检索结果-南通市图书馆

Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm

在线全文

学校读者我要写书评

暂无评论

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第4期10卷 497-503页

作者： Xin LIU Guo WEI Jin-wei SUN Dan LIU Department of Automatic Measurement and Control Harbin Institute of Technology Harbin 150001 China

Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.

关键词： Least squares support vector machine Total least squares Multifunctional sensor signal reconstruction

A sparsity adaptive compressed signal reconstruction based on sensing dictionary

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2021年第6期32卷 1345-1353页

作者： SHEN Zhiyuan WANG Qianqian CHENG Xinmiao College of Civil Aviation Nanjing University of Aeronautics and AstronauticsNanjing 210016China Zhejiang Scientific Research Institute of Transport Hangzhou 310023China Civil Aviation Branch Jiangsu Transportation InstituteNanjing 210003China

signal reconstruction is a significantly important theoretical issue for compressed *** the situation of signal reconstruction with unknown sparsity,the conventional signal reconstruction algorithms usually perform low *** this work,a sparsity adaptive signal reconstruction algorithm using sensing dictionary is proposed to achieve a lower reconstruction *** sparsity estimation method is combined with the construction of the support set based on sensing *** the adaptive sparsity method,an iterative signal reconstruction algorithm is *** sufficient conditions for the exact signal reconstruction of the algorithm also is proved by *** to a series of simulations,the results show that the proposed method has higher precision compared with other state-of-the-art signal reconstruction algorithms especially in a high compression ratio scenarios.

关键词： compressed sensing signal reconstruction adaptive sparsity estimation sensing dictionary

Graph signal reconstruction from Low-Resolution Multi-Bit Observations

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第1期33卷 153-160页

作者： Zhaoting LIU Chen YU Yafeng WANG Shuchen LIU School of Communication Engineering Hangzhou Dianzi University

Low hardware cost and power consumption in information transmission, processing and storage is an urgent demand for many big data problems, in which the high-dimensional data often be modelled as graph *** paper considers the problem of recovering a smooth graph signal by using its low-resolution multi-bit quantized observations. The underlying problem is formulated as a regularized maximum-likelihood optimization and is solved via an expectation maximization scheme. With this scheme, the multi-bit graph signal recovery(MB-GSR) is efficiently implemented by using the quantized observations collected from random subsets of graph nodes. The simulation results show that increasing the sampling resolution to 2 or 3 bits per sample leads to a considerable performance improvement, while the energy consumption and implementation costs remain much lower compared to the implementation of high resolution sampling.

关键词： Quantization (signal) Costs Power demand Simulation Energy resolution signal sampling signal reconstruction

Nonuniform Three-dimensional Configuration Distributed SAR signal reconstruction Clutter Suppression

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Aeronautics 2012年第3期25卷 423-429页

作者： LIU Mei ZHANG Lei LI Chenlei School of Electronics Information Engineering Harbin Institute of TechnologyHarbin 150001China

This paper deals with the problem of clutter suppression in spaceborne distributed synthetic aperture radar （D-SAR） with nonuniform three-dimensional （3D） configuration geometry. In order to make a breakthrough of the configuration limitation of the traditional space time adaptive processing （STAP） based on uniform array and improve the inhomogeneous clutter suppres- sion performance, this paper considers signal reconstrtiction technique using array interpolation to process the D-SAR signal. An array interpolation signal reconstruction method based on pitching-partition is derived then a signal reconstruction 3D-STAP clutter suppression method applied to nonuniform 3D configuration is proposed. In particular, the proposed method is compared with conventional methods and the performance analysis is carried out based on simulations. The improvement factor （IF） for clutter suppression is imported and reported as a benchmark on the clutter suppression effect.

关键词： distributed synthetic aperture radar nonunitform 3D configuration clutter suppression signal reconstruction STAP

For LEO Satellite Networks: Intelligent Interference Sensing and signal reconstruction Based on Blind Separation Technology

在线全文

学校读者我要写书评

暂无评论

China Communications 2024年第2期21卷 85-95页

作者： Chengjie Li Lidong Zhu Zhen Zhang The Key Laboratory for Computer Systems of State Ethnic Affairs Commission School of Computer Science and Technology(Southwest Minzu University)Chengdu 610000China National Key Laboratory of Science and Technology on Communications(University of Electronic Science and Technology of China) Chengdu 610000China College of Computer Science(Sichuan University) Chengdu 610000China

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

关键词： blind source separation greedy optimization algorithm interference sensing LEO satellite communication networks signal reconstruction

Research on the signal reconstruction of the Phased Array Structural Health Monitoring Based Using the Basis Pursuit Algorithm

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2019年第2期58卷 409-420页

作者： Yajie Sun Yanqing Yuan Qi Wang Lihua Wang Enlu Li Li Qiao Jiangsu Engineering Centre of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information and Control Nanjing University of Information Science and TechnologyNanjing210044China Capability Systems Centre School of Engineering and Information TechnologyUniversity of New South WalesCanberra2600Australia

The signal processing problem has become increasingly complex and demand high acquisition system,this paper proposes a new method to reconstruct the structure phased array structural health monitoring *** method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array *** to the principles of the compressive sensing and signal processing method,non-sparse ultrasonic signals are converted to sparse signals by using sparse *** sparse coefficients are obtained by sparse decomposition of the original signal,and then the observation matrix is constructed according to the corresponding sparse ***,the original signal is reconstructed by using basis pursuit algorithm,and error analysis is carried *** research analysis shows that the signal reconstruction method can reduce the signal complexity and required the space efficiently.

关键词： Basis pursuit algorithm compressive sensing phased array signal reconstruction

Obtaining Prior Information for Ultrasonic signal reconstruction from FRI Sparse Sampling Data

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Harbin Institute of Technology(New Series) 2018年第4期25卷 65-72页

作者： Shoupeng Song Yingjie Ni Yonghua Shao Department of Instrument Science and Engineering Jiangsu University

Finite rate of innovation sampling is a novel sub-Nyquist sampling method that can reconstruct a signal from sparse sampling *** application of this method in ultrasonic testing greatly reduces the signal sampling rate and the quantity of sampling ***,the pulse number of the signal must be known beforehand for the signal reconstruction *** accuracy of this prior information directly affects the accuracy of the estimated parameters of the signal and influences the assessment of flaws,leading to a lower defect detection *** the pulse number can be pre-given by theoretical analysis,the process is still unable to assess actual complex random orientation ***,this paper proposes a new method that uses singular value decomposition(SVD) for estimating the pulse number from sparse sampling data and avoids the shortcoming of providing the pulse number in advance for signal *** the sparse sampling data have been acquired from the ultrasonic signal,these data are transformed to discrete Fourier coefficients.A Hankel matrix is then constructed from these coefficients,and SVD is performed on the *** decomposition coefficients reserve the information of the pulse *** the decomposition coefficients generated by noise according to noise level are removed,the number of the remaining decomposition coefficients is the signal pulse *** feasibility of the proposed method was verified through simulation *** applicability was tested in ultrasonic experiments by using sample flawed *** from simulations and real experiments demonstrated the efficiency of this method.

关键词： FRI ultrasonic signal sparse sampling signal reconstruction prior information

Extracting useful high-frequency information from wide-field electromagnetic data using time-domain signal reconstruction

在线全文

学校读者我要写书评

暂无评论

Journal of Central South University 2022年第11期29卷 3767-3778页

作者： LING Fan YANG Yang LI Gang ZHOU Chang-yu HUANG Min WANG Xin ZHANG Heng ZHU Yu-zhen SUN Huai-feng School of Geosciences and Info-Physics Central South UniversityChangsha 410083China Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring of Ministry of Education(Central South University) Changsha 410083China Geotechnical and Structural Engineering Research Center Shandong UniversityJinan 250000China Advanced Exploration and Transparent City Innovation Center Shandong Research Institute of Industrial TechnologyJinan 250101China Jinan Rail Transit Group Co. Ltd.Jinan 250101China Institute of Urban Underground Space and Energy Studies the Chinese University of Hong KongShenzhen 518000China Shandong Coal Geological Planning and Exploration Research Institute Jinan 250000China

The wide-field electromagnetic method is widely used in hydrocarbon exploration,mineral deposit detection,and geological disaster ***,apparent resistivity and normalized field amplitude exceeding 2048 Hz often exhibit upward warping in data,making geophysical inversion and interpretation *** cumulative error of the crystal oscillator in signal transmission and acquisition contributes to an upturned apparent resistivity *** address this,a high-frequency information extraction method is proposed based on time-domain signal reconstruction,which helps to record a complete current data sequence;moreover,it helps estimate the crystal oscillator error for the transmitted *** the recorded error,a received signal was corrected using a set of reconstruction *** processing,the high-frequency component of the wide-field electromagnetic data was not upturned,while accurate high-frequency information was extracted from the ***,the proposed method helped effectively extract high-frequency components of all wide-field electromagnetic data.

关键词： wide-field electromagnetic method crystal oscillator error time series signal resampling signal reconstruction

Comparison of signal reconstruction under different transforms

在线全文

学校读者我要写书评

暂无评论

Journal of Southeast University(English Edition) 2015年第4期31卷 474-478页

作者：刘洁媛伍家松 Lotfi Senhadji 舒华忠东南大学计算机网络与信息集成重点实验室南京210096 东南大学中法生物医学信息研究中心南京210096 法国国家医学与健康研究院 u1099法国雷恩35042 雷恩第一大学信号与图像处理实验室法国雷恩35042

A newalgorithm, called Magnitude Cut, to recover a signal from its phase in the transform domain, is ***, the recovery problem is converted to an equivalent convex optimization problem, and then it is solved by the block coordinate descent（ BCD） algorithm and the interior point algorithm. Finally, the one-dimensional and twodimensional signal reconstructions are implemented and the reconstruction results under the Fourier transform with a Gaussian random mask（ FTGM）, the Cauchy wavelets transform（ CWT）, the Fourier transform with a binary random mask（ FTBM） and the Gaussian random transform（ GRT） are also comparatively analyzed. The analysis results reveal that the M agnitude Cut method can reconstruct the original signal with the phase information of different transforms; and it needs less phase information to recover the signal from the phase of the FTGM or GRT than that of FTBM or CWT under the same reconstruction error.

关键词： MagnitudeCut algorithm signal reconstruction different transforms convex optimization phase information