适于复杂信息融合系统的近似联合概率数据关联算法

文中在B.Zhou提出的直接概率计算(DC)和近似概率计算(AC)算法基础上提出了一种新的近似多传感器多目标联合概率数据关联算法。近似概率法是以一个目标为中心的近似聚为构造互联事件的起点，并在计算中将DC和AC结合得到的一种全邻的点迹—航迹关联算法，它能有效地提高目标点迹—航迹的关联正确率，在计算时耗上较完全联合概率法快得多，能满足工程中实时性的要求。将其在杂波下目标密集、航迹复杂的数据融合系统中进行实验，对关联正确率，关联耗时等与最近邻法进行了比较，效果较好。     

四像限光电探测器的逆光路模型

讨论了探测器的观测空间转换问题。介绍了一种用神经网络建立的从电信号特征参数到光路参数的光路反模型的方法。根据四像限光电探测器的两路输出信号在过零点附近时间段的逼近直线的斜率和截距与光电探测器的三自由度安装位置，以及探测器光敏面的离焦量的特殊关系，建立了称之为模型1的四像限光电探测器光路逆模型。同时以探测器特定时刻输出电压作为观测量，建立了称之为模型2的探测器光路逆模型。并以探测器光敏面的离焦量为例，给出了两个模型的实测值和模型1的重复性测试值。重复性测试值表明，模型1的最大重复测试误差只有O．015mm。实测结果证明，模型1的检测精度可以达到微米级，而用探测器特定时刻输出电压建立的逆模型的检测精度只能达到毫米级，这证明用探测器输出信号过零点附近时间段的逼近直线参数作为观测信号优于用输出信号特定时刻电压作为观测信号。     

一种模糊自适应BP算法的研究

本文在人工神经网络中引入模糊集理论，提出一种模糊自适应ＢＰ算法。通过奇偶校验和ＥＥＧ异常波形检测两上实例，验证了新算法在学习速度与性能上都优于传统的ＢＰ和虎法。     

Acoustic detection and classification of river boats

We present a robust algorithm to detect the arrival of a boat of a certain type when other background noises are present. It is done via the analysis of its acoustic signature against an existing database of recorded and processed acoustic signals. We characterize the signals by the distribution of their energies among blocks of wavelet packet coefficients. To derive the acoustic signature of the boat of interest, we use the Best Discriminant Basis method. The decision is made by combining the answers from the Linear Discriminant Analysis (LDA) classifier and from the Classification and Regression Trees (CART) that is also accompanied with an additional unit, called Aisles, that reduces false alarms rate. The proposed algorithm is a generic solution for process control that is based on a learning phase (training) followed by an automatic real time detection while minimizing the false alarms rate.     

基于参数BP网络的自整定PID控制在柔性结构控制中的应用

针对大射电望远镜(LT)悬索粗调系统为一非线性慢时变大滞后柔性系统的特点,提出用参数BP神经网络自整定PID控制器来实现馈源轨迹跟踪策略.仿真研究表明,该控制算法可以很好地满足馈源系统轨迹跟踪高精度要求.     

Roles of N?→NN and πN→? Reactions in Heavy-Ion Collisions at Intermediate Energies

Within the framework of the isospin-dependent transport model, the roles of the reactions N? → NN and πN→ ? are investigated through simulating heavy-ion collisions at 1000 MeV/nucleon. The absorption process N? → NN plays an important role for heavy impact systems and small impact parameters than for light impact systems and large impact parameters. The resorption process πN→ ? is of importance for heavy impact systems and large impact parameters than for light impact systems and small impact parameters. Thus the influences of the reaction N? → N N(πN→ ?) on pion production dynamics can be neglected in heavy-ion collisions for smaller(larger) impact parameters and light systems. It is the reaction πN→ ? that causes the anti-correlation of pions and nucleons in the rapidity dependence of the directed flow.     

基于e-修正神经网络的直接自适应控制设计

针对一般非线性不确定系统设计了一种e-修正神经网络直接自适应控制方法。首先采用虚拟控制量的方法,并将其分解成参考模型输出、线性动态补偿输出与神经网络自适应输出三项;然后针对传统σ-修正神经网络在权值更新时的不足,设计了一种基于e-修正方法的权值自适应更新律,并设计了输出反馈误差观测器用以对神经网络进行训练;最后对基于σ-修正与e-修正两种权值自适应更新律进行仿真对比。仿真结果表明基于e-修正神经网络方法在跟踪误差、不确定性逼近等效果上均优于基于σ-修正神经网络方法。     

An Extended Chiral SU(3) Quark Model

The chiral SU(3) quark model is extended by including the vector meson exchanges to describe the short range interactions. The phase shifts of NN scattering are studied in this model. Compared with the results of the chiral SU(3) quark model in which only the pseudo-scalar and scalar chiralfields are considered, the phase shifts of 1 So wave are obviously improved.