BSC信道下线性分组码的差错概率下界分析

针对BSC信道,提出了一种线性分组码的最大似然译码差错概率下界的计算方法.根据最大似然译码算法原理,首先将译码差错概率转化为差错事件的联合概率,基于改进的Dawson-Sankoff界的优化准则,推导出BSC信道下线性分组码差错冗余事件的判决准则,最后得到差错概率下界的计算表达式.该下界只依赖于码字的Hamming重量...     

初速可控舰炮对海上目标命中概率的影响

针对新能源技术发射弹丸初速可控的新特点,研究初速对命中概率的影响。建立海上目标运动模型,利用Cramer-Rao下界理论得到目标运动要素估计误差的计算模型。根据海上目标特点,推导出弹丸外弹道方程及目标命中界计算模型,并对射击误差进行分析,得到弹丸对海上目标的命中概率模型。分析了射击误差、目标距离、弹丸射角和初速对目标命中概率的影响,结果表明对视距内海上目标存在最佳弹丸初速使命中概率达到最大。     

基于Neyman-Pearson准则的自适应门限干扰抑制算法

针对制约变换域通信系统抗干扰性能的门限抑制问题,提出了基于Neyman-Pearson准则的自适应门限干扰抑制算法。从硬件实现角度,通过干扰提取模块和自适应门限比较器,建立干扰抑制系统;根据环境频谱,基于高斯分布和N-sigma原理,确定初始门限和虚警概率;提出了基于Neyman-Pearson准则的自适应门限算法,在约束条件下保证检测概率最大化。仿真结果表明,该自适应门限算法能够有效抑制多音干扰和线性调频干扰,干扰的剔除效果较好;同时具有良好的检测性能,较传统的双门限检测概率提高约3.14%的性能增益。     

一种改进的联合概率数据关联算法

联合概率数据关联算法(JPDA)是密集杂波环境下一种有效的多目标跟踪算法,但该算法的复杂度会随着目标和观测值的增加而显著增长。为了减少JPDA算法所需要的存贮空间和计算时间,提出了一种改进的联合概率数据关联算法(I-JPDA)。首先通过合理选取跟踪门门限的阈值,去除小概率事件,然后再根据跟踪门内目标的关联概率对关联事件的概率密度值进行衰减,计算出跟踪门内各目标的关联概率。经过理论分析和仿真试验,证明了该方法在保证跟踪成功率的同时,还具有算法简单、计算量小和易于工程实现等优点。     

利用区间着色 Petri 网的 C~3I 系统时延分析

Ｃ３Ｉ系统是一个复杂的分布式离散事件动态系统,适合于用Ｐｅｔｒｉ网来描述其异步,并发行的,而且Ｃ３Ｉ系统是一个时间准则系统,文中提出的区间着色Ｐｅｔｒｉ网非常适合于分析其严格时限,并给出计算时延上（下）界的算法。     

基于N-P准则的雷达网反隐身探测概率分析

提高雷达网的探测概率是改善雷达网反隐身性能的重要手段。在分析单部雷达探测概率的基础上,提出了一种基于Neyman-Pearson(N-P)准则的雷达网信号检测数据融合评估算法,算法利用数据融合原理构建了N-P探测模型,给出了基于迭代算法的最优检测概率和判决门限计算方法。仿真结果表明了系统反隐身的有效性和融合算法的优越性。     

适用于复杂系统仿真试验的试验设计方法

拉丁超立方试验设计是"充满空间"试验设计方法的重要领域.传统拉丁超立方试验设计优化以列相关系数最小化或试验点之间最大距离最小为单一优化准则,这种单目标试验设计优化方法存在缺陷.提出了将两类优化准则作为优化目标的多目标优化准则,以及实现多目标优化的改进ESE算法.算例分析证明,提出的试验设计优化算法优于已有典型试验设计方法.     

等概率抽样群体演化算法的隐含并行性

在等概率抽样群体的条件下,讨论了演化算法的隐合并行性,得到了算法每代隐含处理的模式长度不超过ls（0≤ls≤l）的不同模式期望数的精确表达,并估计了其上下界．     

故障树近似计算中最优权因子的选取

在故障树近似计算时,探讨通过加权提高计算准确度的简便方法。根据底事件发生概率的不同,利用VisualC 语言进行蒙特卡罗仿真计算,得到了在近似计算故障树顶事件发生概率时,在不同底事件发生概率对应区间内的最优权因子。利用该方法得到的最优权因子可以提高故障树近似计算的准确度,尤其是在当底事件发生概率较大时,其效果更为明显,可较好地满足采用故障树对某些特殊设备进行顶事件发生概率计算时提高计算精度的需求。     

基于模糊的联合概率数据关联简化算法

为解决联合概率数据关联(JPDA)实时性差的问题,提出了基于模糊的联合概率数据关联简化算法。首先结合模糊理论、概率数据关联(PDA)算法,构建模糊矩阵,并根据隶属度大小建立新的确认矩阵,然后采用JPDA算法计算关联概率。仿真结果表明算法简单有效,与JPDA算法相比,在跟踪性能相当的前提下,算法的实时性能得到了较大提升。     

Minimizing the sum of weighted completion times of n-independent jobs when resource availability varies over time: Performance of a simple priority rule

In this article our objective is to evaluate the performance of a WSPT (weighted shortest processing time) rule for scheduling n independent jobs where the resources to process these jobs vary over time and a job can be processed by several processors simultaneously. This problem was raised by Baker and Nuttle [2]. A linear-programming (LP) model is formulated to obtain a lower bound on the minimum value of the weighted completion times. The purpose of the model is to provide a basis for evaluating the WSPT heuristic. 1000 experiments were performed using different resource profiles to test the performance of WSPT. Using WSPT, the weighted completion times were found to be, on the average, 0.2% away from their LP lower bounds.     

随机弱实时系统作业调度概率保证分析

随机弱实时系统与强实时系统的显著区别是 ,它不要求实时任务的每一项作业都满足时限要求 ,只要保证作业的时限延误率低于某一阈值 ,其总体执行性能就是可以接受的。提出了概率时间需求分析法 (PTDA) ,用于估计可剥夺静态优先级调度策略下周期性任务的作业满足时限约束的概率的下界 ,并通过一个具体的实例考察了下界的紧性。对实例系统的仿真结果表明 ,PTDA分析的误差小于 1 0 % ,计算速度快 ,可以为弱实时应用的设计提供重要的参考依据     

Stein–Chen approximation and error bounds for order fill rates in assemble‐to‐order systems

Assemble‐to‐order (ATO) is an important operational strategy for manufacturing firms to achieve quick response to customer orders while keeping low finished good inventories. This strategy has been successfully used not only by manufacturers (e.g., Dell, IBM) but also by retailers (e.g., Amazon.com). The evaluation of order‐based performance is known to be an important but difficult task, and the existing literature has been mainly focused on stochastic comparison to obtain performance bounds. In this article, we develop an extremely simple Stein–Chen approximation as well as its error‐bound for order‐based fill rate for a multiproduct multicomponent ATO system with random leadtimes to replenish components. This approximation gives an expression for order‐based fill rate in terms of component‐based fill rates. The approximation has the property that the higher the component replenishment leadtime variability, the smaller the error bound. The result allows an operations manager to analyze the improvement in order‐based fill rates when the base‐stock level for any component changes. Numerical studies demonstrate that the approximation performs well, especially when the demand processes of different components are highly correlated; when the components have high base‐stock levels; or when the component replenishment leadtimes have high variability. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Bounds on the availability function

This paper gives bounds on the availability function for an alternating renewal process with exponential failure and general repair times. A bound on the error is also given. Several of the bounds with greatest practical consequence are worked out and illustrated. Repair distributions for which a lower bound on availability is easily computed are gamma (integer shape parameter), log normal, and Weibull. Finally, some simulation results for log normal repair versus gamma repair are given.     

差分跳频码性能检验研究

差分跳频是一种新的扩展频谱通信技术.在介绍差分跳频基本原理的基础上,将差分跳频的频率跳变过程建模成齐次马尔可夫链.分析了G函数的功能,重点讨论了差分跳频码性能的检验方法,包括不可约性、频隙滞留、均匀性和随机性检验,其中频隙滞留是首次提出应用于差分跳频码性能的检验.这些检验方法对于差分跳频G函数的设计具有一定的指导意义.     

磁性目标跟踪的后验克拉美罗下限分析与计算

为了求解磁性目标跟踪问题的后验克拉美罗下限(PCRB),提出了PCRB-GMSPPF算法。该算法利用高斯混合采样粒子滤波算法对目标状态的真实后验概率密度分布进行抽样,再通过蒙特卡洛积分法迭代求解每个观测时刻的Fisher信息矩阵,进而得出目标状态估计的PCRB;克服了基于PF算法求解PCRB过程中由于粒子退化和贫化问题造成不能从后验概率分布中正确抽样的缺点;在建立磁性目标跟踪的状态模型和观测模型的基础上进行仿真分析,将求解出的PCRB与采用GMSPPF及PF算法进行跟踪的均方根误差做对比,验证所提的PCRB-GMSPPF算法的有效性,结果表明:针对磁性目标跟踪问题,PCRB-GMSPPF算法较PCRB-PF算法具有更好的准确性,并可用于一般的非线性模型跟踪误差下限分析。     

空气深度预冷组合循环发动机吸气式模态建模及性能分析

针对空气深度预冷组合循环发动机——协同吸气式火箭发动机(Synergistic Air-Breathing Rocket Engine,SABRE),采用部件法对其进行建模,匹配计算得到吸气式模态下飞行走廊内其性能参数变化规律,并研究其高度速度特性。计算模型可信度较高,推力误差小于6%,能够较为准确地模拟SABRE吸气式模态的性能参数。结果表明:SABRE兼具火箭发动机大推力和航空发动机高比冲的特点,吸气式模态下比冲介于21 300~27 380 m/s,随着高度速度的增大,其推力比冲先增大后减小;SABRE利用预冷器将入口空气温度降低,可使其空域速域拓宽至25 km、5Ma,满足高超声速飞行的动力需求;发动机速度下限由压气机最大流量决定,速度上限则由氦气回路减压器工作限制条件决定。     

Distribution free bounds for service constrained (Q,r) inventory systems

A classical and important problem in stochastic inventory theory is to determine the order quantity (Q) and the reorder level (r) to minimize inventory holding and backorder costs subject to a service constraint that the fill rate, i.e., the fraction of demand satisfied by inventory in stock, is at least equal to a desired value. This problem is often hard to solve because the fill rate constraint is not convex in (Q, r) unless additional assumptions are made about the distribution of demand during the lead‐time. As a consequence, there are no known algorithms, other than exhaustive search, that are available for solving this problem in its full generality. Our paper derives the first known bounds to the fill‐rate constrained (Q, r) inventory problem. We derive upper and lower bounds for the optimal values of the order quantity and the reorder level for this problem that are independent of the distribution of demand during the lead time and its variance. We show that the classical economic order quantity is a lower bound on the optimal ordering quantity. We present an efficient solution procedure that exploits these bounds and has a guaranteed bound on the error. When the Lagrangian of the fill rate constraint is convex or when the fill rate constraint does not exist, our bounds can be used to enhance the efficiency of existing algorithms. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 635–656, 2000     

机动目标跟踪误差CRLB计算与分析

克拉美-罗下限(CRLB)作为参数估计所能达到的最低误差限,常被用来衡量算法估计性能的优劣程度。以转弯机动为例,研究了有源(主动)和无源(被动)两种观测条件下目标跟踪CRLB计算的一般方法,并通过矩阵理论分析了目标机动可能引起的CRLB突变的原因,为机动目标跟踪的算法性能评估提供了有效手段。最后给出了仿真算例。