基于神经元网络的燃油锅炉烟气氧含量的软

针对目前各种氧含量检测仪表在运行过程中的可靠性差、使用寿命短及价格昂贵等诸多不足，通过探寻锅炉运行中的其他参数与烟气氧含量的映射关系，建立ＢＰ神经元网络，提出了燃油锅炉烟气氧含量的软测量方法。结果表明，其精度完全达到了设计要求。     

遗传算法在混合H_2/H_∞优化控制设计中的应用

介绍了现已成为关键智能计算之一的一种新的全局优化搜索算法—遗传算法，并探讨了在混合Ｈ２／Ｈ∞最优指标下优化控制设计中的应用。其最大特点是：本质并行、全局优化，它不要求目标函数连续和可微，比梯度法和随机搜索算法更适合于ＰＩＤ混合Ｈ２／Ｈ∞优化问题。     

对有梭织机探纬诱导及纬停装置的改进

探讨了用两种光电检测装置来代替目前有梭织机上探纬诱导机构和纬停装置，为织机的改造提供了一种新的途径     

确定局部结构已知的半群的一种算法

给出了确定局部结构已知的有限半群的推理法则，提出了一种新的计算机算法。     

神经网络控制器用于永磁电机的伺服驱动

提出用一种遗传算法（ＧｅｎｅｔｉｃＡｌｇｏｒｉｔｈｍ，简称ＧＡ）训练的多层神经网络结构（ＮＮ），并把它用于交流直线永磁同步电动机（简称ＬＰＭＳＭ）的辩识与控制，使其运行在伺服驱动环境．ＮＮ可随时辩识被控系统的动态待性，而不需要ＬＰＭＳＭ的精确的数学模型．仿真结果令人满意     

加速基因方法在最大流量频率曲线参数估计中的应用

基因方法是基于自然选择和自然基因机制的并行随机自适应工程模型参数全局优化估计的通用数值方法。它不限制模型结构、优化准则、被估参数的数目、约束条件等，已开始广泛用于各种工程模型的优化设计之中。文中对它的原理、步骤、特点进行初步探讨，并针对基因方法的弱点，作者提出予以改进的加速基因方法，后者在最大流量频率曲线参数估计中得到成功应用     

加密算法与单片机编程

结合单片机编程信息的特点，对各种加密算法在单片机编程中的应用进行了研究     

一种阵列信号超分辨率快速算法

提出了一种阵列信号超分辨率快速算法，并分析了它的收敛速度。这种算法基于协方差矩阵的特征值平移和矩阵的幂迭代，而不需要矩阵求逆。它的收敛速度快，一般只需几次迭代就能收敛，且算法结构简单，易于实现。     

Numerical inversion of multidimensional Laplace transforms by the Laguerre method

Numerical transform inversion can be useful to solve stochastic models arising in the performance evaluation of telecommunications and computer systems. We contribute to this technique in this paper by extending our recently developed variant of the Laguerre method for numerically inverting Laplace transforms to multidimensional Laplace transforms. An important application of multidimensional inversion is to calculate time-dependent performance measures of stochastic systems. Key features of our new algorithm are: (1) an efficient FFT-based extension of our previously developed variant of the Fourierseries method to calculate the coefficients of the multidimensional Laguerre generating function, and (2) systematic methods for scaling to accelerate convergence of infinite series, using Wynn's ε-algorithm and exploiting geometric decay rates of Laguerre coefficients. These features greatly speed up the algorithm while controlling errors. We illustrate the effectiveness of our algorithm through numerical examples. For many problems, hundreds of function evaluations can be computed in just a few seconds.     

Rough Terrain Autonomous Mobility—Part 1: A Theoretical Analysis of Requirements

A basic requirement of autonomous vehicles is that of guaranteeing the safety of the vehicle by avoiding hazardous situations. This paper analyses this requirement in general terms of real-time response, throughput, and the resolution and accuracy of sensors and computations. Several nondimensional expressions emerge which characterize requirements in canonical form.The automatic generation of dense geometric models for autonomously navigating vehicles is a computationally expensive process. Using first principles, it is possible to quantify the relationship between the raw throughput required of the perception system and the maximum safely achievable speed of the vehicle. We derive several useful expressions for the complexity of terrain mapping perception under various assumptions. All of them can be reduced to polynomials in the response distance.The significant time consumed by geometric perception degrades real-time response characteristics. Using our results, several strategies of active geometric perception arise which are practical for autonomous vehicles and increasingly important at higher speeds.