mpc_2

说明：  机械工程设计中对于连杆机构的运动分析的相关程序(Mechanical Engineering Design movement for linkage analysis procedures)

离散对称信道的信道容量的计算离散对称信道的信道容量的计算(Discrete symmetric channel is the channel capacity of computing discrete symmetric channel calculation of channel capacity)

被控对象为三阶系统，可以根据M的参数设置演示低通滤波效果，控制部分采用PID控制。(Third-order system for the controlled object, you can set the parameters according to M shows low-pass filtering effect, the control part of the PID control.)

基于SVR的线性系统逆模型辨识建模及校验的仿真程序，由于辨识信号采用的都是随机信号，不是数值固定的信号，所以程序每次运行的结果都可能有所不同。(Linear inverse model identification modeling and verification system simulation program based on SVR identification signal are random signal, not the value of the fixed signal, so the program each time you run the results are likely to differ.)

用matlab编写的车牌识别的源程序，可以准确定位到车牌(Prepared using matlab source license plate recognition, can accurately locate the license plate)

利用阈值函数进行心音去噪的程序，利用了改进的双参数可调阈值函数(A threshold function is used to denoise the heart sound, and the improved dual parameter adjustable threshold function is used.)

说明：  多目标遗传算法是NSGA-II[1]（改进的非支配排序算法）,该遗传算法相比于其它的多目标遗传算法有如下优点：传统的非支配排序算法的复杂度为 ，而NSGA-II的复杂度为 ，其中M为目标函数的个数，N为种群中的个体数。引进精英策略，保证某些优良的种群个体在进化过程中不会被丢弃，从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子，不但克服了NSGA中需要人为指定共享参数的缺陷，而且将其作为种群中个体间的比较标准，使得准Pareto域中的个体能均匀地扩展到整个Pareto域，保证了种群的多样性。（消除了共享参数）。(Multi-objective genetic algorithm is nsga-ii [1] (improved non-dominant sorting algorithm), which has the following advantages compared with other multi-objective genetic algorithms: the complexity of the traditional non-dominant sorting algorithm is, while the complexity of nsga-ii is, where M is the number of objective functions and N is the number of individuals in the population.The introduction of elite strategy to ensure that some good individuals in the evolutionary process will not be discarded, thus improving the accuracy of the optimization results.The comparison operator of crowding degree and crowding degree not only overcomes the defect that NSGA needs to specify the Shared parameter artificially, but also takes it as the comparison standard between individuals in the population, so that individuals in the quasi-pareto domain can uniformly expand to the whole Pareto domain, ensuring the diversity of the population.(eliminating Shared parameters).)

This is the code for IRIS recognition by masek.It includes all the files including description of MASEK thesis.

numerical analysis code

comparison of disturbance included fuzzy and kalman