Abstract:In recent years, with the development of device-free sensing (DFS), researchers have applied it to the field of identity recognition. By taking advantage of the unique influence that different people have on surrounding wireless signals, the technology is able to identify people in a contactless way. Some progress has been made in identification by analyzing the gait information in the received wireless signals, but it needs to provide enough space for walking, which limits its application scenarios to some extent. In order to solve this problem, this paper proposes WAID, a recognition system based on human activities. Through analyzing the unique influence of different people doing the same activity on the channel state information (CSI) of WiFi signal, the identity information of people can be extracted from it. Thus, identification can be achieved by performing activities in fixed locations where there are no area requirements. The experimental results show that in the case of 2 to 6 people, the average recognition accuracy of WAID is 94.3% to 88%, and the average accuracy under six positions is 84.8%.

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	1. Research on Activity-based Device-Free Human Identification Approach
	YANG Yu,JIANG Ting,DING Xue,ZHONG Yi
	Electrics, Communication and Autocontrol Technology 31 March 2021
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	Abstract:In recent years, with the development of device-free sensing (DFS), researchers have applied it to the field of identity recognition. By taking advantage of the unique influence that different people have on surrounding wireless signals, the technology is able to identify people in a contactless way. Some progress has been made in identification by analyzing the gait information in the received wireless signals, but it needs to provide enough space for walking, which limits its application scenarios to some extent. In order to solve this problem, this paper proposes WAID, a recognition system based on human activities. Through analyzing the unique influence of different people doing the same activity on the channel state information (CSI) of WiFi signal, the identity information of people can be extracted from it. Thus, identification can be achieved by performing activities in fixed locations where there are no area requirements. The experimental results show that in the case of 2 to 6 people, the average recognition accuracy of WAID is 94.3% to 88%, and the average accuracy under six positions is 84.8%.
	TO cite this article:YANG Yu,JIANG Ting,DING Xue, et al. Research on Activity-based Device-Free Human Identification Approach[OL].[31 March 2021] http://en.paper.edu.cn/en_releasepaper/content/4754417


	2. END-TO-END MUSIC DENOISING APPROACHES BASED ON HIGH-RESOLUTION REPRESENTATIONS
	Lin Chunyu,Liu Shuchang,Guo Li
	Electrics, Communication and Autocontrol Technology 25 March 2020
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	Abstract:With the rapid development of the information technology, digital music is becoming an essential carrier of music communication. Researches of speech enhancement are penetrating deeply and have got a good performance recently, while it is relatively less in music denoising. In the applications of music information retrieval(MIR), such as automatic music transcription and music alignment, various noises may influence the performance of retrieval algorithms. In this paper, end-to-end approaches based on high-resolution representations are presented without manual feature extraction. The U-Net model cascades neural networks with different resolutions while the HRNet model fuses high-to-low resolutions to extract high-resolution features. To solve the lack of specialized music denoising database, we mix the music database MusicNet and the noise database NoiseX-92 with five different signal-to-noise ratios. Through the analysis of source to distortion ratio, the HRNet model outperforms the U-Net model. The results reveal that the resolution fusion methods of HRNet is more suitable for high-resolution feature extraction to reduce noises.
	TO cite this article:Lin Chunyu,Liu Shuchang,Guo Li. END-TO-END MUSIC DENOISING APPROACHES BASED ON HIGH-RESOLUTION REPRESENTATIONS[OL].[25 March 2020] http://en.paper.edu.cn/en_releasepaper/content/4751331

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	3. The study of an integral method of health states for voluntary college students
	PENG Jianrong,YU Junsheng,GUO Jinglin
	Electrics, Communication and Autocontrol Technology 10 March 2020
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	Abstract: An integral method for studying the health states is presented based on the random matrix theory and the classification theory of health states. The pulse of volunteer is labeled by the state 1,2,3,4 respectively, then the single-ring theorem is used to analyze the spectral distribution and mean spectral radius of the pulse, and the health state is obtained. The pulse data of 23 voluntary college students were processed, it has been found that the mean spectral radius of pulse approaches the smallest when the states are both disordered in physical and unbalanced in mental states which is named the state 3.
	TO cite this article:PENG Jianrong,YU Junsheng,GUO Jinglin. The study of an integral method of health states for voluntary college students[OL].[10 March 2020] http://en.paper.edu.cn/en_releasepaper/content/4751133


	4. The new model of semi-tensor compressive sensing
	Liu Lifei, Li Lixiang, Peng Haipeng, Yang Yixian
	Electrics, Communication and Autocontrol Technology 14 January 2019
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	Abstract:Compressive sensing is introduced at first. Compressive sensing not only can compress signal, but also can encrypt signal. But the constraint is that the column of measurement matrix is equal to the row of the signal. In this paper, the model of semi-tensor compressive sensing is given. The model is composed of measurement matrix and auxiliary matrix. The measurement matrix is generated by Logistic chaotic system. The auxiliary matrix is generated by Tent chaotic system. The proposed model breaks the restriction of matrix multiplication, so the matrix can be multiplied when their dimensions do not match. Moreover, the size of measurement matrix of semi-tensor compressive sensing is smaller than compressive sensing, which reduces the transmission overhead and storage space greatly. The experimental simulations show the factor that affect the successful recovery of the signal, including sparsity and the number of measurements. When compression ratio is fixed, the larger the sparsity is, the smaller the percentage of successful recovery is. When sparsity is fixed, the more the number of measurements is, the larger the percentage of successful recovery is. In the experiment, the compression ratio is 0.5, when sparsity is less than 15, the percentage of successful recovery is equal to 1 regardless of the size of measurement matrix.
	TO cite this article:Liu Lifei, Li Lixiang, Peng Haipeng, et al. The new model of semi-tensor compressive sensing[OL].[14 January 2019] http://en.paper.edu.cn/en_releasepaper/content/4747069


	5. A novel time-frequency analysis approach using multiscale radial basis functions aided by a modified particle swarm optimization(PSO) algorithm
	LIU Qing,LI Yang,TAN Sirui
	Electrics, Communication and Autocontrol Technology 31 March 2015
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	Abstract:An efficient time-varying autoregressive (TVAR) modeling approach using the multiscale radial basis functions (MRBF) method is presented for analyzing nonstationary signal processing, with application to artificial EEG data modeling and power spectral estimation. In the new parametric modeling framework, the time-dependent coefficients in the TVAR model are approximated by using MRBF that can better identify time-varying parameters with a variety of dynamic processes in nonstationary signals. Thus, the time-varying modeling problem is simplified to optimal scale determination of MRBF and parameter estimation, which can be effectively resolved by a modified particle swarm optimization (PSO) method and an ordinary least square (OLS) algorithm, respectively. To evaluate the effectiveness of the proposed approach, a comparison with recursive least squares (RLS) and Legendre polynomials expansion method for a synthesized EEG signal is performed. Results demonstrate the proposed approach can indeed provide optimal time-frequency resolution as compared to RLS and Legendre polynomials expansion.
	TO cite this article:LIU Qing,LI Yang,TAN Sirui. A novel time-frequency analysis approach using multiscale radial basis functions aided by a modified particle swarm optimization(PSO) algorithm[OL].[31 March 2015] http://en.paper.edu.cn/en_releasepaper/content/4637119


	6. USER SPECIFIC FRIEND RECOMMENDATION IN SOCIAL MEDIA COMMUNITY
	Cong Guo, Xinmei Tian, Tao Mei
	Electrics, Communication and Autocontrol Technology 22 May 2014
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	Abstract:Social networks nowadays have become an important form of communication in which users can post their current status or share their lives by mobile phones or the Web. In this paper, we develop an effective and efficient model to estimate continuous tie strength between users for friend recommendation with the heterogeneous data from social media community. We categorize those multimodal data into two classes: interaction data (e.g., comments, marking favorite photos) and similarity data(e.g., common friends, groups, tags, geo, visual). We propose to use asymmetric relationship in the interaction data for tie strength estimation instead of using the conventional symmetric ones. Furthermore, by exploring a user's behavior in social media community, we find that the tie strength between users can be approximately modeled as a linear function of their social connections. Based on this observation, we propose an effective and highly efficient user specific linear model for the tie strength estimation. The experiments on a popular social network show promising results and demonstrate the effectiveness of our proposed method.
	TO cite this article:Cong Guo, Xinmei Tian, Tao Mei. USER SPECIFIC FRIEND RECOMMENDATION IN SOCIAL MEDIA COMMUNITY[OL].[22 May 2014] http://en.paper.edu.cn/en_releasepaper/content/4596592


	7. A platform for massive railway information data storage
	SHAN Xu,WANG Genying,LIU Lin
	Electrics, Communication and Autocontrol Technology 01 July 2013
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	Abstract:With the development of national large-scale railway construction, massive railway information data emerge rapidly, and then how to store and manage these data effectively becomes very significant. This paper puts forward a method based on distributed computing technology to store and manage massive railway information data, builds massive railway information data storage platform by using the Linux cluster technology. This system consists of three levels including data access layer, data management layer, application interface layer, enjoying safety and reliability, low operation cost, fast processing speed, easy expansibility characteristics, which shall satisfy the massive railway information data storage requirement.
	TO cite this article:SHAN Xu,WANG Genying,LIU Lin. A platform for massive railway information data storage[OL].[ 1 July 2013] http://en.paper.edu.cn/en_releasepaper/content/4549326


	8. A Novel Method for determining the presampling modulation transfer function in digital radiography based on Wiener deconvolution technique
	Zhou Zhongxing,Zhu Qingzhen,Zhao Huijuan,Gaofeng
	Electrics, Communication and Autocontrol Technology 16 January 2013
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	Abstract:A Novel method for determining the presampling modulation transfer function (MTF) of digital radiography systems from slanted edge images was developed based on Wiener deconvolution. The supersampled degraded edge spread function (ESF) was obtained from simulated slanted edge images with known MTF in the presence of poisson noise, and its corresponding ideal ESF without degration was constructed according to its central edge position. To meet the requirements of the absolute integrable condition of Fourier transformation, the origianl ESFs were mirrored to construct the symmetric pattern of ESFs. Then based on Wiener deconvolution technique, the supersampled line spread function (LSF) could be acquired from the symmetric pattern of supersampled degraded ESFs in the presence of ideal symmetric ESFs and system noise. The MTF is then the normalized magnitude of the Fourier transform of the LSF. The determined MTF showed a strong agreement with the theoritical true MTF when appropriated Wiener parameter was chosen. The effects of Wiener parameter value and the width of square-like wave peak in symmetric ESFs were illustrated and discussed. In conclusion, an accurate and simple method to measure the presampling MTF was established using Wiener deconvolution technique according to slanted edge images.
	TO cite this article:Zhou Zhongxing,Zhu Qingzhen,Zhao Huijuan, et al. A Novel Method for determining the presampling modulation transfer function in digital radiography based on Wiener deconvolution technique[OL].[16 January 2013] http://en.paper.edu.cn/en_releasepaper/content/4511636


	9. Blind Beamforming for Noncircular Signals via Output Impropriety-Degree Maximization
	Xu Yougen,Liu Zhiwen
	Electrics, Communication and Autocontrol Technology 30 December 2008
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	Abstract:A noncircularity exploiting adaptive beamforming scheme is presented for blind recovery of a narrow-band signal with nonzero impropriety-degree (ID). By maximizing the ID of the output signal, this new second-order blind beamformer can directly extract the signal of interest from circular interferences and noise (not necessarily Gaussian) without training signal and array calibration.
	TO cite this article:Xu Yougen,Liu Zhiwen. Blind Beamforming for Noncircular Signals via Output Impropriety-Degree Maximization[OL].[30 December 2008] http://en.paper.edu.cn/en_releasepaper/content/27077


	10. A novel block-matching algorithm for motion estimation
	Ma Jidong ,Gu Zhaowei ,Qu Fuming ,Shen Gongjian ,Wang Anna
	Electrics, Communication and Autocontrol Technology 06 June 2008
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	Abstract:In order to reduce the computational complexity of the fast motion estimation and improve the performance of motion compensation, a block-matching algorithm of mixing diamond search and adaptive rood pattern search has been proposed. Combining the advantages of fixed search pattern and spatial correlation search pattern, the algorithm employs the high search accuracy of DS and the high search speed of ARPS. It performs zero motion prejudging for immobile macroblocks between the two adjacent frames to reduce the computational complexity, and employs the spatial correlation of motion vectors to improve the quality of predicted motion vectors. Compared to ARPS, experimental results show that the computational complexity could be reduced at least 60% while guaranteeing the search accuracy.
	TO cite this article:Ma Jidong ,Gu Zhaowei ,Qu Fuming , et al. A novel block-matching algorithm for motion estimation[OL].[ 6 June 2008] http://en.paper.edu.cn/en_releasepaper/content/22042

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