NpIca-v1.2

说明：  一个经典的宽带多位sigma delta调制器设计，较为好用(More than a classic sigma delta modulator broadband design, the more useful)

TSP问题模拟退火算法MATLAB源码,已通过调试(TSP problem simulated annealing algorithm MATLAB source code, has passed the commissioning)

UCP problem solving Using Dynamic Problem by Maninder Kaur and Vikram Kumar

Induction machine Rotoric fault

流形学习算法LTSA的线性化方法，在基因分类聚类中得到了应用，可以将新样本线性地投射到低维空间。(LTSA manifold learning algorithm of the linearization method, clustering in gene classification has been applied to new samples can be projected onto the linear and low-dimensional space.)

Implementation of a low pas filter. Signals processing.

是关于大学matlab课堂做的作业，几乎每个学生都必须在学期末要提交的！学子们，加油！(About University matlab classroom to do the job, almost every student must be at the end of the term you want to submit the! Students who, come on!)

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).)

proper inverter is simulated

this describes matlab us in image processing.