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匈牙利算法,求解二分图最大匹配的一个时间复杂度与程序复杂度折中的算法-Hungary algorithm to solve the greatest two minutes map matching a time complexity and the complexity of program compromise Algorithm
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对图进行匹配的算法-right map Matching Algorithm
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任意图的最大匹配算法，值得一学。毕竟各位不是只要会会匈牙利算法的那种人吧？-arbitrary map of the maximum matching algorithm, it is worth a study. After all, you would not say that the kind of Hungary algorithm people? Ha ha
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source code for Stereo matching algorithm
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双目视觉的深度图立体匹配算法改进Binocular stereo vision matching algorithm to improve the depth map-Binocular stereo vision matching algorithm to improve the depth map
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《大话数据结构》主要内容包含：数据结构介绍、算法推导大O阶的方法；顺序结构与链式结构差异、栈与队列的应用；串的朴素模式匹配、KMP模式匹配算法；二叉树前中后序遍历、赫夫曼树及应用；图的深度、广度遍历；最小生成树两种算法、最短路径两种算法；拓扑排序与关键路径算法；折半查找、插值查找、斐波那契查找等静态查找；稠密索引、分块索引、倒排索引等索引技术；冒泡、选择、插入等简单排序；希尔、堆、归并、快速等改进排序-" Westward the data structure," the m
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selforganising map for the matching algorithm for the biometric appilcations enroll ment
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A Map Matching Algorithm wrote in C-A Map Matching Algorithm wrote in C++
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基于一种改进的遗传地图匹配算法，将Marchal算法和遗传算法结合起来，本源代码基于C++开发，包括了完整的实验数据和算法实现。-Based on an improved genetic map-matching algorithm, Marchal and genetic algorithms to combine source code is based C++ development, including the full experimental data and algorithms.
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最大似然（ML）准则和最大后验概率（MAP）准则，粒子图像分割及匹配均为自行编制的子例程，通过matlab代码，车牌识别定位程序的部分功能，包含了阵列信号处理的常见算法，是学习PCA特征提取的很好的学习资料。- Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Particle image segmentation and matching subroutines themselves are p
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最大似然（ML）准则和最大后验概率（MAP）准则，直线阵采用切比学夫加权控制主旁瓣比，使用matlab实现智能预测控制算法，迭代自组织数据分析，粒子图像分割及匹配均为自行编制的子例程，有CDF三角函数曲线/三维曲线图，连续相位调制信号(CPM)产生。- Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Linear array using cut than learning laid upon t
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最大似然（ML）准则和最大后验概率（MAP）准则，匹配追踪和正交匹配追踪，脉冲响应的相关分析算法并检验。- Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Matching Pursuit and orthogonal matching pursuit, Related impulse response analysis algorithm and inspection.
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匈牙利算法，用于求解二分图的匈牙利算法，里面包含量两种求解方法，希望对大家有用。(Hungarian algorithm can be used to solve the bipartite matching problem , but it requires the bipartite graph to be completely symmetric. Hence we need to transform the original non-symmetric binary map matchi
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