Constrained NSGA2

FEM solution for microstrip

这个是空域MUSIC算法和MVDR算法。采用8阵元的均匀圆阵(This is the airspace MUSIC algorithm and MVDR algorithm. 8 element uniform circular arrays)

实现低通，高通，带通的不同类型滤波器，并用几个基本的函数进行了验证(Low pass, high pass, the different types of band-pass filter, and a few basic functions were verified)

本书详细介绍了用Maple和MATLAB解决科学计算问题，有很多的实例供大家学习 。(The book details the use of Maple and MATLAB to solve the issue of scientific computing, there are many examples of learning for everyone.)

借助于MATLAB GUI模拟甚高频ACARS系统的下行数据链(The downlink data chain of the high frequency ACARS system is simulated with GUI MATLAB.)

针对实际工业生产中常见的多输入多输出时滞过程, 构造多变量Smith预估控制结构, 提出基于对象模 型伴随矩阵的解耦器设计方法. 通过对解耦后对象的幅频和相频特性分析, 获得对象的简化一阶数学模型. 根 据Smith预估控制结构闭环特征方程的特点, 利用Butterworth滤波器极点配置的原理, 对解耦后的多变量时滞过程 设计PI控制器. 结合实际过程中常见的不确定性, 分析了控制系统保证鲁棒稳定性的充要条件. 最后以实例验证了 本文所提方法的优越性.(The decoupling Smith control method is presented for multi-input-multi-output system with time-delays which are often encountered in practical engineering. A new method for designing the decoupler based on the adjoint matrix of the multivariable system model with time-delays is proposed. By analyzing the amplitude-frequency and phasefrequency characteristics of the decoupled model, the decoupled model is reduced to a first-order model with time-delay. According to the closed-loop characteristic equation of Smith predictor structure, a PI controller is developed by using the principle of pole assignment for Butterworth filter. Sufficient and necessary conditions for robust stability are derived for adaptive and multiplicative uncertainties commonly occurred in practice. Simulation results show the superiority of the proposed method.)

a Matlab Programme to simulate the cooperative communication technique AF amplify and forward between tow users and a destination

本书介绍matblab与c，c++混合编程，适合c和matlab有一定基础的同学参阅(This book describes matblab and c, c++ mixed programming for c and matlab students see there is some basis)

粒子群优化最优路径算法，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优(Similar to simulated annealing (SA), particle swarm optimization (PSO) optimizes the optimal path by iteratively searching for the optimal solution from a random solution. It also evaluates the quality of the solution by fitness, but it is simpler than the genetic algorithm rules. It does not have the crossover and Mutation operations of genetic algorithm. It finds the global optimum by following the best values currently searched.)

Tool to load waveforms into a agilemt esg signal generator