Aging is the fundamental of neurodegeneration and dementia, affecting every organ in the body. With the aggravation of global aging, more and more research is focusing on how brain changes in older adults. This study aimed to uncover the differences in brain functional networks from the perspective of graph theory between young individuals and older individuals. Here, 61 individuals in their 20s and 94 cognitively healthy old individuals in their 70s underwent a resting-state functional magnetic resonance imaging scan. Based on the graph theory method, a functional network was constructed for each participant. Our results revealed that brain functional networks in older adults maintained small-world properties. However other nodal parameters including degree centrality, betweenness centrality, shortest path lengths, local efficiency, nodal efficiency, and cluster coefficients showed significant differences in many nodes (brain regions) between the 2 groups. Moreover, we correlated these nodal parameters with age, exploring 8 brain regions significantly affected with age. 7 out of 8 brain regions including the bilateral superior parietal lobule, bilateral precuneus, right middle cingulate, right inferior parietal lobule and right transverse temporal gyri were distributed in the default mode network. Our findings, based on graph theory, provided evidence for the alteration of the default mode network in older adults from the perspective of the functional network.
{"title":"Alterations of Brain Functional Networks in Older Adults: A Resting-state fMRI Study Using Graph Theory","authors":"Jing Ai, Tiantian Liu, Kexin Wang, Tianyi Yan, Jian Zhang, Tianlin Huang","doi":"10.1109/CISP-BMEI51763.2020.9263643","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263643","url":null,"abstract":"Aging is the fundamental of neurodegeneration and dementia, affecting every organ in the body. With the aggravation of global aging, more and more research is focusing on how brain changes in older adults. This study aimed to uncover the differences in brain functional networks from the perspective of graph theory between young individuals and older individuals. Here, 61 individuals in their 20s and 94 cognitively healthy old individuals in their 70s underwent a resting-state functional magnetic resonance imaging scan. Based on the graph theory method, a functional network was constructed for each participant. Our results revealed that brain functional networks in older adults maintained small-world properties. However other nodal parameters including degree centrality, betweenness centrality, shortest path lengths, local efficiency, nodal efficiency, and cluster coefficients showed significant differences in many nodes (brain regions) between the 2 groups. Moreover, we correlated these nodal parameters with age, exploring 8 brain regions significantly affected with age. 7 out of 8 brain regions including the bilateral superior parietal lobule, bilateral precuneus, right middle cingulate, right inferior parietal lobule and right transverse temporal gyri were distributed in the default mode network. Our findings, based on graph theory, provided evidence for the alteration of the default mode network in older adults from the perspective of the functional network.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117110394","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263492
Shan Liu, Yingbo Zhang, Sichen Wang
The number of film works in China has increased year by year, many works have won unanimous praise from domestic and foreign audiences. But overall, the quality of works in the entire domestic film industry is still uneven, more high-quality film works are needed. In this paper, a new method based on multiple dimensions to analyze and excavate the film works communication effects is proposed. By categorizing and summarizing the film genres, the system can predict the communication effects of different types of film works and provide creative suggestions based on the market acceptance. According to the audience preferences, the system will recommend different film works to meet the audience’s needs. The simulation results demonstrated that the prediction system can greatly improve the propagation of film works.
{"title":"Development of Film Genres Prediction System Based on Intelligent Tags","authors":"Shan Liu, Yingbo Zhang, Sichen Wang","doi":"10.1109/CISP-BMEI51763.2020.9263492","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263492","url":null,"abstract":"The number of film works in China has increased year by year, many works have won unanimous praise from domestic and foreign audiences. But overall, the quality of works in the entire domestic film industry is still uneven, more high-quality film works are needed. In this paper, a new method based on multiple dimensions to analyze and excavate the film works communication effects is proposed. By categorizing and summarizing the film genres, the system can predict the communication effects of different types of film works and provide creative suggestions based on the market acceptance. According to the audience preferences, the system will recommend different film works to meet the audience’s needs. The simulation results demonstrated that the prediction system can greatly improve the propagation of film works.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128121379","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263581
Yan Liu, Fulai An, Xun Lang, Yakang Dai
Noninvasive scalp single channel EEG is increasing being applied in our daily lives, due to its minimal instrumentation complexity and safety compared with multichannel EEG and invasive EEG. The unavoidable artifacts really hamper its applications and the artifacts correction remains challenging especially in the case of only one channel recordings available. In this paper, we propose a novel approach for removing motion artifacts, particularly frequent during recording, from scalp single channel EEG recordings. The novel approach is developed based on Noise Assisted Least Square Multivariate Empirical Mode Decomposition (NALSMEMD), which solves the problems of subspace incompleteness in Ensemble EMD (EEMD) and therefore further improve the motion artifacts removal performance. First, the single channel EEG is decomposed into several Intrinsic Mode Functions (IMFs) assisted by the separated white Gaussian noise channels. Then the artifacts related IMFs are selected and rejected according to the IMFs’ autocorrelation coefficients. Finally, the EEG related IMFs are reconstructed as the motion artifacts free EEG. The 23 sessions of single channel EEG data downloaded from https://www.physionet.org/content/motion-artifacts/1.0.0/ are used in our study for verifying the performance of our approach. The results show that our approach outperforms EEMD based approach in terms of SNR change before and after artifacts removal and percentage reduction in artifacts after artifacts removal.
{"title":"Remove Motion Artifacts from Scalp Single Channel EEG based on Noise Assisted Least Square Multivariate Empirical Mode Decomposition","authors":"Yan Liu, Fulai An, Xun Lang, Yakang Dai","doi":"10.1109/CISP-BMEI51763.2020.9263581","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263581","url":null,"abstract":"Noninvasive scalp single channel EEG is increasing being applied in our daily lives, due to its minimal instrumentation complexity and safety compared with multichannel EEG and invasive EEG. The unavoidable artifacts really hamper its applications and the artifacts correction remains challenging especially in the case of only one channel recordings available. In this paper, we propose a novel approach for removing motion artifacts, particularly frequent during recording, from scalp single channel EEG recordings. The novel approach is developed based on Noise Assisted Least Square Multivariate Empirical Mode Decomposition (NALSMEMD), which solves the problems of subspace incompleteness in Ensemble EMD (EEMD) and therefore further improve the motion artifacts removal performance. First, the single channel EEG is decomposed into several Intrinsic Mode Functions (IMFs) assisted by the separated white Gaussian noise channels. Then the artifacts related IMFs are selected and rejected according to the IMFs’ autocorrelation coefficients. Finally, the EEG related IMFs are reconstructed as the motion artifacts free EEG. The 23 sessions of single channel EEG data downloaded from https://www.physionet.org/content/motion-artifacts/1.0.0/ are used in our study for verifying the performance of our approach. The results show that our approach outperforms EEMD based approach in terms of SNR change before and after artifacts removal and percentage reduction in artifacts after artifacts removal.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121665571","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263646
Zhengzhen Li, Ke Li, Na Wei
In this paper, three different classification methods, including the support vector machine (SVM), the deep learning method based on multi-layer perceptron (MLP) and multichannel convolutional neural network (multi-channel CNN), were used to classify 13 hand gestures. The surface electromyography (sEMG) were extracted from six muscles of hand and forearm. For the SVM and MLP, six features in the time domain, frequency domain and time-frequency domain were extracted. For the multi-channel CNN, a sliding window segment of the original sEMG image was used as the input. Hand gesture recognition based on deep learning had similar performance to traditional machine learning in off-line classification. Considering the high robustness and generalization ability, deep learning is likely a more robust alternative to traditional machine learning in the field of sEMG hand gesture recognition.
{"title":"A sEMG-Based Hand Gesture Recognition Using Mulit-channel CNN and MLP","authors":"Zhengzhen Li, Ke Li, Na Wei","doi":"10.1109/CISP-BMEI51763.2020.9263646","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263646","url":null,"abstract":"In this paper, three different classification methods, including the support vector machine (SVM), the deep learning method based on multi-layer perceptron (MLP) and multichannel convolutional neural network (multi-channel CNN), were used to classify 13 hand gestures. The surface electromyography (sEMG) were extracted from six muscles of hand and forearm. For the SVM and MLP, six features in the time domain, frequency domain and time-frequency domain were extracted. For the multi-channel CNN, a sliding window segment of the original sEMG image was used as the input. Hand gesture recognition based on deep learning had similar performance to traditional machine learning in off-line classification. Considering the high robustness and generalization ability, deep learning is likely a more robust alternative to traditional machine learning in the field of sEMG hand gesture recognition.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121914858","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263637
Xiujun Li, Jingjing Yang, Jinglong Wu, Dan Tong
Reading and writing in the second language (L2) is a very difficult process, involving the communication between native language (L1) and second languages. Previous studies have shown that bilingual learners use their marker graphic L1 (Chinese) to read the neural system and apply it to the letter two (English) reading. Functional magnetic resonance imaging (fMRI) was used to investigate the differences of brain activity during semantic and phonological processing. In the experiment, semantic and phonological processing related tasks in Chinese and Japanese were used to explore the differences of brain activity between Chinese and Japanese bilingual and Japanese subjects by judging different brain activation in the task. The results showed that for Chinese and Japanese bilingual subjects, the subtraction of Chinese semantic judgment task and Chinese pronunciation judgment task did not get the difference brain area, while the subtraction of Japanese semantic judgment task and Japanese pronunciation judgment task got the difference brain area, It is mainly manifested in the right anterior frontal gyrus (Ba8 / 9), left fusiform gyrus (BA37) and right temporal lobe (Ba22 / 38); for Japanese subjects, the subtraction of Japanese semantic judgment task and Japanese pronunciation judgment task leads to the difference between the two brain regions, mainly in the left superior temporal gyrus (Ba40) and left temporal lobe (Ba22) and so on.
{"title":"Studies on the Differences Semantic Processing Between Chinese-Japanese Bilinguals and Japanese Native Subjects","authors":"Xiujun Li, Jingjing Yang, Jinglong Wu, Dan Tong","doi":"10.1109/CISP-BMEI51763.2020.9263637","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263637","url":null,"abstract":"Reading and writing in the second language (L2) is a very difficult process, involving the communication between native language (L1) and second languages. Previous studies have shown that bilingual learners use their marker graphic L1 (Chinese) to read the neural system and apply it to the letter two (English) reading. Functional magnetic resonance imaging (fMRI) was used to investigate the differences of brain activity during semantic and phonological processing. In the experiment, semantic and phonological processing related tasks in Chinese and Japanese were used to explore the differences of brain activity between Chinese and Japanese bilingual and Japanese subjects by judging different brain activation in the task. The results showed that for Chinese and Japanese bilingual subjects, the subtraction of Chinese semantic judgment task and Chinese pronunciation judgment task did not get the difference brain area, while the subtraction of Japanese semantic judgment task and Japanese pronunciation judgment task got the difference brain area, It is mainly manifested in the right anterior frontal gyrus (Ba8 / 9), left fusiform gyrus (BA37) and right temporal lobe (Ba22 / 38); for Japanese subjects, the subtraction of Japanese semantic judgment task and Japanese pronunciation judgment task leads to the difference between the two brain regions, mainly in the left superior temporal gyrus (Ba40) and left temporal lobe (Ba22) and so on.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122580477","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263501
Tong-xiang Wang, Yanhua Jin
In order to solve the problems of complex networks, large amount of calculation and high equipment requirements in the current deep learning method to complete the modulation recognition process, this paper proposes a modulation recognition algorithm based on lightweight neural networks. First, map the common 8 kinds of modulated signals to constellation diagrams to make image data sets. In the process of retaining the original signals, make full use of the performance of the neural network, build a representative the MobileNet neural network in the neural network to complete the training of the data set, use the test samples Verify the effectiveness of the lightweight neural networks used. Simulation experiment results show that the overall recognition rate of modulation reaches 98% when the SNR is greater than 2dB, but the training speed is greatly improved.
{"title":"Modulation Recognition Based on Lightweight Neural Networks","authors":"Tong-xiang Wang, Yanhua Jin","doi":"10.1109/CISP-BMEI51763.2020.9263501","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263501","url":null,"abstract":"In order to solve the problems of complex networks, large amount of calculation and high equipment requirements in the current deep learning method to complete the modulation recognition process, this paper proposes a modulation recognition algorithm based on lightweight neural networks. First, map the common 8 kinds of modulated signals to constellation diagrams to make image data sets. In the process of retaining the original signals, make full use of the performance of the neural network, build a representative the MobileNet neural network in the neural network to complete the training of the data set, use the test samples Verify the effectiveness of the lightweight neural networks used. Simulation experiment results show that the overall recognition rate of modulation reaches 98% when the SNR is greater than 2dB, but the training speed is greatly improved.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126502450","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263512
Yuanzhe Zhao, Chundong Hu, Q. Cui, Wei Liu
Neutral beam injection (NBI) heating is one of the most efficient auxiliary plasma heating methods for fusion devices. The development of timing node (TN) for NBI system in the experimental advanced superconducting tokamak (EAST) is presented in this paper. AS an important sub-system, TN is designed to provide a unified clock for all sub-systems of NBI, control the input/output services of digital and analog signals, realize failsafe and latch the trouble signals, and control DC/AC output of high voltage power supply system. The timing node is developed on a PXI (PCI eXtensions for Instrumentation) platform consisting of a LabVIEW workstation and a timing control terminal. The architecture and implementation of TN are presented in this paper.
中性束注入(NBI)加热是核聚变装置最有效的辅助等离子体加热方法之一。本文介绍了实验性先进超导托卡马克(EAST) NBI系统定时节点(TN)的研制情况。TN作为一个重要的子系统，为NBI的所有子系统提供统一的时钟，控制数字和模拟信号的输入/输出服务，实现故障信号的故障保护和锁存，控制高压供电系统的DC/AC输出。时序节点是在PXI (PCI eXtensions for Instrumentation)平台上开发的，该平台由LabVIEW工作站和时序控制终端组成。本文介绍了TN的体系结构和实现方法。
{"title":"Development of Timing Node on EAST Neutral Beam Injector","authors":"Yuanzhe Zhao, Chundong Hu, Q. Cui, Wei Liu","doi":"10.1109/CISP-BMEI51763.2020.9263512","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263512","url":null,"abstract":"Neutral beam injection (NBI) heating is one of the most efficient auxiliary plasma heating methods for fusion devices. The development of timing node (TN) for NBI system in the experimental advanced superconducting tokamak (EAST) is presented in this paper. AS an important sub-system, TN is designed to provide a unified clock for all sub-systems of NBI, control the input/output services of digital and analog signals, realize failsafe and latch the trouble signals, and control DC/AC output of high voltage power supply system. The timing node is developed on a PXI (PCI eXtensions for Instrumentation) platform consisting of a LabVIEW workstation and a timing control terminal. The architecture and implementation of TN are presented in this paper.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131901142","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263518
Guoming Chen
In this paper, we propose a Schroedinger Eigenmaps (SE) manifold learning and dimensionality reduction method on glaucoma image classification. The visualization of binary image recognition three dimensional electronic cloud image on the retinal fundus dataset shows that after quantum circuit diagram transformation, the recognition performance of the image data in the Schroedinger Eigenmaps (SE) manifold learning dimensionality reduction spatial distribution has been significantly improved for binary image classification.
{"title":"Schroedinger Eigenmaps for Dimensionality Reduction and Image Classification","authors":"Guoming Chen","doi":"10.1109/CISP-BMEI51763.2020.9263518","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263518","url":null,"abstract":"In this paper, we propose a Schroedinger Eigenmaps (SE) manifold learning and dimensionality reduction method on glaucoma image classification. The visualization of binary image recognition three dimensional electronic cloud image on the retinal fundus dataset shows that after quantum circuit diagram transformation, the recognition performance of the image data in the Schroedinger Eigenmaps (SE) manifold learning dimensionality reduction spatial distribution has been significantly improved for binary image classification.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"63 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129561363","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263503
Tongtong Liu, Wenming Ma, Yulong Song
The appearance of recommendation system solves the problem of information overload. Traditional recommendation systems generally consider the preferences of users, but ignore external conditions, such as the timeliness and popularity of goods.In this experiment, the time factor is added to form a triple, like User-Item-Time, and the neural network is used for training. Compared with the matrix factorization experiment which integrates time factor, the prediction effect is better when the movie popularity is integrated into the recommendation.
{"title":"Deep Time-Aware Matrix Factorization","authors":"Tongtong Liu, Wenming Ma, Yulong Song","doi":"10.1109/CISP-BMEI51763.2020.9263503","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263503","url":null,"abstract":"The appearance of recommendation system solves the problem of information overload. Traditional recommendation systems generally consider the preferences of users, but ignore external conditions, such as the timeliness and popularity of goods.In this experiment, the time factor is added to form a triple, like User-Item-Time, and the neural network is used for training. Compared with the matrix factorization experiment which integrates time factor, the prediction effect is better when the movie popularity is integrated into the recommendation.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131642152","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}
Pub Date : 2020-10-17DOI: 10.1109/CISP-BMEI51763.2020.9263689
Jiejun Yin, H. Bi, F. Tian, Ling Wang, Jiarui Deng, Jingjing Zhang
As a potential tool for atmospheric observation, weather radar has shown good performance in providing abundant meteorological data during a short time. The key to use weather radar is that the collected data should have sufficient accuracy. To achieve this purpose, weather radar external calibration technique is proposed and applied for practical data processing, which is usually performed based on the deployed calibrators. However, because of the environment of calibration field is complicated and the scheme is difficult to operate, traditional deployed calibrator based methods have several limitations. In this paper, the novel low-cost and repeatable simulated calibrators based weather radar external calibration technology is proposed. Experimental results show that in the single-polarized mode, the proposed method can recover the reflectivity factor accurately from noisy echo data. While in the dual-polarized mode, the crosstalk and channel imbalance can be estimated and compensated successfully by the proposed method.
{"title":"Simulated Calibrators Based Polarimetric Weather Radar External Calibration","authors":"Jiejun Yin, H. Bi, F. Tian, Ling Wang, Jiarui Deng, Jingjing Zhang","doi":"10.1109/CISP-BMEI51763.2020.9263689","DOIUrl":"https://doi.org/10.1109/CISP-BMEI51763.2020.9263689","url":null,"abstract":"As a potential tool for atmospheric observation, weather radar has shown good performance in providing abundant meteorological data during a short time. The key to use weather radar is that the collected data should have sufficient accuracy. To achieve this purpose, weather radar external calibration technique is proposed and applied for practical data processing, which is usually performed based on the deployed calibrators. However, because of the environment of calibration field is complicated and the scheme is difficult to operate, traditional deployed calibrator based methods have several limitations. In this paper, the novel low-cost and repeatable simulated calibrators based weather radar external calibration technology is proposed. Experimental results show that in the single-polarized mode, the proposed method can recover the reflectivity factor accurately from noisy echo data. While in the dual-polarized mode, the crosstalk and channel imbalance can be estimated and compensated successfully by the proposed method.","PeriodicalId":346757,"journal":{"name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127624689","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}
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