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One-to-one non-linear transformation for RSS-based localization with unknown transmit power

IET COMMUNICATIONS 2021年第4期15卷 627-641页

作者： Danaee, Meysam Raees Imam Hussein Comprehens Univ Elect Engn Dept 3rd Floor 303 Tehran Iran

For most of the positioning algorithms, based on the received signal strength, the objective function of the estimator is linearized so that the conventional least square algorithm can be executed. This would necessitate using a data model containing many noisy elements which implicitly violates the least squares assumptions. To avoid this violation, an optimized data modelling would have to be set up as shown in this paper. The authors then trivially provide the solution of this new least square problem which is still a primary coarse position estimation because of ignoring the non-linear relationships existing among parameters of the estimation. To extract quantitative information from these non-linear relationships, the authors also propose two new signal space points for using Taylor-series expansion as effectively as possible in accordance of the new data model. The proposed algorithms work without any knowledge about the transmit power. The performance evaluation of the proposed idea indicates that the new suggested estimators perform significantly better than the other existing linear position estimators for a large range of noise variance and path-loss exponent values.

关键词： WSN Taylor-series expansion RSS-based localization sensor placement Optimisation techniques Signal processing and detection Wireless sensor networks optimized data modelling signal space points least square algorithm primary coarse position estimation least squares approximations positioning algorithms one-to-one nonlinear transformation wireless sensor networks Interpolation and function approximation (numerical analysis) objective function linear position estimators signal processing nonlinear relationships least square problem received signal strength

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A new physical parameter identification method for shear frame structures under limited inputs and outputs

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ADVANCES IN STRUCTURAL ENGINEERING 2021年第4期24卷 667-679页

作者： Liu, Jing-Liang Yu, An-Hua Chang, Chia-Ming Ren, Wei-Xin Zhang, Jing Fujian Agr & Forestry Univ Sch Transportat & Civil Engn Fuzhou Peoples R China Natl Taiwan Univ Dept Civil Engn Taipei Taiwan Shenzhen Univ Sch Civil & Traff Engn Nanhai Ave 3688 Shenzhen Peoples R China Hefei Univ Technol Sch Civil & Hydraul Engn Tunxi Rd 193 Hefei 230009 Peoples R China

A new physical parameter identification method with a name of EKPF-LS is proposed for shear frame structures under limited inputs and outputs by a combination of extended Kalman particle filter (EKPF) and least square (LS) algorithm. The basic principle of EKPF-LS is to establish the proposed distribution function of the particle filter through EKF-LS. In this method, EKPF is introduced to get rid of the restriction of Gaussian white noise model and reduce the linearization error caused by EKF. Meanwhile, LS is utilized to address the problem of unmeasured excitation estimations. The effectiveness and accuracy of the proposed EKPF-LS method is verified by a numerical example of a four-story hysteretic shear frame under an earthquake excitation and an experimental test of a four-story shear type frame using Gaussian white noise and sine sweep signal as excitations, respectively. Gaussian colored noises are then added to the solved and measured response signals in the numerical example and experimental test, respectively. The results demonstrate that the proposed method can identify the stiffness of shear frame structures effectively and is superior to the existed EKF-LS approach when the structural system is nonlinear structural system or Colored noise model.

关键词： extended Kalman particle filter least square algorithm physical parameter limited input and output shear frame structure

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Controlling of lower-order dead system by implementing adaptive RST algorithm

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2021年第4期39卷 272-278页

作者： Guo, Yanzhu Xian Railway Vocat & Tech Inst Xian Shaanxi Peoples R China

Since the advent of time, humankind has made numerous technological advancements. Every system built is indeed time-varying in nature as well as nonlinear, and they tend to vary with time. The dead or slow system tends to vary at a slow rate. To control such a system, we implemented an RST-based control algorithm that can track the output of the unknown system and control it with minimal error. (tau) is a quantity measured in time and it is a time-varying parameter for the lower order system, this is the parameter that will change with time and in turn change an entire system response. Previously applied control parameters might not be suitable to control the system. Therefore, this study introduces a novel mechanism that combines the least squares (LS) algorithm with RST. LS used to track the changes occurring in the system with time and thus change the control parameter to complement the changes that occurred in the system. The proposed algorithm design of a slow time-varying system is compiled and simulated in MATLAB. It is compared with the conventional PID controller and it tracks the signal faster with the same amount of work force. It shows better performance more robust and effective than the PID controller.

关键词： RST control algorithm slow time-varying system dead systems least square algorithm adaptive control self-tuning regulator

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Digital interference signal filtering on laser interface for optical fiber communication

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EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS 2023年第2期10卷

作者： Zhang, Shengnan Gadekallu, Thippa Reddy Nanchang Jiao Tong Inst Sch Transportat Nanchang 330199 Peoples R China Vellore Inst Technol Sch Informat Technol & Engn Vellore India

INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information outputOBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is ***: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be ***: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the ***: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.

关键词： digital filtering technology optical fiber communication laser interface interference signal filtering wavelet denoising least square algorithm

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SEM-Based Trust Evaluation Model and algorithm for B2C E-Commerce 17

SEM-Based Trust Evaluation Model and Algorithm for B2C E-Com...

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17th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Ren, Xiang Henan Coll Ind & Informat Technol Zhengzhou 454000 Henan Peoples R China

ISBN: (纸本)9781728186160

With the advancement of information technology and the large-scale popularization of the Internet, the promotion and application of e-commerce has greatly promoted the information communication between the supply and demand sides, significantly reduced transaction costs, and effectively improved the overall economic benefits of enterprises and their participation in domestic and foreign markets Competence. This paper aims to study the B2C e-commerce trust evaluation model and algorithm based on SEM. Experiments based on the fuzzy theory-based B2C credit evaluation model construction equation and least squares algorithm to analyze the influencing factors of trust in B2C e-commerce. Experimental data shows that consumers' distrust of online merchants, in addition to factors other than the lack of security, also accounts for a large proportion of consumers' distrust of product quality and the merchant's after-sales service attitude. The development of e-commerce is likely to be on the rise. The experimental results show that through a survey of online shopping Internet users, people's trust in Internet shopping is as follows: all are unreliable 4%, a small part is reliable 14%, half are reliable and half are unreliable 60%, and most are reliable 18%, all reliable accounted for 1%, no clear attitude accounted for 3%. This paper is based on the SEM equation theory and the B2C credit evaluation model combined with fuzzy theory. It is of great significance for analyzing the factors affecting e-commerce trust and evaluating website customer trust. Through actual proof, it is found that the algorithm we research is effective and feasible.

关键词： SEM E-Commerce Trust Evaluation Model least square algorithm

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Electrical equivalent circuit and modeling of a pulsed air corona discharge

Electrical equivalent circuit and modeling of a pulsed air c...

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International Conference on Plasma and Energy Materials (ICPEM)

作者： Saber, K. Guedah, H. Abahazem, A. Merbahi, N. Yousfi, M. Ibn Zohr Univ Phys Dept Lab Mat & Renewable Energies BP 8106 City Dakhla Agadir Morocco Paul Sabatier Univ CNRS UMR 5213 LAPLACE 118 Route NarbonneBat 3R2 F-31062 Toulouse 9 France CRMEF SM Ave Mly AbdellahBP 106 Inezgane Morocco

In this paper, we present an equivalent circuit model of a multi filamentary corona discharge powered by pulsed positive voltage in the case of humid air at atmospheric pressure. The elements of the equivalent circuit are obtained by an optimization method of parameter identification, applying the Recursive least square algorithm with a Variable Forgetting factor (RLS-VF), based on the measured currents and voltages of the discharge. A comparison between the measured discharge current and the calculated current shows a good agreement. The obtained time varying discharge resistance is between about 5-300 m Omega and the capacitance between about 0.01 pF to 1 pF. Then we used the equivalent circuit components to calculate the energy efficiency versus the applied voltage that varies at its maximum under the present experimental conditions from about 20% to 50%. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Corona discharge Pulsed voltage Humid air least square algorithm Equivalent circuit model

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A Model Predictive Control with Online inductance estimator for Three-Phase VIENNA Rectifiers 46

A Model Predictive Control with Online inductance estimator ...

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46th Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)

作者： Zhou Yunhong Zhang Aimin Zhang Hang Huang Jingjing Du Yudong Zhang Lei Zhang Wei Xi An Jiao Tong Univ Sch Elect & Informat Engn Xian Peoples R China Xi An Jiao Tong Univ Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9781728154145

A model predictive control with online inductance estimator (OIEMPC) for three-phase VIENNA rectifiers is presented in this paper. An OIE adopting the dynamic filtering method and least square algorithm is proposed to further improve system robustness. In this OIE, the VIENNA rectifier pole voltages are obtained by computation utilizing the gate signals of the switching devices, AC current direction and the DC voltage, so that no additional voltage sensors are needed. Compared to the conventional MPC with finite control set (FCS-MPC), the proposed strategy can have better control performance, which effectively improves the robustness of the system. The effectiveness and correctness of the proposed OIEMPC method are demonstrated by the results of Simulink experiments.

关键词： model predictive control least square algorithm online inductance estimator VIENNA rectifier

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Single-Channel Blind Source Separation of Two MPSK Signals Based on Stack algorithm 12

Single-Channel Blind Source Separation of Two MPSK Signals B...

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12th International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Peng, Zhongchong Li, Hui Univ Sci & Technol China Key Lab Wireless Opt Commun Chinese Acad Sci Hefei 230027 Peoples R China

ISBN: (纸本)9781728172361

In this paper, single-channel blind source separation(SCBSS) of two multiple phase shift keying(MPSK) signals based on stack-tree-searching (STS) algorithm is proposed. Unlike the conventional per-survivor processing (PSP) algorithm combining decision feedback sequence estimation (DFSE), the STS algorithm has lower complexity and even slightly better performance under the medium and high signal-noise ratio (SNR). It is found that the complexity of the STS algorithm drops fast as the SNR increases and this property also applies to oversampling cases. Simulation results show that proposed STS algorithm reduces computational complexity more than 80% of PSP algorithm when SNR is 17dB for QPSK modulation, in twice oversampling mode. When channel impulse response(CIR) estimation is not perfect, STS algorithm performs the rapid convergence with suitable initialization by least mean square(LMS) and least square(LS) algorithm. Meanwhile, the proposed algorithm is effective for separating mixed signals with its two 8PSK signals.

关键词： stack-tree-searching MPSK single-channel blind separation least square algorithm

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A Method of Mining Truck Loading Volume Detection Based on Deep Learning and Image Recognition

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SENSORS 2021年第2期21卷 635-635页

作者： Sun, Xiaoyu Li, Xuerao Xiao, Dong Chen, Yu Wang, Baohua Northeastern Univ Sch Resources & Civil Engn Shenyang 110004 Peoples R China Northeastern Univ Informat Sci & Engn Sch Shenyang 110004 Peoples R China

Detection of the loading volume of mining trucks is an important task in open pit mining. Aiming at the addressing the current problems of low accuracy and high cost of the detection of the loading volume of mining trucks, this paper proposes a mining truck loading volume detection model based on deep learning and image recognition. The training and test data of the model consists of 6000 sets of images taken in a laboratory environment. After image preprocessing, the VGG16 network model is used to pre classify the ore images. The classification results are displayed and the possibility of each category is determined. Then, the loading volume of mining trucks is calculated by using the classification results and the least squares algorithm. By using the labeled image data of five kinds of mining truck loading volume, the arbitrary loading volume detection of mining trucks is realized, which effectively solves the problem of a lack of labeled data types caused by the difficulty in obtaining mine data. Root mean square error (RMSE) and mean absolute error (MAE) are used to evaluate the fitting effect of the model. The experimental results show that the model has high prediction accuracy. The average absolute error is 17.85 cm3. In addition, this paper uses 400 real mining truck images of open-pit mines to verify the model and the average absolute error is 2.53 m3. The experimental results show that the model has good generality and can be applied well to the actual production of open-pit mines.

关键词： open pit mine loading volume image recognition VGG16 least square algorithm

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A New and Fast Method for On-line Estimation of d and q Axes Inductances of Interior Permanent Magnet Synchronous Machines Using Measurements of Current Derivatives and Inverter DC-Bus Voltage

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第10期66卷 7488-7497页

作者： Bui, Minh Xuan Rahman, M. Faz Guan, Deqi Xiao, Dan Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

This paper proposes a novel on-line technique for estimation of the inductances of an interior permanent magnet synchronous machine (IPMSM) based on the measurement of dc-bus voltage of the inverter and the stator current derivatives at certain voltage vectors during each pulsewidth modulation (PWM) cycle. This technique removes the requirement for the bulky and expensive shaft-locking mechanisms and test signal injection for obtaining the machine dq inductance parameters off line. It also overcomes the problems associated with other recursive on-line techniques which take a number of PWM cycles to update the parameters. The proposed method estimates the d and q axes inductances of IPMSMs within each PWM cycle without requiring knowledge of stator resistance, rotor flux linkage, and rotor speed. It also tracks the variations of the inductances (especially the q-axis inductance), which vary significantly due to q-axis magnetic saturation and cross saturation effect of the IPMSM, with sufficient accuracy. This paper presents full analysis, system simulation, and extensive experimental studies in order to verify the accuracy, quick tracking ability, and robustness of the proposed method.

关键词： Current derivative measurement interior permanent magnet synchronous machine (IPMSM) least square algorithm on-line inductance estimation SVPWM

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