A pipelined Reed-Solomon decoder based on a modified step-by-step algorithm

We propose a pipelined Reed-Solomon(RS) decoder for an ultra-wideband system using a modified stepby-step algorithm. To reduce the complexity, the modified step-by-step algorithm merges two cases of the original algorithm. The pipelined structure allows the decoder to work at high rates with minimum delay. Consequently, for RS(23,17) codes, the proposed architecture requires 42.5% and 24.4% less area compared with a modified Euclidean architecture and a pipelined degree-computationless modified Euclidean architecture, respectively. The area of the proposed decoder is 11.3% less than that of the previous step-by-step decoder with a lower critical path delay.

Random Timestepping Algorithm with Exponential Distribution for Pricing Various Structures of One-Sided Barrier Options

The exponentially-distributed random timestepping algorithm with boundary test is implemented to evaluate the prices of some variety of single one-sided barrier option contracts within the framework of Black-Scholes model, giving efficient estimation of their hitting times. It is numerically shown that this algorithm, as for the Brownian bridge technique, can improve the rate of weak convergence from order one-half for the standard Monte Carlo to order 1. The exponential timestepping algorithm, however, displays better results, for a given amount of CPU time, than the Brownian bridge technique as the step size becomes larger or the volatility grows up. This is due to the features of the exponential distribution which is more strongly peaked near the origin and has a higher kurtosis compared to the normal distribution, giving more stability of the exponential timestepping algorithm at large time steps and high levels of volatility.

Auxiliary principle and three-step iterative algorithms for generalized set-valued strongly nonlinear mixed variational-like inequalities

An auxiliary principle technique to study a class of generalized set-valued strongly nonlinear mixed variational-like inequalities is extended. The existence and uniqueness of the solution of the auxiliary problem for the generalized set-valued strongly nonlinear mixed variational-like inequalities are proved, a novel and innovative three-step iterative algorithm to compute approximate solution is constructed, and the existence of the solution of the generalized set-valued strongly nonlinear mixed variational-like inequality is shown using the auxiliary principle iterative sequences generated by the algorithm technique. The convergence of three-step is also proved.

Sliding state stepping algorithm for solving impact problems of multi-rigid-body system with joint friction

Impact dynamics of multi-rigid-body systems with joint friction is considered. Based on the traditional approximate assumption dealing with impact problem, a general numerical method called the sliding state stepping algorithm is introduced. This method can avoid difficulties in solving differential equations with variable scale and its result can avoid energy inconsistency before and after impact from considering complexily of tangential sliding mode. An example is given to describe details using this algorithm.

Study of Variable Step Size LMS Adaptive Algorithm Based on Variable Region

This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size p（k） in the algorithm varies with the variation of the region of deviation e （k） to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise,

Application of simulated annealing algorithm to optimizing sequencing of operation steps

Discusses the optimization of machining operation sequencing by simulated annealing, and building a simulated annealing optimization model. From which, a new way to optimize operation sequencing can be developed.

Convergence Properties and Step Size Estimation for MLMS Algorithm

According to the exact expression of the maladjustment, an equation for calculating the boundary of step-size in MLMS algorithm is derived and the relationship between the convergence rate and step-size is discussed in detail. It is shown that the threshold of the step-size is constrained by maladjustment. Three different properties are presented between the LMS and MLMS algorithms based on comparison. It is indicated that MLMS does not differ significantly from LMS when the given maladjustment is small.

一种混合多策略改进的麻雀搜索算法

针对麻雀搜索算法SSA求解目标函数最优解时具有过早收敛、在多峰条件下易陷入局部最优和在高维情况下求解精度不足等问题,提出了一种混合多策略改进的麻雀搜索算法MISSA。考虑到算法初始解的质量很大程度上会影响整个算法的收敛速度与精度,引入精英反向学习策略,扩大算法的搜索区域,提升初始种群的质量和多样性;对步长进行分阶段控制,以提高算法的求解精度;通过在跟随者的位置中加入Circle映射参数与余弦因子,提高算法的遍历性与搜索能力;采用自适应选择机制在麻雀个体位置更新中加入Lévy飞行,增强算法寻优和跳出局部最优的能力。将改进后的算法与麻雀搜索算法及其他算法在13个测试函数上进行对比,并进行Friedman检验。实验结果表明,改进后的麻雀搜索算法能够有效提高寻优精度与收敛速度,并在高维问题中也具备较高的稳定性。

基于多线程加速的STEP标准并行解析算法

当前CAD软件加载大型STEP中性文件时速度慢,其效率瓶颈关键在于其解析算法.针对基于单线程的中性标准解析算法已经远远不能满足当前CAD应用需求的问题,提出了一种基于多线程的分层并行数据解析算法,利用当前主流CPU都采用的多核并行架构,大幅提升了STEP文件解析效率.根据模型体中数据的分层特性,算法利用线程池对各层数据解析进行并行加速.文中算法已经在开源几何引擎OpenGE中实现.与OpenCASCADE的对比实验验证了文中算法的有效性.实验结果表明,算法的并行解析程序运行速度相比串行解析程序运行速度提升至原算法的2倍,比OpenCASCADE解析算法快50%.

基于POD-αATS的油浸变压器瞬态温升降阶自适应变步长计算方法

针对油浸式电力变压器瞬态温升计算效率过低的问题,该文提出本征正交分解-αATS(proper orthogonal decomposition-adaptive time stepping based onαfactor,POD-αATS)降阶自适应变步长瞬态计算方法。首先,推导变压器绕组瞬态温升计算的有限元离散方程;其次,采用POD降阶算法改善传统瞬态计算中存在的条件数过大及方程阶数过高的问题;同时对于瞬态计算中的时间步长选择问题,提出适用于非线性问题的αATS变步长策略;然后,为验证方法的有效性,基于110 kV油浸式电力变压器绕组的基本结构建立二维八分区数值计算模型,同时将计算结果与基于110 kV绕组的温升实验结果进行对比。数值计算及实验结果表明,所提算法与全阶定步长算法在流场和温度场中的精度几乎相同,且流场计算效率提升约45倍,温度场计算效率提升约38倍,计算速度得到显著提高。这一点在温升实验中同样得到验证,说明该文所提算法的准确性、高效性及一定的工程实用性。

An Adaptive Fruit Fly Optimization Algorithm for Optimization Problems

In this paper, we present a new fruit fly optimization algorithm with the adaptive step for solving unconstrained optimization problems, which is able to avoid the slow convergence and the tendency to fall into local optimum of the standard fruit fly optimization algorithm. By using the information of the iteration number and the maximum iteration number, the proposed algorithm uses the floor function to ensure that the fruit fly swarms adopt the large step search during the olfactory search stage which improves the search speed;in the visual search stage, the small step is used to effectively avoid local optimum. Finally, using commonly used benchmark testing functions, the proposed algorithm is compared with the standard fruit fly optimization algorithm with some fixed steps. The simulation experiment results show that the proposed algorithm can quickly approach the optimal solution in the olfactory search stage and accurately search in the visual search stage, demonstrating more effective performance.

3D打印机多轴联动插补算法的研究与优化

针对3D打印过程中,打印机多轴联动插补算法计算效率低的问题和Bresenham算法在3D打印运动控制中的不足,在现有算法基础之上提出阶跃式Bresenham算法、速度自适应算法,分别完成喷嘴的成型扫描运动和浆料的挤出运动.采用两种算法相结合的方式控制3D打印机多轴联动,从而提高3D打印机的插补速度.同时分析了该控制方式在微控制器中的实现流程,并将其移植于微控制器中.本研究设计了直线插补仿真试验和不同算法的3D打印试验,证明了该控制方式在打印精度不变的前提下能够提高打印效率.

基于改进APF-Informed-RRT^(*)的机械臂避障路径规划

针对Informed-RRT^(*)算法在避障路径规划中缺乏目的性和方向性,存在规划时间长、迭代效率低等问题,提出了结合人工势场法和Informed-RRT^(*)算法的避障规划算法。首先,针对传统人工势场法存在目标点不可达、易与障碍物碰撞的问题,提出了改进后的人工势场法,并将其融入Informed-RRT^(*)算法中,使随机树沿势场下降的方向生长,增强其方向性;其次,依据随机树与障碍物间的距离,提出了一种自适应生长步长策略,提高了对空间的探索能力;最后,引入贪心算法的思想,在生长时直接判断随机树能否直达目标点,提高了路径规划效率。在二维和三维环境下对改进后的算法与传统算法及其衍生算法进行对比实验,仿真结果表明改进后的Informed-RRT^(*)算法相较于原始算法规划的路径长度和规划耗时分别减少了17.42%和36.21%。

具有串并行异类工序约束的多柔性车间联合调度

为了减少具有串并行异类工序约束多车间联合调度的总延期时间,提出了基于知识牵引遗传算法的调度求解方法。首先,采用扩展工艺树描述串并行异类工序约束,并基于无向图描述机器在多车间的分布;针对染色体初始化和进化过程中的扩展工艺树约束,定义了紧前工序数和剩余紧前工序数的概念,基于剩余紧前工序数设计了染色体初始化和进化方法;为了提高遗传算法的进化能力,将种群进化能力和最优个体进化能力作为知识,用于牵引算法的进化方式和方向,从而提出了知识牵引遗传算法的求解方法。经实验验证,知识牵引遗传算法调度的总延期时间均值最小,为30.8 h,说明该算法在多车间调度中具有最好的优化性能;且总延期时间盒须图长度最小,说明知识牵引遗传算法的稳定性也较好。

基于改进深度强化学习的SCR脱硝系统复合控制研究

针对选择性催化还原(Selective catalytic reduction,SCR)脱硝系统延迟大、扰动多等特点,提出了一种基于改进双延迟深度确定性策略梯度(Twin delayed deep deterministic policy gradient,TD3)的SCR脱硝系统复合控制策略。首先,提出了一种融合多步时序差分(Muti-step temporal-difference,MSTD)和优先经验回放(Prioritized experience replay,PER)的改进TD3算法。该算法在策略更新时使用MSTD计算回报,同时利用PER选择重要的经验进行学习,以此提高TD3算法的策略学习能力并加速算法的学习过程。其次,通过设计多维状态观测,综合考虑SCR脱硝系统的前馈信号和验证反馈信号来实现SCR脱硝系统的复合控制,进而维持出口NOx浓度的稳定性。最后,进行仿真实验验证,结果表明基于MSTD-PER-TD3算法的复合控制策略能更有效地克服入口NOx浓度波动对出口NOx浓度的影响,并具有优秀的抗干扰能力和鲁棒性。

基于改进RRT-Connect算法的全局路径规划

针对RRT-Connect算法在复杂环境内的路径规划中存在探索性弱、收敛速度慢、冗余节点多、搜索路径较长等问题,提出一种改进的RRT-Connect算法。通过引入高质量随机点和动态步长的方法,提高了生成随机树的质量并减少了冗余节点数量;采用正向寻优和逆向贪婪的方式,改善了搜索路径较长的问题。实验结果表明,改进RRT-Connect算法平均路径规划时间缩短26.41%,平均路径规划长度缩短19.05%,平均路径规划节点个数减少41.91%,证明了改进RRT-Connect算法相比于原算法规划效率更高,规划时间更少,规划路径质量更优。

单调线性权互补问题的新全牛顿步可行内点算法

提出求解单调线性权互补问题(WLCP)的全牛顿步可行内点算法。基于线性优化的连续可微函数,给出中心方程的新等价形式,接着运用牛顿法求解定义中心路径的等价方程组,从而得到单调WLCP的新搜索方向。沿该搜索方向使用全牛顿步,无需进行线搜索。通过适当选取参数,分析了全牛顿步的严格可行性,证得算法是二次收敛的且具有多项式时间迭代复杂度。最后数值实验结果表明算法有效。

柔性机械爪力控的变步长自适应滤波算法

机械爪工作中,由于电源和机械震动会导致电流有波动,将测得的电流数据通过滤波,减少电流的波动,从而让力控的准确度更高。传统的自适应算法无法满足在快速收敛的同时,实现较高鲁棒性和较小稳态误差的要求。针对上述问题,文中提出一种新的自适应滤波算法。首先,建立基于双曲正切函数的变步长模型,实现更新步长因子的动态变值,其次,将滤波器权向量差及可变因子引入更新权值迭代算法中,以达到快速收敛和减少稳态误差的目的。通过实验证明,文中算法实现了快速收敛,并具有较小的稳态误差,提高了系统的鲁棒性。

尾矿坝位移分级预警阈值研究及规律分析

针对尾矿坝在线监测重建设、轻利用的现状,基于尾矿坝位移在线监测时间序列,通过多步逆向云变换算法(Multi-step Backward Cloud Transformation Algorithm Based on Sampling with Replacement,MBCT-SR)改进云模型,根据“3E_(n)原则”和内外包络曲线确定在线监测位移的正常运行值,从而建立尾矿坝位移分级预警阈值模型,并利用某尾矿坝全球导航卫星(Global Navigation Satellite System,GNSS)技术表面位移在线监测数据进行实例验证。结果表明:该尾矿坝水平方向位移的黄、橙、红预警阈值分别为8.41 mm/d、12.94 mm/d、19.41 mm/d,呈现出坝体中间预警阈值最大、并由中间向两侧减小的空间变化规律;尾矿坝垂直方向位移的黄、橙、红预警阈值分别为16.56 mm/d、25.48 mm/d、38.22 mm/d,且随着子坝的堆积,预警阈值逐渐增大。

改进海洋捕食者算法的机器人路径规划研究

为解决海洋捕食者算法(MPA)收敛速度慢、收敛精度低、易陷入局部最优的问题,提出一种多策略改进海洋捕食者算法(IMPA)。引入Logistic混沌映射初始化种群,增加捕食者种群多样性;基于当前迭代次数t的自适应移动步长动态调整策略,增强算法逃离局部最优的能力;在IMPA迭代后期,加入中垂线算法(MA),基于中垂线策略的游离粒子位置更新方法,能够加快更新捕食者的位置,增强算法的寻优速度和寻优精度,避免算法陷入局部最优。最后通过改变IMPA阶段转换寻优过程,进一步平衡搜索过程,加强全局与局部适应性。选用6个基准测试函数对算法性能进行测试,测试结果显示:IMPA收敛速度更快,收敛精度更高;最后将改进算法应用于移动机器人路径规划,仿真结果表明:该算法规划的路径长度更短,搜索效率更高。