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pdco5

于 2020-06-23 发布 文件大小:4817KB
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  内点优化法,stanford大学The Systems Optimization Laboratory 开发(Interior point,stanford university The Systems Optimization Laboratory)

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  • quanguoshumo
    2008年全国大学生数学建模获奖论文所需程序代码,其中有较详细的matlab编程,应该有些用处吧(Mathematical Contest in Modeling 2008, papers required for award-winning code, including more detailed matlab programming, it should be of some use)
    2010-09-07 13:26:10下载
    积分:1
  • LMS
    最小均方(LMS)自适应算法就是一中已期望响应和滤波输出信号之间误差的均方值最小为准的,依据输入信号在迭代过程中估计梯度矢量,并更新权系数以达到最优的自适应迭代算法。LMS算法是一种梯度最速下降方法,其显著的特点是它的简单性。这算法不需要计算相应的相关函数,也不需要进行矩阵运算。(Minimum mean-square (LMS) adaptive algorithm is that one has to respond to the expectations and filtering the output signal of the mean square error between the value of the minimum-based, based on the input signal is estimated in the iterative process of gradient vector, and to update the weights in order to achieve the most Adaptive iterative algorithm gifted. LMS algorithm is a steepest descent gradient method, and its significant features is its simplicity. This algorithm does not require calculation of the corresponding correlation function, nor the need for matrix calculation.)
    2008-05-26 12:05:15下载
    积分:1
  • the_min_cost
    本程序用来求有向网络中的最大流和最小费用的问题。这里最小费用是在可能有多个最大流的基础上优化得到的。故前提条件是最大流,如果没有没有最大流,可以不运输,成本为0,那就没有意义了。(This program used to beg for the maximum flow to the network and the minimum cost. Here is the minimum cost in May have multiple maximum flow based on optimization get. So premise condition is maximum flow, if no no maximum flow, can not transport, the cost of 0, that is no sense. )
    2010-12-03 19:41:13下载
    积分:1
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    说明:  按FPE定阶的 源程序:fpe.cpp M序列:M序列.txt 白噪声:Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数,再用fpe方法判断模型的阶次。 程序运行结果如下: n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出,当n=5时,fpe值最小,所以这时的模型阶次和参数估计值为最优结果: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)
    2008-09-12 01:14:14下载
    积分:1
  • w1
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    2014-01-29 20:44:40下载
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    2018-11-10 20:25:07下载
    积分:1
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    2010-06-23 20:53:39下载
    积分:1
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