Novel cued search strategy based on information gain for phased array radar

A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.     

Fast motion estimation algorithm for H.264/AVC based on centered prediction

H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality. However, this comes at a cost in considerably increased complexity at the encoder and thus increases the difficulty in hardware implementation. The high redundancy that exists between the successive frames of a video sequence makes it possible to achieve a high data compression ratio. Motion estimation (ME) plays an important role in motion compensated video coding. A fast motion estimation algorithm for H.264/AVC is proposed based on centered prediction, called centered prediction based fast mixed search algorithm (CPFMS). It makes use of the spatial and temporal correlation in motion vector (MV) fields and feature of all-zero blocks to accelerate the searching process. With the initialized searching point prediction, adaptive search window changing and searching direction decision, CPFMS is provided to reduce computation in block-matching process. The experimental results show that the speed of CPFMS is nearly 12 times of FS with a negligible peak signal-noise ratio (PSNR) loss. Also, the efficiency of CPFMS outperforms some popular fast algorithms such as hybrid unsymmetrical cross multi-hexagongrid search and a novel multidirectional gradient descent search evidently.     

作战武器任务规划仿真系统原型的开发

针对复杂虚拟战场环境下的联合作战仿真,设计出了一套仿真方案。利用建模软件Maya、人机交互仿真软件Virtools及程序开发语言C#,开发出了该方案的一个原型。原型采用了根据模型精细度建模、模块化程序设计等优化设计方法。程序运行结果表明,该原型具有模型文件量小、仿真视觉效果佳、程序运行流畅及程序可修改性、可重用性较好等特点,其针对武器装备的作战规划仿真结果为联合作战环境下武器装备的效能评估提供了依据。

Abstract：

A simulation scheme was designed aiming at joint operations simulation in the comprehensive virtual combat environment which developed the prototype of this scheme, with modeling software Maya, human-computer interaction designing software Virtools, program developing language C#. The prototype applied optimum design methods like modeling according to models＇ fineness, modular program designing and so on. Based on the program running results, the prototype possessed such good features as lightweight modeling, good visual effects, fluent program operation, better modifying and reusing properties, etc. The simulation results for weapon equipment mission planning provide reference to weapon equipment effectiveness evaluation in the joint operational environment.     

基于智能虚拟环境的地铁站台仿真系统

实现了一个用于列车驾驶培训的地铁站台仿真系统.系统由一个可被感知的站台虚拟环境和虚拟乘客系统组成.站台环境由静态场景、动态场景两部分组成,可在用户控制下发生变化.虚拟乘客通过感知站台环境的变化做出行为判断与动作.乘客仿真模型采用分层结构,分别实现环境感知、决策、行为选择、动作实现与实时绘制.目前,该系统已用于地铁列车仿真器,成为培训司机站台操作的工具.     

Efficient combination rule of Dezert-Smarandache theory

The Dezert-Smarandache theory （DSmT） is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in data fusion and object recognition. However, there exist shortcomings in its combination rule. An efficient combination rule is presented, that is, the evidence＇s conflicting probability is distributed to every proposition based on remaining the focal elements of conflict. Experiments show that the new combination rule improves the reliability and rationality of the combination results. Although evidences conflict another one highly, good combination results are also obtained.     

一种基于通用DSP的快速余弦变换算法

在对传统快速DCT算法进行分析的基础上 ,充分考虑到通用DSP乘加速度相同等指令特点 ,并且结合DCT变换的性质 ,同时还考虑了对于通用DSP实现相当重要的存取操作的因素 ,提出了一种新的基于通用DSP的快速余弦变换 (FDCT)算法 ,以使总操作数最少。与传统快速DCT相比 ,速度有了明显的提高 ,并且易于实现。给出了该算法在数码相机中的实现结果     

一种混沌神经网络及其在优化计算中的应用

研究了一种具有混沌特性的神经网络 ,该网络具有瞬态混沌响应 ,类似于Hopfield网络的结构 ,但有比Hopfield网络更加丰富的动力学特征、更强的全局搜索能力。通过把混沌动力学与收敛动力学相结合 ,使网络逐渐由混沌神经网络向Hopfield网络过渡 ,达到控制混沌的目的 ,并且提供一个在全局最优解附近的初值 ,有效地解决了Hopfield网络的局部极值问题。该网络模型可以用来解决复杂的非线性优化问题。     

基于质量评价技术的多信道语音选优决策系统

在分析远距离多信道同源语音信道特性的基础上 ,用若干特征参数来表征信道传输的语音质量并建立了语音质量客观评价模型 ,结合人的听觉特性等因素开发出一种基于语音质量客观评价技术的优质语音信道选优决策系统。该系统能够确保语音通信始终在最佳信道上 ,且在切换过程中无跳变感觉 ,不影响听觉效果 ,现已在实际工程中得到成功运用并取得了满意效果。     

基于神经网络的一类非线性系统的变结构控制

在已知名义系统的基础上 ,将小脑关节模型控制器 (CMAC)神经网络用于一类状态反馈可线性化的多输入多输出连续时间非线性系统的变结构控制中。利用自适应技术估计了估计误差的大小 ,减小了系统的不确定性 ,并利用模糊控制技术调整了变结构增益 ,改善了系统的性能。在很弱的假设条件下 ,应用Lyapunov稳定性定理证明了闭环系统内的所有信号为均匀最终有界。算法在导弹控制系统中的应用进一步证明了本文方法的有效性。     

生产作业计划调整的优先调度算法研究

本文基于生产作业计划生成的优先调度法,提出了针对生产作业计划调整的机床优先调度算法和工件优先调度算法。在机床优先调度算法中,设计了机床优先调度算法的步骤。而在工件优先调度算法中,利用归纳学习方法,研究了面向生产系统状态的生产作业计划调整方法。