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IEEE International Conference on Mechatronics and Automation

作者： Sun, Xiaofang Minjiang Coll Dept Geog Fuzhou 350121 Fujian Peoples R China

ISBN: (纸本)9781509023967

In the paper, it is proposed that multi-spectral image pure pixel is utilized for completing SAM classification. The classified samples are utilized for electively constructing sparse dictionary, thereby improving the representativeness of the dictionary. Eight surface feature types are set in Landsat8 image. PPI index is used for calculating pure pixel index of each pixel. Pure pixel of each surface feature is further extracted through N-D visualizer, which is used for SAM calculation. Eight kinds of surface feature samples are selected from SAM image for online dictionary learning. Multi-spectral image sparse dictionary is generated. Multi-spectral image sparse coefficient is calculated through dictionary and omp. Meanwhile, online dictionary and omp are utilized for obtaining panchromatic image sparse coefficient. Fusion sparse coefficient is generated by maximum values both sparse coefficients. Multi- spectral image sparse dictionary is combined for reconstructing and generating fusion image. Eight quantitative fusion evaluation indicators are adopted for comparing algorithm fusion and weighted fusion in the paper. Fusion method proposed in the paper contains more information, fusion image texture detail information is improved, and better image multi-spectral information is kept.

关键词： Sparse dictionary Online dictionary learning algorithm omp algorithm SAM

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Weak chatter detection in milling based on sparse dictionary 48th

Weak chatter detection in milling based on sparse dictionary

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48th SME North American Manufacturing Research Conference (NAMRC)

作者： Wang, Chenxi Zhang, Xingwu Chen, Xuefeng Yan, Ruqiang Wang, Peng Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xianning West Rd 28 Xian 710049 Peoples R China Univ Kentucky Dept Elect & Comp Engn Dept Mech Engn Lexington KY 40506 USA

As one of the most unfavorable factors in milling, chatter will lead to poor surface quality, low production efficiency and tool life reduction. Chatter detection, especially weak chatter detection, is an effective way to ensure stable cutting. In this work, the milling dynamic responses based weak chatter detection method is put forward using sparse dictionary. Based on the milling dynamic equations, chatter frequencies are calculated and verified, which are the bases for chatter detection. With the calculated chatter frequencies, the sparse dictionary matrix can be constructed and the orthogonal matching pursuit (omp) algorithm is adopted for chatter frequencies reconstruction. The proposed method can extract weak chatter frequencies accurately. Experimental results shows that the proposed method can be successful in weak chatter identification. (c) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Scientific Committee of the NAMRI/SME.

关键词： Weak chatter dentification Milling Sparse dictionary omp algorithm

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A Method of Seabed Soil Image Reconstruction Based on Compressed Sensing

A Method of Seabed Soil Image Reconstruction Based on Compre...

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International Conference on Emerging Materials and Mechanics Applications (ICEMMA 2012)

作者： Xu ZhiJing Jiang Li Dai HuanLei Shanghai Maritime Univ Coll Informat Engn Shanghai Peoples R China

ISBN: (纸本)9783037853788

Compressed Sensing(CS) can project a high dimensional signal to a low dimensional signal by a random measurement matrix. As the projection calculation is time-consuming in the process of reconstruction, the reconstruction speed is greatly affected. In order to improve the reconstruction speed, some improvement in the selection of the measurement matrix and the design of the reconstruction algorithm is made. The wavelet transform is used to sparse decompose the image, and the very sparse random projection matrix is used as the measurement matrix, after the image block processing we use the omp algorithm to reconstruct the image. The experimental result shows that this method could reduce the algorithm time and improved the reconstruction speed greatly.

关键词： compressed sensing signal reconstruction random projection omp algorithm

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Recovery of Temperature Measuring Points Based on Compressed Sensing 15

Recovery of Temperature Measuring Points Based on Compressed...

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15th IEEE International Conference on Networking, Sensing and Control (ICNSC)

作者： Jiang, Xuemei Xu, Ya Zhang, Xiaomei Yan, Junwei Hui, Jiwei Lou, Ping WUT Sch Informat Engn Wuhan 430070 Hubei Peoples R China WUT Minist Educ Key Lab Fibre Opt Sensing Technol & Informat Proc Wuhan 430070 Hubei Peoples R China

ISBN: (纸本)9781538650530

In the process of on-line monitoring the temperature measuring points of CNC machine tools, the sensing data are usually missing or abnormal because of sensor or transmission failure. To recover the abnormal temperature measuring points, a recovery method based on compressed sensing is proposed. The method uses K-SVD algorithm to carry out dictionary learning with the large amount of temperature monitoring data to obtain the over-complete dictionary, and then the mutual coherence is used to constructs the observation matrix that is suitable for the data type. Finally the omp algorithm is used to realize the recovery of the temperature measuring points. In this paper, the method is applied to the recovery of spindle temperature measuring points of heavy CNC machine tools. Experiments under different working conditions show that the method can achieve good recovery results.

关键词： compressed sensing recovery of temperature measuring points K-SVD algorithm omp algorithm

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Improved SVD algorithm for DOA Estimation of Coherent Signal Sources 36

Improved SVD Algorithm for DOA Estimation of Coherent Signal...

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第36届中国控制会议

作者： Ji Zheng-yan Chen Hui Zhang Jia-jia Key Research Laboratory Air Force Early Warning Academy

ISBN: (纸本)9781538629185

In order to solve the coherent problem of Orthogonally Matched(omp) Pursuit algorithm in sparse reconstruction,the feature vector corresponding to large eigenvalue of SVD is constructed by using received data,and two improved methods are *** methods reconstruct the angle through the feature vector,and can reconstruct the angle information accurately without knowingthe number of the signal *** with the classical omp algorithm,the operation speed is faster and the sparse reconstruction effect is *** analysis and simulation results verify the good performance of the algorithm.

关键词： omp algorithm Coherent signal source SVD algorithm

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Comparative Performance Analysis of omp and SABMP for Massive MIMO OFDM Channel Estimation 5

Comparative Performance Analysis of OMP and SABMP for Massiv...

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5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)

作者： Rao, K. Deergha Kartheek, B. K. Osmania Univ Vasavi Coll Engn Dept ECE Hyderabad Telangana India

ISBN: (纸本)9781538650028

The orthogonal matching pursuit (omp) algorithm and Support Agnostic Bayesian matching pursuit (SABMP) algorithm for sparse channel estimation are reported in the literature. In this paper, the performance of these algorithms is analyzed for massive MIMO OFDM channel estimation. The greedy approach based SABMP algorithm orders its metric updates recursively to determine pre dominant sparsesupports to find MMSE estimate. Simulations are carried out to evaluate the normalized mean square error(NMSE) of omp and SAMP for 5x5 MIMO with 32 pilot carriers. Further, the NMSE performance of SABMP algorithm is demonstrated for antenna arrays of size(5 x 5, 10 x 10, 20x20) with 16 pilot carriers and varying sparsities (3,7), and QAMs (4,16).

关键词： compressed sensing sparse reconstruction massive MIMO OFDM omp algorithm SABMP algorithm

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Performance Evaluation of a Millimeter Wave MIMO Hybrid Beamforming System

Performance Evaluation of a Millimeter Wave MIMO Hybrid Beam...

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IEEE Latin-American Conference on Communications (LATINCOM)

作者： Jain, Swarnima Markan, Anhad Markan, C. M. Dayalbagh Educ Inst Dept Phys & Comp Sci Agra Uttar Pradesh India Dayalbagh Educ Inst Dept Elect Engn Agra Uttar Pradesh India

ISBN: (纸本)9781728189031

Massive MIMO (multiple-input-multiple-output) technology along with beamforming has become the mainstream feature in 5G physical layer technologies to provide high increase in spectral efficiency and to combat the high propagation loss at high frequencies. Unlike conventional MIMO systems where all the signal processing is carried out in the digital domain, Hybrid Analog-Digital (HAD) signal processing or hybrid beamforming has the potential to reduce cost and power consumption. In this paper, a novel hybrid beamforming architecture based on the orthogonal matching pursuit (omp) algorithm is exploited for a single-user system in which massive antenna array is operated by a limited number of transmit and receive RF chains. A simulation model is studied for performance of the hybrid beamformer compared to conventional digital beamformer of the proposed system. Results show spectral efficiency as performance metric which shows near optimal efficiency using hybrid beamforming weights compared to the digital weights.

关键词： Massive MIMO Hybrid beamforming omp algorithm Spectral Efficiency

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A new mathematics method for structural health monitoring's damage detection based on WSNs 1

A new mathematics method for structural health monitoring's ...

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1st International Conference on Computational Intelligence Theory, Systems and Applications (CCITSA)

作者： Ji, Sai Yang, Ping Sun, Yajie Shen, Jian Wang, Jin Nanjing Univ Informat Sci & Technol Educ Minist Demonstrat Base Internet Applicat Inn Nanjing Jiangsu Peoples R China Yangzhou Univ Sch Informat Engn Yangzhou Jiangsu Peoples R China

ISBN: (纸本)9781467386005

In the Wireless Sensor Network (WSN) for structural health monitoring (SHM), usually, we transmit the original acquisition data and exchange the large amounts of data between nodes which consume huge energy, occupy a large amount of communication bandwidth. Thus, data compression or data fusion to reduce network traffic and energy loss before transmission is necessary. In this work, we established a suitability compressive sensing (CS) to address some challenges in the Aviation Aluminum Plate Structural Health Monitoring System (AAPSHM) using WSN. Through the experimental demonstration, the application of this method could ensure the accuracy of the data as well as balance the network energy consumption. And it can also reduce the cost of data storage and transmission, improve the efficiency and make a certain contribution to the quality for the AAPSHM.

关键词： compressive sensing structural health monitoring data compression the measurement matrix omp algorithm AAPSHM

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Wideband Spectrum Sensing Using Modulated Wideband Converter and Data Reduction Invariant algorithms

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SENSORS 2023年第4期23卷 2263-2263页

作者： Burel, Gilles Radoi, Emanuel Gautier, Roland Le Jeune, Denis Univ Brest CNRS Lab STICC CS 93837 6 Ave Gorgeu F-29238 Brest 3 France ENSTA Bretagne CNRS Lab STICC 2 Rue Francois Verny F-29806 Brest 9 France

Wideband spectrum sensing is a challenging problem in the framework of cognitive radio and spectrum surveillance, mainly because of the high sampling rates required by standard approaches. In this paper, a compressed sensing approach was considered to solve this problem, relying on a sub-Nyquist or Xsampling scheme, known as a modulated wideband converter. First, the data reduction at its output is performed in order to enable a highly effective processing scheme for spectrum reconstruction. The impact of this data transformation on the behavior of the most popular sparse reconstruction algorithms is then analyzed. A new mathematical approach is proposed to demonstrate that greedy reconstruction algorithms, such as Orthogonal Matching Pursuit, are invariant with respect to the proposed data reduction. Relying on the same formalism, a data reduction invariant version of the LASSO (least absolute shrinkage and selection operator) reconstruction algorithm was also introduced. It is finally demonstrated that the proposed algorithm provides good reconstruction results in a wideband spectrum sensing scenario, using both synthetic and measured data.

关键词： Xsampling modulated wideband converter compressed sensing data reduction omp algorithm LASSO algorithm wideband spectrum sensing

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Real Micro-Doppler Parameters Extraction of Spinning Targets Based on Rotating Interference Antenna

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REMOTE SENSING 2022年第21期14卷 5300-5300页

作者： Wang, Zhihao Chen, Yijun Yuan, Hang Luo, Ying Zhang, Qun Air Force Engn Univ Informat & Nav Coll Xian 710077 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Engn Univ PAP Coll Informat Engn Xian 710086 Peoples R China

Micro-Doppler is a unique characteristic of targets with micro-motions, which can provide significant information for target classification and recognition. However, the monostatic radar has the shortcoming of only obtaining the radial micro-motion characteristics. Although the vortex-electromagnetic-wave-based radar has the potential to obtain real micro-motion parameters, it has a high dependence on the mode number and purity of the orbital angular momentum, which greatly restricts its application in the micro-motion parameter extraction. To overcome the above problems, a new radar configuration based on the rotating interference antenna is proposed in this paper. Through the interference processing of the micro-Doppler curves of the rotating and fixed antenna, the curves containing the real micro-motion information of the target can be obtained. Then the real micro-motion characteristics of the spinning target can be reconstructed by the orthogonal matching pursuit algorithm. The effectiveness and robustness of the proposed method are validated by simulations.

关键词： rotating interference antenna spinning targets micro-Doppler parameters extraction omp algorithm

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