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Improved hybrid algorithm of indoor wireless localization based on RSSI for wireless sensor networks

Journal of Computational Information Systems 2013年第9期9卷 3707-3714页

作者： Zhu, Jun Gao, Hui Ma, Shuai Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

Due to the complexity of indoor wireless environment, indoor position is more difficult than other location technologies in wireless sensor network, and how to improve accuracy of location is one of the key research problems. So a new hybrid algorithm based on RSSI (Received signal Strength Indicator) is proposed. In this algorithm, a dynamic real-time method of solving path fading factor is introduced, which improves accuracy of RSSI ranging obviously;then a modified algorithm based on weighted centric algorithm is used, which improves accuracy of location estimation. Simulation results show that the hybrid algorithm has better performance compared with weighted centric algorithm and least square method algorithm. The proposed hybrid algorithm can achieve obviously higher localization accuracy and better error performances. © 2013 by Binary Information Press.

关键词： Wireless sensor networks

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Economic development prediction based on wavelet LSSVM algorithm

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Journal of Computational Information Systems 2013年第13期9卷 5197-5204页

作者： Li, Ping Zhang, Yu Wang, Jie Li, Weiming Ding, Dawei Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

This paper is to predict economic development based on wavelet least squares support vector machine algorithm. The same as support vector machine, least squares support vector machine employs the principle of structure risk minimization, which has better generalization ability compared with SVM. In the study, wavelet kernel function can be used to create the kernel function of least squares support vector machine. In order to testify the effective of wavelet least squares support vector machine for economic development prediction, the comparison of the prediction error among the three prediction methods: wavelet least squares support vector machine, least squares support vector machine and support vector machine is performed. Obviously, the prediction error of wavelet least squares support vector machine for economic development is smaller than other prediction models. Therefore, we can conclude that the prediction ability of wavelet least squares support vector machine for economic development is better than least squares support vector machine and support vector machine. © 2013 by Binary Information Press.

关键词： Support vector machines

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Improving whisper intelligibility in noise environment based on joint time frequency analysis

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Information Technology Journal 2013年第6期12卷 1089-1097页

作者： Zhou, Jian Wang, Huabin Fang, Xianyong Tao, Liang Zhao, Li Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Heifei 230601 China Key Laboratory of Underwater Acoustic Signal Processing Ministry of Education Southeast University Nanjing 210096 China

A whisper intelligibility enhancement method was proposed based on the Real-valued Discrete Gabor Transform (RDGT) in the joint time frequency domain where the RDGT can change the density of the spectrum through the over sample rate parameter. An optimal logarithmic spectrum estimator was derived based on RDGT coefficients. Experimental results showed that the proposed method improved the intelligibility of enhanced whisper in an adverse noise environment when using a proper over sample rate value. The largest gains in intelligibility were got when the over sample rate value is set to 16 or 32. The proposed method outperforms other four speech enhancement algorithms in terms of intelligibility improvement. The experimental results also implied that the intelligibility performance of the conventional speech enhancement algorithms might be improved when increasing the density of the time-frequency spectrum properly. © 2013 Asian Network for Scientific Information.

关键词： Frequency domain analysis

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Robust point pattern matching based on spectral context

Robust point pattern matching based on spectral context

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作者： Tang, Jun Shao, Ling Zhen, Xiantong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Huangshan Road Hefei 230039 China College of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing 210044 China Department of Electronic and Electrical Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom

Finding correspondences between two related feature point sets is a basic task in computer vision and pattern recognition. In this paper, we present a novel method for point pattern matching via spectral graph analysis. In particular, we aim to render the spectral matching algorithm more robust for positional jitter and outlier. A local structural descriptor, namely the spectral context, is proposed to describe the attribute domain of point sets, which is fundamentally different from the previous methods. Furthermore, the approximate distance order is defined and employed as the metric for geometric consistency of neighboring points in this work. By combining these two novel ingredients, we formulate feature point set matching as an optimization problem with one-to-one constraints. The correspondences are then obtained by maximizing the given objective function via the technique of probabilistic relaxation. Comparative experiments conducted on both synthetic and real data demonstrate the effectiveness of the proposed method, especially in the presence of positional jitter and outliers. © 2013 Elsevier Ltd. All rights reserved.

关键词： Jitter

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Remote sensing identification of shrub encroachment in grassland in Inner Mongolia

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2014年第11期30卷 152-158页

作者： Dong, Zhou Zhao, Xia Liang, Dong Huang, Wenjiang Peng, Dailiang Huang, Linsheng Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Electronic and Information Engineering Anhui University Hefei 230039 China Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100094 China State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences Beijing 100093 China

Shrub encroachment has been a wide phenomenon across the arid and semi-arid grasslands in Inner Mongolia, China. Although numerous studies have investigated the effect of this phenomenon on community composition, ecosystem structure, and nutrient cycling, reports on the distribution patterns of shrub encroachment are limited. A recent development in satellite remote sensing enables accurate assessment of shrub distribution and its dynamics at large scales. In this paper, the combined ground survey in Xianghuangqi, four satellite images (with spatial resolution of 5.8 m) of ZY-3, covering nearly the whole area and taken between July and August in 2013, were used to identify the shrub distribution in this region. It should be noted that the shrub here indicated the shrub-grass mosaic due to the mixed pixel effect, and the identification was weak when the coverage of shrub was on low levels. The NDVI threshold method was first used to extract the vegetation coverage area, and then three traditional pixel-oriented methods (Support vector machine, Maximum likelihood and Mahalanobis distance), compared with the object-oriented method, were used for the classification of images. Object-oriented method is different from the traditional one, in that the classification is not based on the spectral characteristics of individual pixel, but relies on the image object with spatial texture and shape and size characteristics. Ground survey data were used to compare the accuracy level of these methods. It indicated that the shrub recognition accuracy by using support vector machine algorithm is the highest among the three pixel-oriented methods, with higher producer accuracy and user accuracy than the other two algorithms. Furthermore, the overall classification accuracy of this algorithm is 81.15% higher than that of the maximum likelihood (73.33%) and the Mahalanobis distance (61.77%). However, the overall recognition accuracy by using the object-oriented approach (combined scale

关键词： Maximum likelihood

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Strain Sensing: Graphene Reinforced Carbon Nanotube Networks for Wearable Strain Sensors (Adv. Funct. Mater. 13/2016)

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Advanced Functional Materials 2016年第13期26卷

作者： Jidong Shi Xinming Li Huanyu Cheng Zhuangjian Liu Lingyu Zhao Tingting Yang Zhaohe Dai Zengguang Cheng Enzheng Shi Long Yang Zhong Zhang Anyuan Cao Hongwei Zhu Ying Fang National Center for Nanoscience and Technology Beijing 100190 P. R. China Department of Engineering Science and Mechanics Materials Research Institute The Pennsylvania State University University Park PA 16802 USA Institute of High Performance Computing 1 Fusionopolis Way #16‐16 Connexis A*Star Singapore 138632 Singapore State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 P. R. China Department of Materials Science and Engineering College of Engineering Peking University Beijing 100871 P. R. China CAS Center for Excellence in Brain Science and Intelligence Technology 320 Yue Yang Road Shanghai 200031 P. R. China

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Informative gene selection using the Algebraic Connectivity Strength of Point and Scoring Criteria

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Chinese Science Bulletin 2013年第6期58卷 657-661页

作者： WANG Nian SU LiangLiang TANG Jun YE AiXia Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University School of Electronics and Information Engineering Anhui University

This paper presents a novel method that integrates the Algebraic Connectivity Strength of Point(ACSP) and Scoring Criteria to identify genes associated with tumor ***,for each gene,the ACSP is used to identify reliable expression levels of the gene in all the *** informative genes are then selected using Scoring Criteria based on these reliable expression ***,the Support Vector Machine(SVM) classifier is used to classify the two datasets of gene expression *** results show that the informative genes selected by the proposed method have higher credibility than those selected by Scoring Criteria alone.

关键词：基因选择评分标准信息化强度连通代数基因表达谱支持向量机

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The Low-Power and Long-Distance System Based on Wireless Sensor Networks

The Low-Power and Long-Distance System Based on Wireless Sen...

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IEEE International Symposium on Dependable, Autonomic and Secure computing (DASC)

作者： Liang Liu Yanjun Hu Hua Qian Xuming Pei Key laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei P.R. China CAS Shanghai Research Center for Wireless Communications SIMIT Shanghai P.R. China

With the developing of low-power wireless techniques such as the micro-sensors, analog and digital electronic technology and radio frequency technology, different kinds of wireless sensor networks are widely used in the field of military, civil, medical and so on. However, in practical applications, the low-power consumption and long-distance have not been well achieved in the wireless sensor networks. In this paper, a low-power and long-distance system based on wireless sensor networks is proposed. The system model consists of two parts: the hardware includes server node, client nodes and ARM boards. The software mainly handle the analysis and construction of the communication frame as well as data analysis and processing and then the data information is processed to report to the server. We can reduce the energy consumption and increase the transmission distance by the combined application of hardware and software. The system can be used in different occasions and does have a grand application prospect.

关键词： Wireless sensor networks Hardware Universal Serial Bus Wireless communication Web servers

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Characterizing strong light-atom interaction by a self-consistent solution to Maxwell-Schrödinger equations

Characterizing strong light-atom interaction by a self-consi...

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USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)

作者： Jing Shen Wei E. I. Sha Xianliang Wu Department of Physics and Electronic Engineering Hefei Normal University Hefei China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

Summary form only given. Strong light-atom interaction is at the heart of atomic, molecular and optical physics; and is also important to quantum optics, quantum computing, nuclear magnetic resonance and laser. When an atom (or two-level system) is illuminated by a coherent beam of photons, it will cyclically absorb photons and re-emit them by stimulated emission, which is called Rabi oscillation. Here we developed a semiclassical framework to model the phenomenon via a self-consistent solution to Maxwell-Schrödinger equations. Different from Maxwell-Bloch equations, the wave function of the atom replacing for the density matrix nonlinearly interacts with the magnetic vector potential under coulomb gauge condition. A well-posed time evolution system derived from light-atom Hamiltonian is numerically solved by finite-difference time-domain method. The developed semiclassical Maxwell-Schrödinger framework could be generalized to model light-exciton interaction in semiconductor nanostructures.

关键词： Mathematical model Equations Educational institutions Vectors Physics Roads Atom optics

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Multi-Gabor Expansion and its fast algorithms based auxiliary biorthogonal function

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Journal of Computational Information Systems 2013年第4期9卷 1649-1657页

作者： Hu, Xueyou Li, Rui Tao, Liang Department of Electronics and Electrical Engineering Hefei University Hefei 230601 China Key Lab of Intelligence Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

Due to the uncertainty principle, the traditional single window based discrete Gabor transform has a fixed joint time-frequency resolution. In order to improve the joint time-frequency resolution of the traditional discrete Gabor transform, most researchers have proposed the discrete multi-Gabor transform based on frame theory which can improve the frequency resolution of the discrete Gabor transform, but the computational complexity limits its practical application. In this paper, a fast algorithm to computing the analysis window of real discrete Gabor transforms based on multi-Gaussian window which can simplify the calculation process of the discrete Gabor transforms is present and a discrete Multi-Gabor Expansion (DMGE) based on original biorthogonal function is given. The computational load of the proposed algorithm is far less than the discrete multi-Gabor algorithms. By choosing appropriate multi-windows, the expansion can be used to analyze the narrow- and wide-band components of mixed signal. Experimental results show the effectiveness of the proposed algorithms. Copyright © 2013 Binary Information Press.

关键词： Expansion

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