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2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)最新文献

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A code-assisted carrier synchronization algorithm based on Expectation-Maximum algorithm 基于期望最大值算法的码助载波同步算法
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176829
Jia-Nan Sun
{"title":"A code-assisted carrier synchronization algorithm based on Expectation-Maximum algorithm","authors":"Jia-Nan Sun","doi":"10.1109/ICECAI58670.2023.10176829","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176829","url":null,"abstract":"The performance of the LDPC decoder suffers from deterioration when receiving a signal with residual carrier bias. To address this problem, a carrier synchronization algorithm assisted by LDPC code is proposed. The proposed algorithms include rough carrier estimation and carrier fine estimation based on Expectation-Maximum (EM) algorithm. To reduce the problem of high resource consumption, a cost function that is only related to residual frequency bias is proposed in this article. An iterative carrier fine estimation algorithm using posteriori probability obtained by the LDPC decoder is proposed based on EM algorithm, and the analytic solution of the algorithm is derived in this article. The simulation results validated that the proposed algorithm has a large estimation range, and realizes effective carrier synchronization at a low signal-to-noise ratio (SNR).","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115422334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
License Plate Image Recognition System Based on Firefly Algorithm and BP Neural Network 基于萤火虫算法和BP神经网络的车牌图像识别系统
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176613
Kangyou Su, Ling Zhang, Jianyi Wang
{"title":"License Plate Image Recognition System Based on Firefly Algorithm and BP Neural Network","authors":"Kangyou Su, Ling Zhang, Jianyi Wang","doi":"10.1109/ICECAI58670.2023.10176613","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176613","url":null,"abstract":"Aiming at the defects of low license plate recognition accuracy of the traditional BP (Back Propagation) neural network, a license plate recognition algorithm based on FA (Firefly algorithm) and BP neural network is proposed. Firstly, image enhancement is performed on a license plate image captured by cameras, and then, the license plate image is grayed by the maximum method, average method, and weighted average graying to obtain the best image. Secondly, Hough transform is adopted for license plate correction, segmentation, and location. Finally, FA is introduced into BP neural network to recognize license plate characters. The results show that compared with the traditional BP neural network license plate recognition algorithm, the algorithm proposed in this paper improves the recognition accuracy of Chinese characters, letters, and the overall license plate recognition rate by 4.6%, 2%, and 6.4% respectively.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116886537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Image Registration Algorithm Based on Improved SIFT 基于改进SIFT的图像配准算法
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176776
Xinyang Li, Siyang Li
{"title":"Image Registration Algorithm Based on Improved SIFT","authors":"Xinyang Li, Siyang Li","doi":"10.1109/ICECAI58670.2023.10176776","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176776","url":null,"abstract":"A method is proposed to combine the Shi-Tomasi algorithm with the SFT (Scale-Invariant Feature Transform) algorithm for image registration, aiming to address the non-real-time issue of the SIFT algorithm. The method utilizes the Shi-Tomasi algorithm to extract feature points, and the more efficient PROSAC algorithm is employed to replace the traditional RANSAC algorithm for removing mismatches. Experimental results demonstrate that the proposed algorithm effectively improves matching accuracy while reducing the image matching time by 66.5%.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124575132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The implement of synchronization and differential demodulation algorithm of GMSK signal GMSK信号同步和差分解调算法的实现
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176994
G. Wang, Jianbin Chen, Zhonghua Bao, Liting Chen, Tianyu Li
{"title":"The implement of synchronization and differential demodulation algorithm of GMSK signal","authors":"G. Wang, Jianbin Chen, Zhonghua Bao, Liting Chen, Tianyu Li","doi":"10.1109/ICECAI58670.2023.10176994","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176994","url":null,"abstract":"GMSK has the advantages of constant envelope, continuous phase, and concentrated power spectral density, and is widely used in the field of digital communication with limited frequency bands. Aiming at the multi-channel receiver system with limited hardware resources, an algorithm for obtaining bit synchronization information based on the phase characteristics and waveform characteristics of the GMSK signal is proposed, which has a simple structure, occupies less hardware resources, has a low sampling rate, and is easy to implement by engineering. And combined with the 2-bit of 10Mpbs, the bit synchronization algorithm can accurately output bit synchronization information at only 5 times the sampling rate, and the demodulation algorithm has only 0.6dB of demodulation loss compared with the theoretical value, which has excellent demodulation performance.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"57 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123492905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Injection Signal Detection Based on PSO-Optimized Extended Kalman Filter 基于pso优化扩展卡尔曼滤波的注入信号检测
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176836
Renjie Li, Xi Cai, Zuoyi Yao, Longwei Chen, Junhao Wang
{"title":"Injection Signal Detection Based on PSO-Optimized Extended Kalman Filter","authors":"Renjie Li, Xi Cai, Zuoyi Yao, Longwei Chen, Junhao Wang","doi":"10.1109/ICECAI58670.2023.10176836","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176836","url":null,"abstract":"In the condition monitoring of ship cables, in order to improve the accuracy of the mixing injection method in cable current detection, this paper proposes the PSO-EKF method for state estimation. We optimize the state covariance matrix and process noise variance of the extended Kalman filter by particle swarm optimization algorithm, which solves the problem that the EKF is challenging to select the optimal covariance matrix. The experimental results show that the particle swarm optimization extended Kalman detection tracking effect has been dramatically improved compared with the traditional Kalman.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114214132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Traffic Pattern Recognition Method with XGBoost Based on Multi-scale Features 基于多尺度特征的XGBoost交通模式识别方法
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176405
Yunlong Song, Hao Wang
{"title":"Traffic Pattern Recognition Method with XGBoost Based on Multi-scale Features","authors":"Yunlong Song, Hao Wang","doi":"10.1109/ICECAI58670.2023.10176405","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176405","url":null,"abstract":"Traffic pattern recognition belongs to a branch of scene recognition and has become a hot research field. Correctly identifying the transportation mode used by users to travel plays a vital role in promoting the development of situational recognition. In the field of traffic pattern recognition research, many recognition methods use GPS, the combination of GPS and WiFi, and the combination of GSM and WiFi to obtain data, and use LR, SVM and deep learning models to make predictions. However, these methods have some disadvantages, such as poor WiFi signal in some outdoor environments, resulting in failure to obtain user data, GPS being interfered by the external environment, resulting in inaccurate data acquisition and other issues, and the models they use have problems such as low prediction accuracy or prolonged prediction consumption. In response to these problems, this paper uses multi-source sensors in mobile phones to obtain data, and preprocesses sensor data through statistics and signal processing methods to generate features at different scales, and finally uses XGBoost to identify various traffic modes. Extensive experiments are carried out on the method proposed in this paper, and the effectiveness of the proposed method is demonstrated by comparing with two state-of-the-art methods.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"380 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114790502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Neural Network-based Model Predictive Control Approach for Modular Multilevel Converters 基于神经网络的模块化多电平变换器模型预测控制方法
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176482
Hongjun Wang, Youjun Yue, Boao Sun, Hui Zhao
{"title":"Neural Network-based Model Predictive Control Approach for Modular Multilevel Converters","authors":"Hongjun Wang, Youjun Yue, Boao Sun, Hui Zhao","doi":"10.1109/ICECAI58670.2023.10176482","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176482","url":null,"abstract":"This paper proposes a neural network (NN) approach as an alternative to the computationally burdensome model predictive control (MPC) in controlling modular multilevel converters (MMCs). Simulation results demonstrate the effectiveness of our approach, with a back propagation (BP) neural network model successfully trained and the NN controller performing comparably to the MPC controller in suppressing circulating currents and stabilizing submodule voltages, while reducing the computational burden of the controller. Additionally, our approach provides an effective control solution for MMCs that can be implemented in real-time power electronic applications, and has important implications for power system optimization and future research in neural network control beyond MMCs.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124376823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on short-term power load forecasting method based on EMD-GRU 基于 EMD-GRU 的短期电力负荷预测方法研究
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10177036
L. Zheng, Kui Wang
{"title":"Research on short-term power load forecasting method based on EMD-GRU","authors":"L. Zheng, Kui Wang","doi":"10.1109/ICECAI58670.2023.10177036","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10177036","url":null,"abstract":"The volatility, non-stationarity, and non-linearity of power load data make it tricky for traditional prediction methods to accurately predict it, while precise forecasting of load data can raise the reliability and economy. Therefore, a combination prediction model based on EMD-GRU network is presented in this paper. Firstly, this paper collected the electric load data set of Cyprus for the whole year of 2018, with a sampling interval of 1 hour. Then, the data was decomposed into multiple sub-sequence modal components using the EMD method, and GRU was used to predict each sub-sequence component. Finally, superimposing the forecasting results of each sub-sequence component, the prediction of power load data was completed. The experimental results indicate that the EMD-GRU-based power load prediction model exhibits superior prediction precision and outperforms other neural network algorithms currently employed.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130178477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on clock holding technology based on PSO-BP neural network 基于PSO-BP神经网络的时钟保持技术研究
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176753
Zengguang Song, Jinsong Xu, Yan Zhen, Jiawei Jiang
{"title":"Research on clock holding technology based on PSO-BP neural network","authors":"Zengguang Song, Jinsong Xu, Yan Zhen, Jiawei Jiang","doi":"10.1109/ICECAI58670.2023.10176753","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176753","url":null,"abstract":"Aiming at the problem that the local crystal oscillator is affected by its own aging factors, which will lead to a decrease in the retention accuracy of the clock synchronization system, firstly, by introducing the particle swarm optimization algorithm, the selection of the initial weight and threshold of the BP neural network is optimized, and the convergence speed is improved. Then use the PSO-BP neural network model to fit and predict the aging data of the two groups of crystal oscillators, establish a related aging model, compare the prediction error of the BP neural network model before and after the optimization of the particle swarm algorithm, and verify the good optimization ability of the particle swarm algorithm. Finally, the model is applied to the clock synchronization system. The frequency accuracy of the system within 24 hours of reference 1PPS signal loss can be maintained at the order of $pm 8 times 10^{-11}$, achieving a high-precision clock retention effect.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134124611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving Image Compression Performance by Spatial-Channel Context Adaptive Model 利用空间信道上下文自适应模型提高图像压缩性能
2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) Pub Date : 2023-05-12 DOI: 10.1109/ICECAI58670.2023.10176903
Hao Wang, Huifen Wang, Junda Xue, Enmin Lu, Hanming Wang, Zijun Wu, Yunlong Song
{"title":"Improving Image Compression Performance by Spatial-Channel Context Adaptive Model","authors":"Hao Wang, Huifen Wang, Junda Xue, Enmin Lu, Hanming Wang, Zijun Wu, Yunlong Song","doi":"10.1109/ICECAI58670.2023.10176903","DOIUrl":"https://doi.org/10.1109/ICECAI58670.2023.10176903","url":null,"abstract":"The significance of enhancing image compression efficiency for machine vision, analysis, and comprehension tasks has gained increasing recognition. In response to this need, we propose and implement a novel method called ELIC (Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding) to achieve high compression efficiency. Our method is evaluated on the classic OpenImage V6 Common Test Condition (CTC) eval datasets, and its performance is compared to baseline methods for machine vision tasks. The results of our study demonstrate a substantial enhancement in compression efficiency, suggesting that the ELIC technique holds promise for pushing the boundaries of state-of-the-art visual compression for vision tasks. Furthermore, we believe that our approach can promote the application of learning-based image compression.","PeriodicalId":189631,"journal":{"name":"2023 4th International Conference on Electronic Communication and Artificial Intelligence (ICECAI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116037670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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