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Stochastic Iterative Learning Control With Faded Signals 预览
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作者 Ganggui Qu Dong Shen 《自动化学报:英文版》 CSCD 2019年第5期1196-1208,共13页
Stochastic iterative learning control(ILC) is designed for solving the tracking problem of stochastic linear systems through fading channels. Consequently, the signals used in learning control algorithms are faded in ... Stochastic iterative learning control(ILC) is designed for solving the tracking problem of stochastic linear systems through fading channels. Consequently, the signals used in learning control algorithms are faded in the sense that a random variable is multiplied by the original signal. To achieve the tracking objective, a two-dimensional Kalman filtering method is used in this study to derive a learning gain matrix varying along both time and iteration axes. The learning gain matrix minimizes the trace of input error covariance. The asymptotic convergence of the generated input sequence to the desired input value is strictly proved in the mean-square sense. Both output and input fading are accounted for separately in turn, followed by a general formulation that both input and output fading coexists.Illustrative examples are provided to verify the effectiveness of the proposed schemes. 展开更多
关键词 FADING channels ITERATIVE learning control (ILC) KALMAN filtering mean-square convergence STOCHASTIC systems
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An effective framework for asynchronous incremental graph processing
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作者 Xinqiao LV Wei XIAO +3 位作者 Yu ZHANG Xiaofei LIAO Hai JIN Qiangsheng HUA 《中国计算机科学前沿:英文版》 SCIE EI CSCD 2019年第3期539-551,共13页
Although many graph processing systems have been proposed, graphs in the real-world are often dynamic. It is important to keep the results of graph computation up-todate. Incremental computation is demonstrated to be ... Although many graph processing systems have been proposed, graphs in the real-world are often dynamic. It is important to keep the results of graph computation up-todate. Incremental computation is demonstrated to be an efficient solution to update calculated results. Recently, many incremental graph processing systems have been proposed to handle dynamic graphs in an asynchronous way and are able to achieve better performance than those processed in a synchronous way. However, these solutions still suffer from sub-optimal convergence speed due to their slow propagation of important vertex state (important to convergence speed) and poor locality. In order to solve these problems, we propose a novel graph processing framework. It introduces a dynamic partition method to gather the important vertices for high locality, and then uses a priority-based scheduling algorithm to assign them with a higher priority for an effective processing order. By such means, it is able to reduce the number of updates and increase the locality, thereby reducing the convergence time. Experimental results show that our method reduces the number of updates by 30%, and reduces the total execution time by 35%, compared with state-of-the-art systems. 展开更多
关键词 INCREMENTAL COMPUTATION GRAPH processing ITERATIVE COMPUTATION ASYNCHRONOUS CONVERGENCE
Closed-Loop Iterative Learning Control for Discrete Singular Systems with Fixed Initial Shift
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作者 GU Panpan TIAN Senping LIU Qian 《系统科学与复杂性学报:英文版》 SCIE EI CSCD 2019年第2期577-587,共11页
This paper deals with the problem of iterative learning control for a class of discrete singular systems with fixed initial shift. According to the characteristics of the discrete singular systems, a closed-loop learn... This paper deals with the problem of iterative learning control for a class of discrete singular systems with fixed initial shift. According to the characteristics of the discrete singular systems, a closed-loop learning algorithm is proposed and the corresponding state limiting trajectory is presented.It is shown that the algorithm can guarantee that the system state converges uniformly to the state limiting trajectory on the whole time interval. Then the initial rectifying strategy is introduced to the discrete singular systems for eliminating the effect of the fixed initial shift. Under the action of the initial rectifying strategy, the system state can converge to the desired state trajectory within the pre-specified finite time interval no matter what value the fixed initial shift takes. Finally, a numerical example is given to illustrate the effectiveness of the proposed approach. 展开更多
关键词 CLOSED-LOOP LEARNING algorithm discrete singular systems fixed INITIAL SHIFT ITERATIVE LEARNING control
Force tracking impedance control with unknown environment via an iterative learning algorithm
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作者 Xiuquan LIANG Huan ZHAO +1 位作者 Xiangfei LI Han DING 《中国科学:信息科学(英文版)》 SCIE EI CSCD 2019年第5期47-49,共3页
Dear editor,Force tracking control is important for constrained operations. In recent years, impedance control is garnering increasing attention in robot force control. A new two-phase impedance function through null ... Dear editor,Force tracking control is important for constrained operations. In recent years, impedance control is garnering increasing attention in robot force control. A new two-phase impedance function through null stiffness in an original impedance equation to satisfy zero-force tracking error for any environment was presented in (1, 2)Further improvement was performed in (3)。 展开更多
关键词 Force TRACKING IMPEDANCE control with UNKNOWN environment VIA AN ITERATIVE learning algorithm
基于RBF神经网络的非线性迭代预测控制 被引量:1
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作者 姜雪莹 陶文华 +2 位作者 施惠元 苏成利 郭颖 《控制工程》 CSCD 北大核心 2019年第3期454-460,共7页
针对工业过程中具有复杂、强非线性的被控对象,提出一种基于RBF神经网络的非线性迭代预测控制算法。该算法采用RBF神经网络建立非线性系统过程模型,将该模型作为预测模型。同时为了避免对每个采样时刻进行线性化时会丢失系统的一些信息... 针对工业过程中具有复杂、强非线性的被控对象,提出一种基于RBF神经网络的非线性迭代预测控制算法。该算法采用RBF神经网络建立非线性系统过程模型,将该模型作为预测模型。同时为了避免对每个采样时刻进行线性化时会丢失系统的一些信息,因此采用多元泰勒展开和内部迭代方法,将迭代输出的预测值沿着输入轨迹展开,从而将求解复杂的非线性优化问题转化为求解简单的二次规划问题,解决了在线实时求解控制律时非线性方程的困难,最终直接递推出预测控制律的解析式。CSTR过程的仿真对比结果表明了该算法具有很强的跟踪和抗干扰能力。 展开更多
关键词 RBF神经网络 预测控制 迭代 CSTR
Boundary condition modelling and identification for cantilever-like structures using natural frequencies
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作者 Wei LIU Zhichun YANG +1 位作者 Le WANG Ning GUO 《中国航空学报:英文版》 SCIE EI CAS CSCD 2019年第6期1451-1464,共14页
The actual boundary conditions of cantilever-like structures might be non-ideally clamped in engineering practice, and they can also vary with time due to damage or aging. Precise modelling of boundary conditions, in ... The actual boundary conditions of cantilever-like structures might be non-ideally clamped in engineering practice, and they can also vary with time due to damage or aging. Precise modelling of boundary conditions, in which both the boundary stiffness and the boundary mass should be modelled correctly, might be one of the most significant aspects in dynamic analysis and testing for such structures. However, only the boundary stiffness was considered in the most existing methods. In this paper, a boundary condition modelling and identification method for cantilever-like structures is proposed to precisely model both the boundary stiffness and the boundary mass using sensitivity analysis of natural frequencies. The boundary conditions of a cantilever-like structure can be parameterized by constant mass, constant rotational inertia,constant translational stiffness, and constant rotational stiffness. The relationship between natural frequencies and boundary parameters is deduced according to the vibration equation for the lateral vibration of a non-uniform beam. Then, an iterative identification formulation is established using the sensitivity analysis of natural frequencies with respect to the boundary parameters. The regularization technique is also used to solve the potential ill-posed problem in the identification procedure.Numerical simulations and experiments are performed to validate the feasibility and accuracy of the proposed method. Results show that the proposed method can be utilized to precisely model the boundary parameters of a cantilever-like structure. 展开更多
关键词 BOUNDARY CONDITION IDENTIFICATION BOUNDARY CONDITION MODELLING Iterative method Natural frequency Sensitivity analysis
Simultaneous Denoising and Interpolation of Seismic Data via the Deep Learning Method 预览
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作者 GAO Han ZHANG Jie 《中国地震研究:英文版》 CSCD 2019年第1期37-51,共15页
Utilizing data from controlled seismic sources to image the subsurface structures and invert the physical properties of the subsurface media is a major effort in exploration geophysics. Dense seismic records with high... Utilizing data from controlled seismic sources to image the subsurface structures and invert the physical properties of the subsurface media is a major effort in exploration geophysics. Dense seismic records with high signal-to-noise ratio (SNR) and high fidelity helps in producing high quality imaging results. Therefore, seismic data denoising and missing traces reconstruction are significant for seismic data processing. Traditional denoising and interpolation methods rarely occasioned rely on noise level estimations, thus requiring heavy manual work to deal with records and the selection of optimal parameters. We propose a simultaneous denoising and interpolation method based on deep learning. For noisy records with missing traces, we adopt an iterative alternating optimization strategy and separate the objective function of the data restoring problem into two sub-problems. The seismic records can be reconstructed by solving a least-square problem and applying a set of pre-trained denoising models alternatively and iteratively. We demonstrate this method with synthetic and field data. 展开更多
关键词 Deep learning Convolutional neural network DENOISING Data INTERPOLATION ITERATIVE ALTERNATING
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基于二分法迭代的频谱感知节能优化策略 预览
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作者 陈长兴 林兴 +3 位作者 任晓岳 王晓东 杨牧 曾志 《电子工程学院学报》 2019年第3期103-108,共6页
针对认知无线电(CR)系统中频谱感知技术能量效率低的问题,提出了一种基于二分法迭代寻优的联合优化算法。该算法通过联合传输功率与感知时隙进行优化,最大化地提高了CR系统的能量效率,并且在针对优化参数ξ的寻优过程中,使用了二分法与... 针对认知无线电(CR)系统中频谱感知技术能量效率低的问题,提出了一种基于二分法迭代寻优的联合优化算法。该算法通过联合传输功率与感知时隙进行优化,最大化地提高了CR系统的能量效率,并且在针对优化参数ξ的寻优过程中,使用了二分法与迭代算法结合的寻优方法。通过理论分析,与其他类似算法相比,该算法的寻优速度更快,算法复杂度更低,函数收敛速度更快,实际应用的可扩展性更强。数值仿真分析结果表明,在保证检测性能的前提下,提出的算法能够很好地解决能效的最优化问题,在恒定检测概率Pd=0.9和Pd=0.7条件下,所提出算法的能耗开销均低于其他算法,在系统吞吐量中所提出算法均优于其他算法,为CR系统的发展提供了理论支撑,更加符合未来CR系统的节能发展方向。 展开更多
关键词 认知无线电 频谱感知 能量效率 二分法 迭代
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Total least-squares EIO model,algorithms and applications
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作者 Xingsheng Deng Ge Liu +1 位作者 Tao Zhou Sichun Peng 《大地测量与地球动力学:英文版》 2019年第1期17-25,共9页
A functional model named EIO(Errors-In-Observations) is proposed for general TLS(total least-squares)adjustment. The EIO model only considers the correction of the observation vector, but doesn’t consider to correct ... A functional model named EIO(Errors-In-Observations) is proposed for general TLS(total least-squares)adjustment. The EIO model only considers the correction of the observation vector, but doesn’t consider to correct all elements in the design matrix as the EIV(Errors-In-Variables) model does, furthermore, the dimension of cofactor matrix is much smaller. Iterative algorithms for the parameter estimation and their precise covariance matrix are derived rigorously, and the computation steps are also presented. The proposed approach considers the correction of the observations in the coefficient matrix, and ensures their agreements in every matrix elements. Parameters and corrections can be solved at the same time.An approximate solution and a precise solution of the covariance matrix can be achieved by corresponding algorithms. Applications of EIO model and the proposed algorithms are demonstrated with several examples. The results and comparative studies show that the proposed EIO model and algorithms are feasible and reliable for general adjustment problems. 展开更多
关键词 ERRORS-IN-VARIABLES Errors-In-Observations WEIGHTED total least square Parameter estimation ITERATIVE COVARIANCE solution
Smart homing guidance strategy with control saturation against a cooperative target-defender team 预览
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作者 GUO Hang FU Wenxing +2 位作者 FU Bin CHEN Kang YAN Jie 《系统工程与电子技术:英文版》 SCIE EI CSCD 2019年第2期366-383,共18页
A smart homing guidance strategy with control saturation against a target-defender team is derived. It is noteworthy that a cooperative strategy of the target-defender team is applied,which has been proved more challe... A smart homing guidance strategy with control saturation against a target-defender team is derived. It is noteworthy that a cooperative strategy of the target-defender team is applied,which has been proved more challenging for the homing guidance.The defender missile is launched by the target and guided by a cooperative augmented proportional navigation(APN). At the same time, the target performs a one-switch maneuver to cooperate and minimize the defender’s acceleration requirement. The problem is analyzed for arbitrary-order linear dynamics of the agents in the linearized form but validated by the mathematical simulations by using nonlinear kinematics. The perfect information of three agents’ states is assumed. Then, a method to deal with the target-defender team is proposed. It contains a combined performance index penalizing the miss distance relative to the target and energy consumption in the whole duration. Besides, the specific miss distance related to the defender is regarded as an inequality constraint. An analytical solution for the smart guidance strategy against the APN guided defender is derived. Meanwhile, the control saturations are introduced to get more realistic and reasonable insights to this practical target-missile-defender problem. A simple but effective iterative searching technique is proposed to determine the saturation time points. The solution provides an optimal homing strategy to evade the defender with a specific miss distance and intercept the target with the minimum miss distance in the minimum energy manner. Nonlinear two-dimensional simulation results are used to validate the theoretical analysis. By comparison with the optimal differential game guidance(ODGG) and the combined minimum effort guidance(CMEG), the superiority of this smart guidance strategy is concluded. 展开更多
关键词 SMART HOMING guidance control SATURATION targetmissile-defender ITERATIVE SEARCHING technique
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A new piecewise quadratic approximation approach for L0 norm minimization problem
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作者 Qian Li Yanqin Bai +1 位作者 Changjun Yu Ya-xiang Yuan 《中国科学:数学英文版》 SCIE CSCD 2019年第1期185-204,共20页
In this paper, we consider the problem of finding sparse solutions for underdetermined systems of linear equations, which can be formulated as a class of L0 norm minimization problem. By using the least absolute resid... In this paper, we consider the problem of finding sparse solutions for underdetermined systems of linear equations, which can be formulated as a class of L0 norm minimization problem. By using the least absolute residual approximation, we propose a new piecewis, quadratic function to approximate the L0 norm.Then, we develop a piecewise quadratic approximation(PQA) model where the objective function is given by the summation of a smooth non-convex component and a non-smooth convex component. To solve the(PQA) model,we present an algorithm based on the idea of the iterative thresholding algorithm and derive the convergence and the convergence rate. Finally, we carry out a series of numerical experiments to demonstrate the performance of the proposed algorithm for(PQA). We also conduct a phase diagram analysis to further show the superiority of(PQA) over L1 and L1/2 regularizations. 展开更多
关键词 SPARSE optimization non-convex approximation ITERATIVE THRESHOLDING algorithm
Unknown Input Observer Design of Switched Systems Based on Iterative Learning
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作者 CAO Wei SUN Ming 《系统科学与复杂性学报:英文版》 SCIE EI CSCD 2019年第3期875-887,共13页
For a class of discrete switched systems with unknown input, an unknown input observer design method is proposed under the premise of changes along time axis but no changes along iteration axis. This method applies th... For a class of discrete switched systems with unknown input, an unknown input observer design method is proposed under the premise of changes along time axis but no changes along iteration axis. This method applies the iterative learning control thought to the design of unknown input observer, construets the unknown input observer by introducing virtual input signal, and uses the error signal generated from the actual system output and the observer output to correct repetitively the virtual input, which gradually approxima tes the actual unknown input as the it erations increase. Moreover, the convergence of the observer is strictly proved based on contraction mapping theory, as well as the convergence condition is given. The theoretical analysis indicates that designed unknown input observer can accurately estimate the state and unknown input of the system simultaneously. Simulation example further verifies the effectiveness of the proposed algorithm. 展开更多
关键词 ITERATIVE learning control SWITCHED system UNKNOWN INPUT OBSERVER virtual INPUT
Improved SLIC Segmentation Algorithm for Artificial Structure Images 预览
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作者 Jianzhong Wang Pengzhan Liu +1 位作者 Jiadong Shi Guodong Yan 《北京理工大学学报:英文版》 EI CAS 2019年第3期418-427,共10页
Simple linear iterative cluster(SLIC) is widely used because controllable superpixel number, accurate edge covering, symmetrical production and fast speed of calculation. The main problem of the SLIC algorithm is its ... Simple linear iterative cluster(SLIC) is widely used because controllable superpixel number, accurate edge covering, symmetrical production and fast speed of calculation. The main problem of the SLIC algorithm is its under-segmentation when applied to segment artificial structure images with unobvious boundaries and narrow regions. Therefore, an improved clustering segmentation algorithm to correct the segmentation results of SLIC is presented in this paper. The allocation of pixels is not only related to its own characteristic, but also to those of its surrounding pixels.Hence, it is appropriate to improve the standard SLIC through the pixels by focusing on boundaries. An improved SLIC method adheres better to the boundaries in the image is proposed, by using the first and second order difference operators as magnified factors. Experimental results demonstrate that the proposed method achieves an excellent boundary adherence for artificial structure images. The application of the proposed method is extended to images with an unobvious boundary in the Berkeley Segmentation Dataset BSDS500. In comparison with SLIC, the boundary adherence is increased obviously. 展开更多
关键词 simple linear ITERATIVE CLUSTER (SLIC) SEGMENTATION superpixel image ENHANCEMENT
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A 2-Stage Strategy for Non-Stationary Signal Prediction and Recovery Using Iterative Filtering and Neural Network
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作者 Feng Zhou Hao-Min Zhou +1 位作者 Zhi-Hua Yang Li-Hua Yang 《计算机科学技术学报:英文版》 SCIE EI CSCD 2019年第2期318-338,共21页
Predicting the future information and recovering the missing data for time series are two vital tasks faced in various application fields.They are often subjected to big challenges,especially when the signal is nonlin... Predicting the future information and recovering the missing data for time series are two vital tasks faced in various application fields.They are often subjected to big challenges,especially when the signal is nonlinear and nonstationary which is common in practice.In this paper,we propose a hybrid 2-stage approach,named IF2FNN,to predict(including short-term and long-term predictions)and recover the general types of time series.In the first stage,we decompose the original non-stationary series into several“quasi stationary”intrinsic mode functions(IMFs)by the iterative filtering(IF)method.In the second stage,all of the IMFs are fed as the inputs to the factorization machine based neural network model to perform the prediction and recovery.We test the strategy on five datasets including an artificial constructed signal(ACS),and four real-world signals:the length of day(LOD),the northern hemisphere land-ocean temperature index(NHLTI),the troposphere monthly mean temperature(TMMT),and the national association of securities dealers automated quotations index(NASDAQ).The results are compared with those obtained from the other prevailing methods.Our experiments indicate that under the same conditions,the proposed method outperforms the others for prediction and recovery according to various metrics such as mean absolute error(MAE),root mean square error(RMSE),and mean absolute percentage error(MAPE). 展开更多
关键词 ITERATIVE FILTERING FACTORIZATION machine NEURAL network time series data RECOVERY
一种改进的编码辅助位定时算法 预览
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作者 孟正科 张昊亮 +1 位作者 王伟 翟盛华 《空间电子技术》 2019年第4期40-43,49共5页
基于期望最大算法(EM)的编码辅助位定时算法是最常用的定时偏差估计算法,其在估计定时偏差时会引入大量的乘法和加法运算,计算复杂度较高。文章针对计算复杂度问题提出了一种改进的算法,通过选取合适的门限值,去除了LDPC码译码之后不可... 基于期望最大算法(EM)的编码辅助位定时算法是最常用的定时偏差估计算法,其在估计定时偏差时会引入大量的乘法和加法运算,计算复杂度较高。文章针对计算复杂度问题提出了一种改进的算法,通过选取合适的门限值,去除了LDPC码译码之后不可靠符号的译码软信息,减少了同步参数估计时参与计算的不可靠样点的个数,可以有效减少原算法的计算量。仿真结果表明,改进算法的系统误码性能及参数估计的均方根误差(RMSE)与原EM算法的性能接近,同时减小了原EM算法的计算量。 展开更多
关键词 低信噪比 编码辅助位定时 LDPC 迭代 低复杂度
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Iterative static modeling of channelized reservoirs using historymatched facies probability data and rejection of training image
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作者 Kyungbook Lee Sungil Kim +2 位作者 Jonggeun Choe Baehyun Min Hyun Suk Lee 《石油科学:英文版》 SCIE CAS CSCD 2019年第1期127-147,共21页
Most inverse reservoir modeling techniques require many forward simulations, and the posterior models cannot preserve geological features of prior models. This study proposes an iterative static modeling approach that... Most inverse reservoir modeling techniques require many forward simulations, and the posterior models cannot preserve geological features of prior models. This study proposes an iterative static modeling approach that utilizes dynamic data for rejecting an unsuitable training image (TI) among a set of TI candidates and for synthesizing history-matched pseudo-soft data. The proposed method is applied to two cases of channelized reservoirs, which have uncertainty in channel geometry such as direction, amplitude, and width. Distance-based clustering is applied to the initial models in total to select the qualified models efficiently. The mean of the qualified models is employed as a history-matched facies probability map in the next iteration of static models. Also, the most plausible TI is determined among TI candidates by rejecting other TIs during the iteration. The posterior models of the proposed method outperform updated models of ensemble Kalman filter (EnKF) and ensemble smoother (ES) because they describe the true facies connectivity with bimodal distribution and predict oil and water production with a reasonable range of uncertainty. In terms of simulation time, it requires 30 times of forward simulation in history matching, while the EnKF and ES need 9000 times and 200 times, respectively. 展开更多
关键词 History-matched FACIES PROBABILITY map Training image REJECTION ITERATIVE STATIC modeling ? Channelized RESERVOIRS - Multiple-point statistics History matching
Sketch simplification guided by complex agglomeration
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作者 Yue LIU Xuemei LI +1 位作者 Pengbo BO Xifeng GAO 《中国科学:信息科学(英文版)》 SCIE EI CSCD 2019年第5期145-160,共16页
We propose a novel method for vector sketch simplification based on the simplification of the geometric structure that is extracted from the input vector graph, which can be referred to as a base complex.Unlike the se... We propose a novel method for vector sketch simplification based on the simplification of the geometric structure that is extracted from the input vector graph, which can be referred to as a base complex.Unlike the sets of strokes, which are treated in the existing approaches, a base complex is considered to be a collection of various geometric primitives. Guided by the shape similarity metrics that are defined for the base complex, an agglomeration procedure is proposed to simplify the base complex by iteratively merging a pair of geometric primitives that exhibit the minimum cost into a new one. This simplified base complex is finally converted into a simplified vector graph. Our algorithm is computationally efficient and is able to retain a large amount of useful shape information from the original vector graph, thereby achieving a tradeoff between efficiency and geometric fidelity. Furthermore, the level of simplification of the input vector graph can be easily controlled using a single threshold in our method. We make comparisons with some existing methods using the datasets that have been provided in the corresponding studies as well as using different styles of sketches drawn by artists. Thus, our experiments demonstrate the computational efficiency of our method and its capability for producing the desirable results. 展开更多
关键词 SKETCH SIMPLIFICATION base COMPLEX ITERATIVE MERGING
Parameter Estimation Based on Set-valued Signals: Theory and Application
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作者 Ting WANG Hang ZHANG Yan-long ZHAO 《应用数学学报:英文版》 SCIE CSCD 2019年第2期255-263,共9页
This paper summarizes the parameter estimation of systems with set-valued signals, which can be classified to three catalogs: one-time completed algorithms, iterative methods and recursive algorithms. For one-time com... This paper summarizes the parameter estimation of systems with set-valued signals, which can be classified to three catalogs: one-time completed algorithms, iterative methods and recursive algorithms. For one-time completed algorithms, empirical measure method is one of the earliest methods to estimate parameters by using set-valued signals, which has been applied to the adaptive tracking of periodic target signals. The iterative methods seek numerical solutions of the maximum likelihood estimation, which have been applied to both complex diseases diagnosis and radar target recognition. The recursive algorithms are constructed via stochastic approximation and stochastic gradient methods, which have been applied to adaptive tracking of non-periodic signals. 展开更多
关键词 SET-VALUED SIGNALS parameter ESTIMATION one-time completed ALGORITHMS ITERATIVE ESTIMATION ALGORITHMS RECURSIVE ESTIMATION ALGORITHMS
Near Infrared Star Centroid Detection by Area Analysis of Multi-Scale Super Pixel Saliency Fusion Map
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作者 Xiaohu Yuan Shaojun Guo +2 位作者 Chunwen Li Bin Lu Shuli Lou 《清华大学学报自然科学版(英文版)》 EI CAS CSCD 2019年第3期291-300,共10页
The centroid location of a near infrared star always deviates from the real center due to the effects of surrounding radiation. To determine a more accurate center of a near infrared star, this paper proposes a method... The centroid location of a near infrared star always deviates from the real center due to the effects of surrounding radiation. To determine a more accurate center of a near infrared star, this paper proposes a method to detect the star’s saliency area and calculate the star’s centroid via the pixels only in this area, which can greatly decrease the effect of the radiation. During saliency area detection, we calculated the boundary connectivity and gray similarity of every pixel to estimate how likely it was to be a background pixel. Aiming to simplify and speed up the calculation process, we divided the near infrared starry sky image into super pixel maps at multi-scale by Simple Linear Iterative Clustering(SLIC). Second, we detected the saliency map for every super pixel map of the image. Finally, we fused the saliency maps according to a weighted coefficient that is determined by the least square method. For the images used in our experiment, we set the multi-scale super pixel numbers to 100, 150,and 200. The results show that our method can obtain an offset variance of less than 0.27 for the center coordinates compared to the labelled centers. 展开更多
关键词 near INFRARED starry STAR SALIENCY Simple Linear ITERATIVE Clustering (SLIC)
An Iterative Compensation Algorithm for Springback Control in Plane Deformation and Its Application
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作者 Rui Ma Chunge Wang +1 位作者 Ruixue Zhai Jun Zhao 《中国机械工程学报:英文版》 SCIE EI CAS CSCD 2019年第2期212-223,共12页
In order to solve the springback problem in sheet metal forming, the trial and error method is a widely used method in the factory, which is time-consuming and costly for its non-direction and non-quantitative. Finite... In order to solve the springback problem in sheet metal forming, the trial and error method is a widely used method in the factory, which is time-consuming and costly for its non-direction and non-quantitative. Finite element simulation is an e ective method to predict the springback of complex shape parts, but its precision is sensitive to the simulation model, particularly material model and boundary conditions. In this paper, the simple iterative method is introduced to establish the iterative compensation algorithm, and the convergence criterion of iterative parameters is put forward. In addition, the new algorithm is applied to the V-free bending and stretch-bending processes, and the convergence of curvature and bending angle is proved theoretically and verified experimentally. At the same time,the iterative compensation experiments for plane bending show that, the new method can predict the next compensaantido tnh ev atlaureg ebta cseurdv oatnu trhe ew sitphri tnhgeb earcrko ro fo fe laecshs ttehsat,n s0 o. 5 th%a ta rteh eo btatraigneet db aefntedri n2 g-3 a nitgelrea tiwoitnhs.t Thhei se rrreosre aorf clhe sps rtohpaons e±s 0 a.1%new iterative compensation algorithm to predict springback in sheet metal forming process, where each compensation value depends only on the iteration parameter di erence before and after springback for the same forming process of same material. 展开更多
关键词 SPRINGBACK control ITERATIVE COMPENSATION algorithm CONVERGENCE CRITERION V-free BENDING Stretchbending
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