磨料水射流切割速率平滑处理算法的仿真优化

在S型曲线加减速算法的基础上,设计开发了一种新的速度变化率与插补位置的非线性算法,得到一种新的速率平滑处理方法.并针对水射流切割速度对切割质量的主要影响因素,进行了一系列的速率处理方式变化、速率平滑处理下加减速距离变化的模拟实验,从而找到水射流切割速率与切割质量的关系和规律.     

A joint introduction to Gaussian Processes and Relevance Vector Machines with connections to Kalman filtering and other kernel smoothers

The expressive power of Bayesian kernel-based methods has led them to become an important tool across many different facets of artificial intelligence, and useful to a plethora of modern application domains, providing both power and interpretability via uncertainty analysis. This article introduces and discusses two methods which straddle the areas of probabilistic Bayesian schemes and kernel methods for regression: Gaussian Processes and Relevance Vector Machines. Our focus is on developing a common framework with which to view these methods, via intermediate methods a probabilistic version of the well-known kernel ridge regression, and drawing connections among them, via dual formulations, and discussion of their application in the context of major tasks: regression, smoothing, interpolation, and filtering. Overall, we provide understanding of the mathematical concepts behind these models, and we summarize and discuss in depth different interpretations and highlight the relationship to other methods, such as linear kernel smoothers, Kalman filtering and Fourier approximations. Throughout, we provide numerous figures to promote understanding, and we make numerous recommendations to practitioners. Benefits and drawbacks of the different techniques are highlighted. To our knowledge, this is the most in-depth study of its kind to date focused on these two methods, and will be relevant to theoretical understanding and practitioners throughout the domains of data-science, signal processing, machine learning, and artificial intelligence in general.     

Robust registration based compensation method based on sparse recovery

The loss of the degree of system freedom and mismatch of prior information based on the registration based compensation (RBC) method will result in a decline in computational performance. In order to solve above problems, a robust method named SRBC is proposed where the sparse recovery method is applied instead of the sub-aperture smoothing operation. First, the SRBC utilizes the sparse recovery to get the super resolution clutter space-time spectrum. Then the transition covariance matrix is calculated. Finally, the clutter covariance matrix is reconstructed by the Capon spectrum. Compared with the traditional RBC method, the SRBC proposed does not depend on sub-aperture smoothing operation and prior information and maintains the performance of clutter range-dependence. In addition, it is also steadier when the sensor error exists. Experimental simulation demonstrates the correctness and feasibility of this method.     

不同选样方法下暴雨频率指数分布曲线的适用性

为了判定指数分布曲线是否适用于选取的样本系列,对不同选样样本系列的概率密度曲线和指数分布曲线之间的相似情况进行了理论分析,并结合实例采用指数分布曲线对不同选样方法下选取的样本系列概率密度直方图进行曲线拟合。结果表明：年最大值法选样从理论上不适宜选用指数分布曲线进行频率分析;年多个样法选取样本系列只有在概率密度曲线呈“捺”形时,才可以考虑采用指数分布曲线,否则不宜采用。     

复杂系统平均寿命的估计和性质

根据已知的基于最小路径或最小割集复杂系统可靠度函数的解析表达式,给出当子系统寿命分布服从指数分布时,系统平均寿命的表达式.利用这一表达形式,在子系统寿命变量服从指数分布条件下,分别就完全数据和截尾数据两种情况,给出了系统平均寿命的估计,并对估计性质进行了研究.并在完全数据下,给出了估计的渐近分布.     

一类二次比式和最优解的研究

对于二次比式和问题的最优解问题,提出了一种罚函数法以及单纯形分枝定界算法.利用指数函数及线性化技术,将约束优化问题转化为易于求解的无约束优化问题,最终给出了算法.     

成型砂轮截面曲线光顺处理的近似双圆弧插补法及误差估算

在解决成型砂轮截面曲线的光顺处理问题时，作者提出了一种新的曲线数字化处理方法——近似双圆弧插补法，简化了计算过程。为了估算该方法的误差，本文模拟曲线反求的过程进行了仿真计算，计算结果表明：若曲线反求时测量点的间距取为0．1mm左右，则对所讨论的实例而言，处理结果对原曲线的最大偏离为0．552μm，这样的误差对数控加工影响很小，而且整个处理过程所花费的时间不足1分钟，因此，该方法能满足数控加工的要求。     

Anti-periodic solutions in a ring of four neurons with multiple delays

This paper is concerned with the existence and exponential stability of anti-periodic solutions of bidirectional associative memory (BAM) neural networks with multiple delays. Applying inequality techniques and Lyapunov method, Sufficient conditions which ensure the existence and exponential stability of anti-periodic solutions of the BAM neural networks are presented. Our results are new and supplement some previously known ones.     

近似非齐次无偏GM(1,1) 模型的递推解法及应用

针对传统近似非齐次灰建模可能出现参数复数解的问题, 提出无偏灰色GM(1,1) 模型的递推解法, 从而减少由差分方程向微分方程跳跃而导致误差的问题. 给出不同初始条件下非齐次无偏GM(1,1) 模型的递推预测公式,并在此基础上, 将递推公式运用于时间序列分段, 提出基于近似非齐次无偏GM(1,1) 模型的时间序列分段表示方法. 实例结果表明, 所提出的递推模型能够获得较高的拟合精度, 分析结果验证了基于灰色预测模型在时间序列分段表示中的有效性和实用性.

     

Stability analysis and control for switched stochastic delayed systems

This paper investigates almost sure exponential stability and feedback stabilization for switched time‐delay systems with nonlinear stochastic perturbations. The main contributions of this paper are threefold: (i) based on the non‐convolution type multiple Lyapunov functionals and the mathematical induction approach, a mean‐square exponential stability condition for nonlinear stochastic switched systems is first established, such that the obtained average dwell time does not rely on any given decay rate; (ii) by using the method developed in part (i) and the stochastic analysis techniques and limit methods in probability, an almost sure exponential stability criterion for switched delayed systems with nonlinear stochastic uncertainties is presented, and then a state feedback controller for the systems under consideration is designed; and (iii) when certain assumptions are made on the nonlinear stochastic perturbations, the results in this paper are further improved by relaxing some conditions. The effectiveness of the proposed method is demonstrated by three illustrative examples. Copyright © 2015 John Wiley & Sons, Ltd.