chap9

travel guide to helsinki

如何从CSV、文本文件中读取记录波形 并返回波形数据 逐行读取文件内容 (How CSV, text file read and returns the waveform data recorded waveforms to read file contents line by line)

基于VSC-HVDC的多端柔性直流输电系统小信号模型及解耦控制 (The flexible multiterminal HVDC system based on VSC- HVDC small signal model and the decoupling control)

Calculate the normal vectors for each facet of a triangular mesh

2*2 mimo-ofdm using awgn channel

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).)

A New Approach to Fourier Synthesis With Application to Neural Encoding and Speech Classification

different edge detection

MATLAB与VC混合编程实习指导书，介绍了几种实用的在VC环境下调用Matlab中函数的方法(MATLAB and VC internship program guide book)

用matlab进行排队论仿真的经典论文，有兴趣的同学可以参考一下。(Matlab simulation carried out with the classic queuing theory papers, students who are interested can refer to.)