三维声场边界元法几乎奇异积分问题分析

以三维声场问题为例,提出一种准确计算高阶单元几乎奇异积分的半解析算法.首先分析高阶单元几何特征,构造近似几何量,然后应用扣除法,将奇异积分核函数分解为规则核函数与近似几何量表达的奇异核函数.规则核函数积分采用常规Gauss数值积分计算,奇异核函数积分采用半解析算法计算.给出三维声场内问题和外问题经典算例,计算了近边界点的声压,结果证明本文半解析算法的有效性和准确性.     

激光传输模拟中基于衍射过程FFT算法的参量优化

为实现采用相位屏法正确模拟准直激光束经湍流大气的传输特性,根据湍流特性、抽样定理以及两屏间衍射过程FFT算法本身所决定的相邻两屏网格间距之间的关系,得出相位屏间距和网格间距确定网格数目最优取值的解析表达式,数值模拟高斯光束经自由空间和湍流大气传输的远场分布,网格数目取解析式求得的最优值848时,光束经自由空间传输的模拟结果与ABCD定律求得的解析结果完全一致;网格数目取836或860时,等效于光束通过偶数相位屏时被正透镜或负透镜阵列会聚或发散,削弱或夸大湍流大气对光束的影响,模拟结果出现严重偏差。     

Blocking probability analysis of pruned optical banyan networks on vertical stacking scheme with extra banyan planes

Vertically stacked pruned optical banyan networks with extra planes (in short, EP-VSOB networks) have lower switch count and optimal time complexity (O(log₂ N)) for routing N input requests. However, blocking probability is relatively higher than that of a VSOB networks using regular banyan planes. In the EP-VSOB architecture, the number of pruned planes has always been considered as , and a few extra planes (regular banyan) have been added with these pruned planes. In this paper we present the results of blocking analysis of a more generalized architecture in which the number of pruned planes can be 2^x, where x ? 0 in addition to the variable extra planes. This generalization helps us make a compromise between different constraints and performance metrics. Our simulation results show that for some given performance requirements (e.g. cost, speed or blocking probability) we can choose a network that has lower switch count compared to -plane pruned crosstalk-free optical banyan networks. For example, to ensure blocking probability <0.02, previously we would chose a pruned network of 32 pruned planes and 1 extra planes (a regular banyan); however, our simulations results show that a network of 16 pruned planes and 2 extra planes is enough to ensure the same performance. It is notable that, the hardware cost decreases by 28.65% in this new combination of pruned and extra planes. We believe our results will provide more flexibility in choosing a particular EP-VSOB network satisfying given requirements.     

雷达回波资料反演海洋波导中观测值权重的确定

提出采用一种与电磁波传播损耗相类似的指数衰减形式来描绘观测值权重随距离的变化,结合标准的统计反演算法来测试不同的观测值权值对反演速度与精度的影响.结果表明,指数衰减形式能较好地描绘观测值权值随距离的变化情况;其中衰减指数的选取是关键.合理地选取衰减指数可较好地改进反演的速度与精度.对于不同频率的电磁波,最优衰减指数是各不相同的. 关键词： 海洋波导 观测值权重 衰减指数 反演算法     

基于多项式模型的混沌系统平方和算法脉冲控制

针对一大类混沌系统,提出一种新颖的基于多项式模型的脉冲控制方法.首先,建立系统的多项式模型.其状态方程由系统状态的多项式矩阵与其单项式组成列向量构成.与其他建模方法相比,该方法不必使用任何预制的假设.其次,提出基于平方和优化算法的脉冲控制方法,使得混沌系统的状态能够实现渐近稳定.基于该算法的脉冲控制与基于线性矩阵不等式凸优化算法的结果相比,能得到更大的脉冲间距,从而可以使用较少的控制能量实现同样的控制效果.最后,仿真实验结果验证了本方法的有效性.     

Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm

Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm is proposed, and a fitness function is provided. Simulations are conducted using the adaptive niche immune genetic algorithm, the simulated annealing algorithm, the quantum genetic algorithm and the simple genetic algorithm, respectively. The results show that the adaptive niche immune genetic algorithm performs better than the other three algorithms in terms of the multi-user cognitive radio network resource allocation, and has quick convergence speed and strong global searching capability, which effectively reduces the system power consumption and bit error rate.     

遗传算法结合正则化方法反演海洋大气波导

针对正则化方法在解决实际反演问题时既能克服问题的不适定性又可以很大程度上抑制噪声和误差的传播, 本文提出了利用遗传算法结合正则化方法的新算法, 在遗传算法适应度函数中引入正则化项来反演波导参数; 然后对算法进行仿真试验, 结果表明新算法与传统遗传算法相比具有较高的反演精度, 并指出当噪声误差小于10%时, 算法具有较强的“去噪”性能; 最后利用机载雷达在Wallops岛探测的海表面处局部回波资料进行反演试验, 将反演结果与实测大气折射率廓线进行比较, 说明该算法的有效性. 新方法为海洋大气波导反演研究提供了一种新思路.     

光学材料光学均匀性的波长调谐两步绝对测量法

光学均匀性是光学材料的重要指标,目前高精度的测量方法一般采用绝对测量法,而该方法步骤繁琐,容易受环境影响。根据波长移相干涉仪的移相特点,提出了测量光学材料光学均匀性的波长调谐两步绝对测量法。该方法在波长移相干涉仪中通过平行平板放入测量和空腔测量两个步骤得到平行平板的光学均匀性。在模拟仿真验证方法的正确性后,进行了实验研究,并与传统的绝对测量法的测量结果进行比较。结果表明,波长调谐两步绝对测量法可用于测量平行平板的光学均匀性,且测量步骤简单,精度较高。     

基于多种群混沌遗传神经网络的模拟电路故障诊断

针对标准遗传算法优化BP神经网络收敛慢,易陷入局部最优的问题,提出了改进的多种群协同进化遗传算法,该算法改变了以往的随机初始化方法,采用了附加混沌扰动的tent映射初始化均匀分布的种群,提高了初始解的质量;每个种群采用自适应交叉率和变异率,引入移民算子实现种群间的横向联系;算法通过多种群的协同进化和种群间的个体移植提高了算法的搜索均匀性和效率;仿真实验表明该算法误差小,收敛速度快,诊断正确率高,较好地解决了模拟电路的软故障诊断问题。     

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation.It treats the DFT as a black box and models the error through external statistical information.As a demonstration,the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides.Through the AGANN correction,the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set.For comparison,the neural network approach reduces the mean value to 2.56%.And for the common combinational approach of genetic algorithm and neural network,the value drops to 2.15%.The multiple linear regression method almost has no correction effect here.