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parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method

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Chinese Physics B 2012年第5期21卷 113-118页

作者：李向涛殷明浩 College of Computer Science Northeast Normal University

We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization *** this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic *** algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning *** are conducted on the Lorenz system and the Chen *** proposed algorithm is used to estimate the parameters for these two *** results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.

关键词： cuckoo search algorithm chaotic system parameter estimation orthogonal learning

parameter estimation for rigid body after micro-Doppler removal based on L-statistics in the radar analysis

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Journal of Systems Engineering and Electronics 2015年第3期26卷 457-467页

作者： Yong Wang Jian Kang School of Electronics and Information Engineering Harbin Institute of Technology

In traditional inverse synthetic aperture radar （ISAR） imaging of moving targets with rotational parts, the micro-Doppler （m-D） effects caused by the rotational parts influence the quality of the radar images. Recently, L. Stankovic proposed an m-D removal method based on L-statistics, which has been proved effective and simple. The algorithm can extract the m-D effects according to different behaviors of signals induced by rotational parts and rigid bodies in time-frequency （T-F） domain. However, by removing m-D effects, some useful short time Fourier transform （STFT） samples of rigid bodies are also extracted, which induces the side lobe problem of rigid bodies. A parameter estimation method for rigid bodies after m-D removal is proposed, which can accurately re- cover rigid bodies and avoid the side lobe problem by only using m-D removal. Simulations are given to validate the effectiveness of the proposed method.

关键词： parameter estimation L-statistics micro-Doppler (m-D) radar imaging.

parameter estimation of Multiple Mono-Pulse Radar Signals Intercepted by Nyquist Folding Receiver Using Periodic Chirp Local Oscillator Based on Periodic Fractional Autocorrelation

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Chinese Journal of Electronics 2022年第1期31卷 181-189页

作者： QIU Zhaoyang LI Tingpeng WANG Yiming State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE) School of Communication Engineering Hangzhou Dianzi University School of Rail Transportation Soochow University

The frequency space of modern radar system has been extended to a wide range. To intercept the modern radar signals with high interception probability, the wideband receiving is of significance to the radar reconnaissance receiver. The Nyquist folding receiver(NYFR) is a novel ultra-wideband receiving architecture,which requires a small amount of equipment. Because the mono-pulse radar signal is widely used in radar systems,the multiple mono-pulse radar signals will be intercepted by the NYFR. The parameter estimation of multiple simultaneous arrival mono-pulse radar signals intercepted by the NYFR using periodic chirp local oscillator is considered. The definition of periodic fractional autocorrelation(PFA) is proposed. Based on the PFA, a novel fast parameter estimation method is given. The proposed estimation approach can estimate the multiple NYFR outputs under frequency aliasing condition and has low computational complexity. Simulation results show the effectiveness of the proposed method.

关键词： modern radar signals computational complexity modern radar system probability Nyquist folding receiver multiple NYFR ultra wideband communication novel fast parameter estimation method radar systems multiple mono-pulse radar signals radio receivers periodic chirp local oscillator periodic fractional autocorrelation high interception probability novel ultra-wideband receiving architecture radar signal processing signal detection radar receivers radar reconnaissance receiver parameter estimation receivers mono-pulse radar signal multiple simultaneous arrival mono-pulse radar signals

parameter estimation of DSSS signals in non-cooperative communication system

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Journal of Systems Engineering and Electronics 2007年第1期18卷 14-21页

作者： Zhang Xiaoming Zhang Zhongzhao Communication Research Center Harbin Inst. of Technology Harbin 150001 P. R. China

A new adaptive estimator for direct sequence spread spectrum （DSSS） signals using fourth-order cumulant based adaptive method is considered. The general higher-order statistics may not be easily applied in signal processing with too complex computation. Based on the fourth-order cumulant with 1-D slices and adaptive filters, an efficient algorithm is proposed to solve the problem and is extended for nonstationary stochastic processes. In order to achieve the accurate parameter estimation of direct sequence spread spectrum （DSSS） signals, the fast step uses the modified fourth-order cumulant to reduce the computing complexity. While the second step employs an adaptive recursive system to estimate the power spectrum in the frequency domain. In the case of intercepted signals without large enough data samples, the estimator provides good performance in parameter estimation and white Gaussian noise suppression. Computer simulations are included to corroborate the theoretical development with different signal-to-noise ratio conditions and recursive coefficients.

关键词： Four order cumulant parameter estimation Adaptive estimator DSSS signal

parameter estimation of continuous variable quantum key distribution system via artificial neural networks

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Chinese Physics B 2022年第2期31卷 233-241页

作者： Hao Luo Yi-Jun Wang Wei Ye Hai Zhong Yi-Yu Mao Ying Guo School of Automation Central South UniversityChangsha 410083China School of Computer Science and Engineering Central South UniversityChangsha 410083China College of Applied Science Jiangxi University of Science and TechnologyGanzhou 341000China

Continuous-variable quantum key distribution(CVQKD)allows legitimate parties to extract and exchange secret ***,the tradeoff between the secret key rate and the accuracy of parameter estimation still around the present CVQKD *** this paper,we suggest an approach for parameter estimation of the CVQKD system via artificial neural networks(ANN),which can be merged in post-processing with less additional *** ANN-based training scheme,enables key prediction without exposing any raw *** results show that the error between the predicted values and the true ones is in a reasonable *** CVQKD system can be improved in terms of the secret key rate and the parameter estimation,which involves less additional devices than the traditional CVQKD system.

关键词： quantum key distribution artificial neural networks secret key rate parameter estimation

parameter estimation of Sub-/Super-synchronous Oscillation Based on Interpolated All-phase Fast Fourier Transform with Optimized Window Function

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1031-1041页

作者： Bo Sun Xi Wu Xi Chen Zixiao Zou Qiang Li Bixing Ren School of Electrical Engineering Southeast UniversityNanjingChina State Grid Jiangsu Electric Power Company Limited Research Institute NanjingChina

In recent years,with increasing amounts of renewable energy sources connecting to power grids,sub-/super-synchronous oscillations(SSOs)occurred more *** to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has become a particularly challenging *** solve this issue,this paper proposes an improved spectrum analysis method by improving the window function and a spectrum correction method to achieve higher ***,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-convolved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO ***,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window function is proposed to estimate the parameters of *** method allows for phase-unbiased estimation while maintaining algorithmic simplicity and *** performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation *** results validate the effectiveness and superiority of the proposed method.

关键词： Sub-/Super-synchronous oscillation(SSO) window function parameter estimation interpolated all-phase fast Fourier transform(ApFFT)

parameter estimation for Hot-spot Thermal Model of Power Transformers Using Unscented Kalman Filters

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Journal of Modern Power Systems and Clean Energy 2023年第2期11卷 634-642页

作者： MiguelÁngel González-Cagigal JoséAntonio Rosendo-Macías Antonio Gómez-Expósito Department of Electrical Engineering University of SevilleSevilleSpain ENGREEN Laboratory of Engineering for Energy and Environmental Sustainability SevilleSpain

This paper presents a parameter estimation technique for the hot-spot thermal model of power *** proposed technique is based on the unscented formulation of the Kalman filter,jointly considering the state variables and parameters of the dynamic thermal model.A two-stage estimation technique that takes advantage of different loading conditions is developed,in order to increase the number of parameters which can be *** results are presented,which show that the observable parameters are estimated with an error of less than 3%.The parameter estimation procedure is mainly intended for factory testing,allowing the manufacturer to enhance the thermal model of power transformers and,therefore,its customers to increase the lifetime of these *** proposed technique could be additionally considered in field applications if the necessary temperature measurements are available.

关键词： parameter estimation power transformer unscented Kalman filter thermal model

parameter estimation for chaotic systems with and without noise using differential evolution-based method

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Chinese Physics B 2011年第6期20卷 72-77页

作者：李念强潘炜闫连山罗斌徐明峰江宁 Centre for Information Photonics and Communications Southwest Jiaotong University

We present an approach in which the differential evolution （DE） algorithm is used to address identification problems in chaotic systems with or without delay terms. Unlike existing considerations, the scheme is able to simultaneously extract （i） the commonly considered parameters, （ii） the delay, and （iii） the initial state. The main goal is to present and verify the robustness against the common white Guassian noise of the DE-based method. Results of the time-delay logistic system, the Mackey Glass system and the Lorenz system are also presented.

关键词： chaotic system differential evolution noise parameter estimation

parameter estimation of a Valve-Controlled Cylinder System Model Based on Bench Test and Operating Data Fusion

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 247-263页

作者： Deying Su Shaojie Wang Haojing Lin Xiaosong Xia Yubing Xu Liang Hou Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361102China Xuzhou XCMG Excavation Machinery Co. LtdXuzhou 221000China

The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder *** test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder *** the actual load information contained in the operating data of the control valve,its acquisition remains *** paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned *** proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating ***,a system model is established,and the parameters in the model are ***,the bench and operating data of the system are ***,the model parameters and weight coefficients are estimated using the data fusion ***,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are *** research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation *** effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO *** load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.

关键词： Valve-controlled cylinder system parameter estimation The Bayesian theory Data fusion method Weight coefficients