simulink environments. Further, the paper demonstrates how the vector control independently controls the flux and torque by decoupling the motor's magnetic field into flux-producing (d-axis) and torque-producing (q-axis) components in both the software tools (ANSYS and MATLAB/Simulink). Additionally, the paper also demonstrates the proportional-integral control strategy which governs and regulate the motor's electromagnetic torque and flux. © 2024 ieee.

关键词： Stators

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Ultrasonic Guided Wave Dispersion Compensation Based on Fourier Basis Convolutional Autoencoder 43

Ultrasonic Guided Wave Dispersion Compensation Based on Four...

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43rd Chinese control conference (CCC)

作者： Zeng, Jianxin Mei, Lin Li, Shuaiyong Li, MaoYang Yang, Zhang Chongqing Univ Posts & Telecommun Minist Educ Key Lab Ind Internet Things & Networked Control Chongqing 400065 Peoples R China Chongqing Special Equipment Inspect & Res Inst Chongqing 401121 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

Ultrasonic guided waves are widely used signals in industry, but their inherent dispersion and multimodal characteristics significantly impact practical applications. Considering the frequency-dependent nature of guided wave signals, this paper proposes a Fourier-based convolutional autoencoder (FCAE) algorithm for dispersion compensation in ultrasonic guided wave signals, thoroughly investigating its practical application in handling ultrasonic guided wave signals. The neural network model combines the time-frequency analysis characteristics of Fourier bases and the nonlinear mapping capability of neural networks to learn the time of flight (TOF) of guided wave modes. Through this approach, the model successfully eliminates phase distortion and energy leakage caused by Lamb wave dispersion in guided wave signals, thereby significantly improving the quality and interpretability of the signals. The proposed Fourier-based neural network model's effectiveness in dispersion compensation is validated through simulation experiments, providing robust support for further applications of ultrasonic guided wave technology.

关键词： Fourier Basis Convolutional Autoencoder Ultrasonic Guided Wave Dispersion Compensation

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