turbo_codes

粒子群优化(PSO)算法是计算智能领域，除蚁群算法外的另外一种基于群体智能的优化算法。(Particle Swarm Optimization)

Basics of Imperialist CompetitveAlgorithm-Global Optimization Strategy using matlab

Using a progressive intuitive/mathematical approach, this introduction to computer vision provides necessary theory and examples for practitioners who work in fields where significant information must be extracted automatically from images-- including those interested in multimedia, art and design, geographic information systems, and image databases, in addition to the traditional areas of automation, image science, medical imaging, remote sensing and computer cartography. The book provides a basic (Computer Vision- Linda Shapiro.pdf)

THIS IS SINGLE MACHINE INFINITE BUS SYSTEM

可以为多种非线性方程组的求解方法生成函数模板(For a variety of methods for solving nonlinear equations generated function template)

说明：  有n个整数，使其前面各数顺序向后移m个位置，最后m个数变成最前面的m个数 (Have n integers, to move back in front of the order m of the number of positions, finally becoming the foremost m m the number of number of)

霍夫曼编码，随机生成10个概率，和为1，用霍夫曼编码输出，采用map函数(Huffman coding, the probability of a randomly generated 10, and 1, with the Huffman code output, the use of map functions)

Orthogonal Least Squares Estimate on a plane, in the simple case of a linear equation, is in fact a problem that can be easily solved analytically with no approximation (see pdf file for detailed explanation). Notice that in the general multidimensional case, an analytical solution may not exist (although Mr. Carr s function is an efficient approximation of the solution).

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).)

高等数学、线性代数及浙江大学概率论答案打包.rar(Advanced Mathematics, Zhejiang University, linear algebra and probability theory packaged answers. Rar)