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Image reconstruction algorithm of compressed sensing based on neural dynamics

Journal of Information Hiding and Multimedia Signal Processing 2017年第3期8卷 623-631页

作者： Gan, Zhenhua Xiong, Baoping Zou, Fumin Liao, Lyuchao Du, Min College of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China College of Electrical Engineering and Automation Fuzhou University No.2 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China Fujian Provincial Key Laboratory of Big Data Mining and Applications No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China Key Lab of Automotive Electronics and Electric Drive Technology of Fujian Province No.3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province China

To improve the recovery performance of compressed sensing (CS) recon- struction, this paper proposed a CS reconstruction model based on neural dynamics optimization algorithm (NDOA) with l1-norm minimization, and applied it to the two- dimensional (2D) image signals to verify the reconstruction effectiveness. Experiments proved the NDOA had performed better in reconstruction than the orthogonal matching pursuit (OMP) and its improved algorithms considering its perfect recovery. When the compressed sampling rate is 0:875 for 64×64 Lena image, the application of NDOA would raise the peak signal to noise ratio (PSNR) by 3:6466dB while decrease the relative error (REOR) by 2:21% in comparison with OMP and SWOMP. It showed that the effective- ness of CS reconstruction of NDOA was evident. At the same time, the adoption of NDOA could realize real-time processing by parallel computing, which would effectively solve real-time problems such as image processing in the realm of high dimensional sparse signals. © 2017.

关键词： Compressed sensing

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Time-Series Analysis on the Impact Level upon Taiwan Stock Market with Events of Signing International Agreements 3

Time-Series Analysis on the Impact Level upon Taiwan Stock M...

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3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

作者： Tsai, Pei-Wei Lin, You-Xin Zhang, Jing Chang, Jui-Fang Chen, Jhih-Sheng Zhang, Jilin College of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Department of International Business National Kaohsiung University of Applied Sciences Kaohsiung Taiwan Department of Mathematics and Physics Fujian University of Technology Fuzhou China

ISBN: (纸本)9781509010936

Stock investment is one of the available conventional financial commodities in the investment market. The individual price of stocks including stocks in the field of industrial, medical, financial, overall, etc. Is subject to many different aspects. The relationship between aspects, the international economy, and the stock price is complex and is not easy to be categorized. Moreover, the trend of the world increases the cooperation and links between countries and different nations. Many agreements in tourism, trade, etc. Are signed between countries. In this paper, we focus on the effect on the stock prices caused by the agreements signed between Taiwan and other countries. The time series method is utilized to analyze the effect on the stock price forecasting caused by 5 of the incidents including WTO, Taiwan-Nicaragua FTA, Taiwan-Honduras FTA, and Taiwan-Japan BIA. Both the pre-event and the post-event periods are included for observing the fluctuation behavior of the stock market price. The MAPE value is used as the criterion to verify the correctness of the forecasting result. The MAPE values obtained in all experiments are all less than 10%. It implies that the time series method presents good forecasting ability in the analyzed cases. © 2016 IEEE.

关键词： Forecasting

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Comparative analysis of identification methods for wheat leaf diseases

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International Agricultural engineering Journal 2016年第3期25卷 197-203页

作者： Zhang, D.Y. Xie, X.H. Liang, D. Huang, L.S. Zhang, X.Q. Teng, L. Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Anhui Engineering Laboratory of Agro-Ecological Big Data Anhui University School of Electronic and Information Engineering Hefei Anhui230601 China

How to fast, accurately and robustly recognize wheat diseases, particularly for those diseases with mild-to-moderate severity, is a challenge for prevention and control of crop disease timely. In this study, image processing technique was applied to segment the infected regions of disease leaves. Twenty disease features were extracted, and eighteen larger weight features were selected by Relief-F algorithm to generate the models of Support Vector Machine (SVM), Relevance Vector Machine (RVM) and Back Propagation Neural Network (BPNN). Subsequently, these models were used to identify two kinds of wheat diseases, namely, wheat stripe rust and powdery mildew. Total 136 samples, including 68 training samples and 68 test samples with different infection severities were used to study the recognition capabilities of the three models. Results showed that high predictive accuracies in identification of two wheat diseases with varying severity for all three models. Overall accuracy of RVM was 89.71%, which was superior to 83.82% of SVM and inferior to 92.64% of BPNN. Meanwhile, the recognition accuracies of SVM, RVM and BPNN models for mild-to-moderate disease were 83.33%, 88.33% and 91.67%, respectively. The prediction time of RVM was less than those of SVM and BPNN, with differences as large as 7.96 and 31.68 times, respectively. Therefore, RVM appeared to be the most suitable for real-time identifying wheat leaf diseases among the three models, which can provide important technical support for wheat diseases management.

关键词： Support vector machines

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Price learning based load distribution strategies for demand response management in smart grid

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International Journal of Smart Home 2016年第11期10卷 79-94页

作者： Tang, Qiang Xie, Ming-Zhong Yang, Kun Luo, Yuan-Sheng Li, Ping Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha Hunan Province410114 China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom

In this paper, a Price learning based Load Distribution Strategy (PLDS) is proposed at first. In PLDS model, Smart Power Service, Utility Company and History Load Curves are included, and by considering both the average electricity consumption cost and the average electricity consumption habit, we proposed a convex optimization model to solve the model. In order to accelerate the convergence of PLDS, a price learning mechanism is proposed, which learns a price curve according to the history price data, and predicts price as a learned price for the next iteration. The optimization cycle of PLDS is one day or 24 hours, and in order to further improve the peak shaving performance, an extended version of PLDS named PLRS (Price learning based Load Redistribution Strategy) is proposed, whose optimization cycle length is 1 hour. The optimization models of PLDS and PLRS are the same, and the differences between them are the optimization cycle and the constraint conditions. In the simulation, we compared the convergence performance, peaking shaving performance and total cost among PLDS, PLRS and other strategy ODC in reference [11], and we found that the convergence performances of PLDS and PLRS are both better than that of ODC. The peak shaving performance of PLRS is better than that of ODC in the long term, and the total cost of PLRS is very close to that of ODC. © 2016 SERSC.

关键词： Costs

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Analysis of volatilities and correlations for chinese stock markets

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Journal of Information Hiding and Multimedia Signal Processing 2016年第5期7卷 1110-1125页

作者： Zhang, Ji Lin Lai, Yong Zeng Tsai, Pei-Wei School of Mathematics and Physics Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350108 China Department of Mathematics Wilfrid Laurier University 75 Universit Ave. E WaterlooONN2L 3C5 Canada College of Information Science and Engineering Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350108 China

In this paper, GARCH, EG ARCH and GJR models are used to fit the volatilities of stock returns for two markets in China, namely, the Shanghai Stock Exchange (SSE) and the Shenzhen Stock Exchange (SZSE) in both the developing and the developed stages. We also compare the performance of the volatilities and the leverage effects both across and within the two markets. Furthermore, we use VAR model to detect the correlation between the targeted markets based on impulse response and variance decomposition analyses. The experimental results indicate that the markets are less volatile and positively skewed in the developing phase while these are more volatile and negatively skewed in the developed phase. Another finding is that one standard-deviation innovation impulses die out after 7 days in the targeted markets and the impact of the SSE on the SZSE is stronger than that of the SZSE on the SSE. © 2016, Ubiquitous International. All Rights Reserved.

关键词： Impulse response

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Design of substation and distribution station monitoring system based on DELPHI and intelligent modules

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Journal of Information Hiding and Multimedia Signal Processing 2016年第4期7卷 818-825页

作者： Zheng, Rongjin Huang, Xiaosheng Deng, Huiqiong College of Information Science and Engineering Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province350118 China

It builds a kind of hierarchical distributed computer monitoring and control system through adding communication modules and intelligent acquisition modules without changing the primary equipment of 10 kV substation and distribution station. DELPHI is brought in the communication software which based on MODBUS-RTU protocol. And the problems of monitoring and control from distribution modules are solved. It also develops human-machine interface and realizes the monitoring of substation and distribution station. Therefore, the automation level of substation and distribution station is improved greatly. © 2016.

关键词： Monitoring

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Real-time Information Service System for the Meteorological Screen Base on CDMA

Real-time Information Service System for the Meteorological ...

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2016 International Conference on Wireless Communication and Network engineering (WCNE2016)

作者： Tai-sheng ZENG Ji-chang WEN College of Mathematics and Computer Science Quanzhu Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information Processing Fujian Province University College of Engineering Quanzhou Meteorological Bureau

Real-time Information Service System for the Meteorological Screen Base on CDMA is designed, a complete set of information gathering, processing, aggregating and publishing system for weather prediction products, disaster warning information, Typhoon real-time position information, weather information every ten minutes. Real-time weather information to the grouping of the LED display live information and notice is automatically released. The system contains user classification and display management module, disaster warning information into the module, all kinds Notice entry module, real-time weather information collected the summary module as well as real-time weather information automatically release the module.

关键词： LED CDMA Information service system

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Neighborhood collaborative classifiers

Neighborhood collaborative classifiers

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Xu, Suping Yang, Xibei Tsang, Eric C. C. Mantey, Eric A. School of Computer Science and Engineering Jiangsu University of Science and Technology Zhenjiang212003 China School of Economics and Management Nanjing University of Science and Technology Nanjing210094 China Faculty of Information Technology Macau University of Science and Technology C-Macau519020 China Intelligent Information Processing Key Laboratory of Shanxi Province Shanxi University Taiyuan030006 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Ocean University Zhoushan316022 China

ISBN: (纸本)9781509003891

In neighborhood rough set model, the majority rule based neighborhood classifier (NC) is easy to be misjudged with the increasing of the size of information granules. To remedy this deficiency, we propose a neighborhood collaborative classifier (NCC) based on the idea of collaborative representation based classification (CRC). NCC first performs feature selection with neighborhood rough set, and then instead of solving the classification problem by the majority rule, NCC solves a similar problem with collaborative representation among the neighbors of each unseen sample. Experiments on UCI data sets demonstrate that: 1) Our NCC achieves satisfactory performance in larger neighborhood information granules when compared with NC;2) NCC reduces the size of dictionary when compared with CRC. © 2016 IEEE.

关键词： Classification (of information)

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The effect in the production and Luminescence property of Zn3V2O8 with fluxing

The effect in the production and Luminescence property of Zn...

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2016 International Conference on Computer engineering,Information Science & Application Technology(ICCIA 2016)

作者： Jiaolian Luo Weifu Cen Xiaoming Zhang Shilin Yu Ruxue Chen Zhenglin Zhou Yingfu Zhang Ting Huang Special and Key Laboratory of Guizhou Provincial Higher Education for Green Energy-Saving Materials.Guizhou Minzu University College of information engineering Guizhou Minzu University College of big data and information engineering Guizhou University

ISBN: (纸本)9781510830363

The sample of Zn3V2O8 has been preparation by high temperature solid phase method with fluxing, and studied the effect of preparation condition and the luminescence property with fluxing. The results of phase studied show that the crystal morphology was improved, the reunite of grain crystal was decreased, and the effect of crystal structure was none by fluxed. The results of luminescence property shows that the emission peak was appeared at the wave-length of 400—700 nm, and the highest peak appeared at the wave-length of 550 nm under the near ultraviolet excitation light of 360 nm, the results shows that the luminescence property was improved by flux of NH4 Cl, NH4 F and H3BO3.

关键词： Zn3V2O8 High temperature solid phase synthesis technique Photo-luminescence Flux Crystal structure

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The effect in the production and Luminescence property of Zn3V2O8 with Eu-doping

The effect in the production and Luminescence property of Zn...

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2016 4th International Conference on Advanced Materials and Information Technology Processing(AMITP 2016)

作者： Jiaolian Luo Weifu Cen Xiaoming Zhang Jifeng Wang Ruxue Chen Zhenglin Zhou Yingfu Zhang Ting Huang Special and Key Laboratory of Guizhou Provincial Higher Education for Green Energy-Saving Materials.Guizhou Minzu University College of information engineering Guizhou Minzu University College of big data and information engineering Guizhou University

The ZnVO and(ZnEu)VO have been production by Solid phase method. The crystal structure, the crystal morphology and the luminescence property of ZnVO and(ZnEu)VO have been studied. The results show that the crystal structure of ZnVO and(ZnEu)VO were the same, and the particle uniformity of(ZnEu)VO was better than ZnVO. The emission band ZnVO and(ZnEu)VO were present at the wave length of 420-690 nm, the luminescence property of(ZnEu)VO was enhance by Eu-doped.

关键词： Zn3V2O8 (Zn1-xEux)3V2O8 Solid phase method Luminescence property Eu-doped

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