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MATLAByuyanchengxuji

于 2010-05-26 发布 文件大小:141KB
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  MATLAB语言常用算法程序集,希望可以对大家有用!!!!1(MATLAB language commonly used algorithm for the assembly, hoping to be useful for everyone! ! ! ! 1)

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  • ForK1
    我们的目的是将一个分数拆分成若干个分子是1分母是正整数的分数之和的形式。例如2/3可以拆分成1/2+1/6的形式。这里不考虑顺序,比如1/6+1/2和1/2+1/6相同。 输入p, q, a, n, 其中p/q为分数,对这个分数进行拆分,要求拆分的分数个数不能多于n个,所有分母的乘积不能大于a。求有多少种拆分方法? 输入:最多200组数据。在每行中都有四个数分别表示p, q, a, n,之间以空格隔开,并且满足p,q<=800,a<=12000,n<=7,最后以四个0做为输入的结束。 输入示例: 2 3 120 3 2 3 300 3 0 0 0 0 输出示例: 4 7 (Our aim is to split a fraction into a number of elements is a denominator is a positive integer fraction of the sum of form. For example, 2/3 can be split into 1/2+1/6 form. Not considered here, the order, such as 1/6+1/2 and 1/2+1/6 of the same. Input p, q, a, n, where p/q as a fraction of this split scores require no more than the number of split points n-all the product of the denominator can not be larger than a. How many kinds of demand split method? Input: Up to 200 sets of data. In each line has four numbers indicate the p, q, a, n, separated by a space between, and meet the p, q < = 800, a < = 12000, n < = 7, the end, four 0 as the input end. Input Example: 2,312,032,330,030,000 sample output: 47)
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    In order to minimize power losses caused by high current and improve the voltage profile in the network distribution, the introduction of dispersed generations also called productions decentralized in distribution network (DG) plays an important role. The installation of DGs directly affects the power requested or purchased
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    2007-12-11 14:20:23下载
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    支持向量机是用于分类与回归的技术。由于其自身的诸多缺点,如无法获得概率输出,需要估计一个误 差参数C,以及必须使用Mercer 核函数等。相关向量机算法,克服了SVM 上述缺点,RVM 能获得与SVM 相比拟的推 广性能,并且更为稀疏。在此基础上,文中介绍了一种RVM 回归用于分类的新分类方法,用RVRC 来表示。并通过 实验证明了它的可行性。(Support vector machines for classification and regression techniques. Due to its many shortcomings, such as the probability that the output can not be obtained, need to estimate an error parameter C, and the need to use Mercer kernel function and so on. Relevance vector machine algorithm to overcome these shortcomings of SVM, RVM and SVM can be obtained comparable to promote performance and more sparse. On this basis, the paper introduces a RVM regression was used to classify new classification method, RVRC to represent. And through experiments proved its feasibility.)
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  • sparsefull
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    2010-10-29 19:49:36下载
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