International Conference on Signal Processing and Communication Security最新文献_第4页

Reinforcement learning based access control architecture of Internet of Things big data peak clustering model 基于强化学习的物联网大数据峰值聚类模型访问控制体系结构

International Conference on Signal Processing and Communication Security Pub Date : 2022-11-02 DOI: 10.1117/12.2655168

Qi Xiong

{"title":"Reinforcement learning based access control architecture of Internet of Things big data peak clustering model","authors":"Qi Xiong","doi":"10.1117/12.2655168","DOIUrl":"https://doi.org/10.1117/12.2655168","url":null,"abstract":"In order to improve the accuracy of Internet of Things access control and the clustering of data transmission, a big data peak clustering method based on reinforcement learning is proposed. A big database management model of Internet of Things access control architecture is established by adopting global data pattern. Based on heterogeneous parameters among big data sources of Internet of Things access control architecture, combined with structural feature analysis of data sources, a big data interference filtering model of Internet of Things access control architecture is established by adopting the feature analysis method of blockchain fusion control and association rule mining, and feature extraction of big data peaks of Internet of Things access control architecture is carried out through reinforcement learning algorithm. According to the change of Internet of Things access mode, cluster analysis and pattern recognition of Internet of Things access control architecture big data peak are realized. By constructing the spatial-temporal distribution model of Internet of Things access control architecture big data and Internet of Things transmission channel, the spectral density cluster analysis method is adopted, according to the quantitative parameter analysis of real-time Internet of Things access control architecture data stream, the quantitative recursive analysis method is adopted, and the online Internet of Things access control architecture big data cleaning is used to realize the identification and cluster analysis of Internet of Things access control architecture big data peak features, so as to improve the Internet of Things access control ability. The simulation results show that this method is highly reliable for peak clustering of big data in the access control architecture of the Internet of Things, and has strong dynamic analysis and recognition ability for Internet of Things access and data scheduling, good convergence of data clustering, and low error rate.","PeriodicalId":105577,"journal":{"name":"International Conference on Signal Processing and Communication Security","volume":"491 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117292686","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

Sound source localization method based on dual microarrays and deep learning 基于双微阵列和深度学习的声源定位方法

International Conference on Signal Processing and Communication Security Pub Date : 2022-11-02 DOI: 10.1117/12.2655183

P. Su, Qingning Zeng, Chao Long

引用次数: 0

Reconstruction algorithm of sample missing signal based on factor analysis 基于因子分析的样本缺失信号重构算法

International Conference on Signal Processing and Communication Security Pub Date : 2022-11-02 DOI: 10.1117/12.2655369

Anjun Chen, Baoshuai Wang, Jiacheng Wu

{"title":"Reconstruction algorithm of sample missing signal based on factor analysis","authors":"Anjun Chen, Baoshuai Wang, Jiacheng Wu","doi":"10.1117/12.2655369","DOIUrl":"https://doi.org/10.1117/12.2655369","url":null,"abstract":"The micro-Doppler modulation feature in radar echo can reflect the geometric structure and motion characteristics of targets, and is widely used in target parameter extraction and pattern recognition. Aiming at the problem of low micro-Doppler resolution under the condition of short dwell time, a sample missing signal reconstruction algorithm based on factor analysis (FA) model is proposed. Firstly, FA is used to describe the unknown complete signal, and then the mathematical model between the sample missing observation signal and the unknown complete signal is established. Then Bayesian theory is used to transform it into a full probability model. The model is solved by variable Bayesian expectation maximization (VBEM), so as to obtain the reconstruction of the complete signal. At the same time, for the problem of determining the number of FA factors, the automatic correlation determination (ARD) prior is introduced into the model to realize the automatic determination of the number of factors. Experimental results based on measured data show that the proposed method can achieve better reconstruction performance than the traditional compressive sensing (CS) method.","PeriodicalId":105577,"journal":{"name":"International Conference on Signal Processing and Communication Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129390575","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

The design of wireless sensor terminal on Internet of Things of power transmission and transformation equipment 物联网输变电设备无线传感器终端的设计

International Conference on Signal Processing and Communication Security Pub Date : 2022-11-02 DOI: 10.1117/12.2655336

Lingzhi Zhang, Jie Bai, Zhigang Wang, Chunling Zhang, Dan Wang, Jinan Li, Gaoquan Ding

{"title":"The design of wireless sensor terminal on Internet of Things of power transmission and transformation equipment","authors":"Lingzhi Zhang, Jie Bai, Zhigang Wang, Chunling Zhang, Dan Wang, Jinan Li, Gaoquan Ding","doi":"10.1117/12.2655336","DOIUrl":"https://doi.org/10.1117/12.2655336","url":null,"abstract":"The system design architecture of wireless sensor terminal is introduced in detail. The wireless sensor terminal is composed of M263 Series NuMicro MCU, bme680 sensor of Bosch and Lora wireless communication module. This paper comprehensively considers the functions of each module, communication reliability, power consumption and power saving, and expounds the design points and principles in detail. As the main control software, MCU is responsible for realizing the functions of driving and business processing, As an environmental sensor, bme680 can collect temperature, humidity, air pressure and other information. The communication protocol of Lora wireless communication module adopts the micro power wireless network communication protocol of the Internet of things for power transmission and transformation equipment of the State Grid. Bme680 is responsible for collecting environment information to MCU. MCU and wireless communication module interact with each other through serial port. The wireless communication module transmits data to and receives information from the sink node through wireless mode, so as to realize intelligent management of power equipment operation. Based on the realization of service functions, this paper focuses on the design of MCU software and wireless communication module, as well as the power consumption and power saving of sensor terminals.","PeriodicalId":105577,"journal":{"name":"International Conference on Signal Processing and Communication Security","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132169668","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

A novel micro-motion feature extraction and estimation method for multicomponent signal 一种新的多分量信号微运动特征提取与估计方法

International Conference on Signal Processing and Communication Security Pub Date : 2022-11-02 DOI: 10.1117/12.2655340

Ruonan Li, Zhiwei Yang, Min Hu, Xianghai Li, G. Liao

引用次数: 0