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artificial

于 2010-01-26 发布 文件大小:8070KB
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  Matlab code for The Labor-Supply Elasticity and Borrowing Constraints: Why Estimates are Biased 1

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  • kalman
    一般KF和UDUKF的比较源程序代码,运行文件夹中的result.m文件。(General comparison of KF and UDUKF source code, run the file in a folder result.m file.)
    2010-11-21 00:32:37下载
    积分:1
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    2010-05-07 20:04:38下载
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    2014-09-11 13:14:45下载
    积分:1
  • 2812
    TI 下载的矢量控制算法,里面包含各种函数,还有PDF文件。(Download the TI vector control algorithm, which contains a variety of functions, and the PDF file.)
    2013-11-07 22:25:41下载
    积分:1
  • sg
    说明:  这是一个短时傅里叶变换的程序,特别详细,超级好用(This is a short-time Fourier transform procedure, particularly detailed, super-easy)
    2013-05-23 10:15:44下载
    积分:1
  • drtoolbox
    降维工具箱,有PCA,LDA等等比较全面,里面有说明。(Dimensionality reduction toolbox, PCA, LDA, and so a more comprehensive, there are instructions.)
    2014-01-12 20:05:30下载
    积分:1
  • ber
    THIS FILE DESCRIBE THE CALCULATION OF BIT ERROR RATE (BER) OF A MODULATED SYSTEM AND THE PLOT OF THE BER WITH SIGNAL TO NOISE RATIO (SNR) TO EVALUATE THE SYSTEM BEHAVIOR
    2014-01-17 15:24:06下载
    积分:1
  • Two-subspace-algorithms-
    两种子空间辨识的闭环方法 两种子空间辨识的闭环方法 (Two closed-loop subspace identification method of the two closed-loop subspace identification methods)
    2014-06-12 16:56:21下载
    积分:1
  • GAforPathPlaning
    说明:  采用栅格对机器人的工作空间进行划分,再利用优化算法对机器人路径优化,是采用智能算法求最优路径的一个经典问题。目前,采用蚁群算法在栅格地图上进行路径优化取得比较好的效果,而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。 利用遗传算法处理栅格地图的机器人路径规划的难点主要包括:1保证路径不间断,2保证路径不穿过障碍。 用遗传算法解决优化问题时的步骤是固定的,就是种群初始化,选择,交叉,变异,适应度计算这样,那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve. The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles. The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.)
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    积分:1
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