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于 2018-03-10 发布 文件大小:131KB
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下载积分: 1 下载次数: 13

代码说明:

  粒子滤波算法的matlab代码,目标跟踪轨迹预测(Particle Filter Algorithm Target tracking trajectory prediction)

文件列表:

code\chap1\本章是绪论,没有程序.txt, 0 , 2017-07-11
code\chap2\main1.m, 869 , 2017-07-11
code\chap3\3.5.1\baby.jpg, 53672 , 2017-07-11
code\chap3\3.5.1\genUnifNoise.m, 1106 , 2017-07-11
code\chap3\3.6.1\main361.m, 1148 , 2017-07-11
code\chap3\3.6.1\myFFT.m, 597 , 2017-07-11
code\chap3\3.6.2\main362.m, 1434 , 2017-07-11
code\chap3\3.6.2\myFFT.m, 599 , 2017-07-11
code\chap4\main431.m, 781 , 2017-07-11
code\chap4\main432.m, 873 , 2017-07-11
code\chap4\main433.m, 1157 , 2017-07-11
code\chap4\main434.m, 1287 , 2017-07-11
code\chap4\main435.m, 805 , 2017-07-11
code\chap4\main436.m, 1077 , 2017-07-11
code\chap4\main441.m, 1158 , 2017-07-11
code\chap4\main442.m, 809 , 2017-07-11
code\chap4\main443.m, 819 , 2017-07-11
code\chap4\main444.m, 852 , 2017-07-11
code\chap5\5.4\multinomialR_test.m, 1557 , 2017-07-11
code\chap5\5.4\randomR_test.m, 1380 , 2017-07-11
code\chap5\5.4\residualR_Test.m, 1752 , 2017-07-11
code\chap5\5.4\systematicR_test.m, 1790 , 2017-07-11
code\chap5\5.6\multinomialR.m, 1022 , 2017-07-11
code\chap5\5.6\Particle_For_UnlineOneDiv.m, 4136 , 2017-07-11
code\chap5\5.6\randomR.m, 813 , 2017-07-11
code\chap5\5.6\residualR.m, 1138 , 2017-07-11
code\chap5\5.6\systematicR.m, 1202 , 2017-07-11
code\chap5\NetMain.m, 1168 , 2017-07-11
code\chap6\ekf.m, 772 , 2017-07-11
code\chap6\epf.m, 1448 , 2017-07-11
code\chap6\ffun.m, 506 , 2017-07-11
code\chap6\gengamma.m, 933 , 2017-07-11
code\chap6\hfun.m, 522 , 2017-07-11
code\chap6\main.m, 3586 , 2017-07-11
code\chap6\multinomialR.m, 957 , 2017-07-11
code\chap6\pf.m, 1101 , 2017-07-11
code\chap6\residualR.m, 1051 , 2017-07-11
code\chap6\scaledSymmetricSigmaPoints.m, 810 , 2017-07-11
code\chap6\systematicR.m, 1213 , 2017-07-11
code\chap6\ukf.m, 2231 , 2017-07-11
code\chap6\upf.m, 1659 , 2017-07-11
code\chap7\7.3.2\distance.m, 612 , 2017-07-11
code\chap7\7.3.2\ffun.m, 844 , 2017-07-11
code\chap7\7.3.2\hfun.m, 747 , 2017-07-11
code\chap7\7.3.2\main.m, 2005 , 2017-07-11
code\chap7\7.3.2\PF.m, 1491 , 2017-07-11
code\chap7\7.3.2\randomR.m, 746 , 2017-07-11
code\chap7\7.3.2\sfun.m, 554 , 2017-07-11
code\chap7\7.4.2\distance.m, 612 , 2017-07-11
code\chap7\7.4.2\ffun.m, 773 , 2017-07-11
code\chap7\7.4.2\hfun.m, 700 , 2017-07-11
code\chap7\7.4.2\main.m, 2010 , 2017-07-11
code\chap7\7.4.2\PF.m, 1499 , 2017-07-11
code\chap7\7.4.2\randomR.m, 747 , 2017-07-11
code\chap7\7.4.2\sfun.m, 554 , 2017-07-11
code\chap7\7.5.2\distance.m, 612 , 2017-07-11
code\chap7\7.5.2\ffun.m, 773 , 2017-07-11
code\chap7\7.5.2\hfun.m, 696 , 2017-07-11
code\chap7\7.5.2\main.m, 2204 , 2017-07-11
code\chap7\7.5.2\PF.m, 1769 , 2017-07-11
code\chap7\7.5.2\randomR.m, 728 , 2017-07-11
code\chap7\7.5.2\sfun.m, 554 , 2017-07-11
code\chap7\7.6\ffun.m, 449 , 2017-07-11
code\chap7\7.6\hfun.m, 463 , 2017-07-11
code\chap7\7.6\main.m, 4600 , 2017-07-11
code\chap7\7.6\randomR.m, 746 , 2017-07-11
code\chap7\7.6\sfun.m, 422 , 2017-07-11
code\chap8\Battery_Capacity.mat, 7518 , 2017-07-11
code\chap8\hfun.m, 592 , 2017-07-11
code\chap8\LoadDataTest.m, 663 , 2017-07-11
code\chap8\main.m, 2293 , 2017-07-11
code\chap8\multinomialR.m, 857 , 2017-07-11
code\chap8\para_fit.m, 729 , 2017-07-11
code\chap8\randomR.m, 615 , 2017-07-11
code\chap8\residualR.m, 1005 , 2017-07-11
code\chap8\systematicR.m, 1076 , 2017-07-11
code\chap9\9.2.1\sfuntmpl.m, 1493 , 2017-07-11
code\chap9\9.3.1\SimuStateFunction.m, 1291 , 2017-07-11
code\chap9\9.3.1\System_State_Observation_Simulation.mdl, 24014 , 2017-07-11
code\chap9\9.3.1\System_State_Simulation.mdl, 20703 , 2017-07-11
code\chap9\9.3.2\DataAnalysis.m, 1150 , 2017-07-11
code\chap9\9.3.2\GetDistanceFunction.m, 1294 , 2017-07-11
code\chap9\9.3.2\ParticleFilter.m, 2496 , 2017-07-11
code\chap9\9.3.2\SimuStateFunction.m, 1436 , 2017-07-11
code\chap9\9.3.2\System_TargetTracking_PF_Simulation.mdl, 26054 , 2017-07-11
code\chap9\9.3.2\Xpf.mat, 1468 , 2017-07-11
code\chap9\9.3.2\Xstate.mat, 1465 , 2017-07-11
code\chap9\9.3.2\Zdist.mat, 527 , 2017-07-11
code\chap3\3.5.1, 0 , 2017-12-15
code\chap3\3.6.1, 0 , 2017-12-15
code\chap3\3.6.2, 0 , 2017-12-15
code\chap5\5.4, 0 , 2017-12-15
code\chap5\5.6, 0 , 2017-12-15
code\chap7\7.3.2, 0 , 2017-12-15
code\chap7\7.4.2, 0 , 2017-12-15
code\chap7\7.5.2, 0 , 2017-12-15
code\chap7\7.6, 0 , 2017-12-15
code\chap9\9.2.1, 0 , 2017-12-15
code\chap9\9.3.1, 0 , 2017-12-15
code\chap9\9.3.2, 0 , 2017-12-15

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    这个文件为粒子滤波算法的matlab源代码程序。(Particle filter)
    2013-01-08 15:30:25下载
    积分:1
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    hough变换求图像中的直线,matlab语言编写,修改图片的路径即可。(hough transform to draw the lines in the picture,writen by matlab, the code can only be used after modify the path of the picture.)
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    说明:  ORIGINAL MATGPR RELEASE
    2020-10-04 07:34:39下载
    积分:1
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    说明:  关于非高斯噪声环境下的各种调制方式信道容量仿真(Non-Gaussian noise environment on a variety of channel capacity modulation simulation)
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    估计一个点云数据的表面法线,表面法线是几何体表面的重要属性。(A point estimate the surface normal, surface normal geometrical surface cloud data is an important attribute volume.)
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    利用有效折射率模型对全内反射型光子晶体光纤的宏弯曲损耗特性进行了理论研究,分析了光子晶体光纤的结构参量和弯曲半径对其宏弯曲损耗谱的影响(bend loss )
    2021-01-16 13:58:45下载
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  • L1_Tracking_v4_release
    该程序将计算机视觉的目标跟踪问题转化为寻找稀疏矩阵的过程,将预先的得到的样本粒子与稀疏矩阵线性相乘得到目标(The program will target tracking in computer vision into the process of finding a sparse matrix, the sample will be obtained in advance of the particles multiplied with the goal of sparse linear)
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    无线通信中的优化技术,原书,通过对现有已运行的网络进行数据分析、现场测试数据采集、参数分析、硬件检查等手段,找出影响网络质量的原因,并且通过参数的修改、网络结构的调整、设备配置的调整和采取某些技术手段。(Optimization of wireless communications technology by Sergiy A. Vorobyov and Yonina C. Eldar, the original book, through the existing network has been in operation for data analysis, field test data acquisition, parameter analysis, hardware checks and other means to identify the factors affecting the quality of the network, and by modifying the parameters of the network structural adjustment, and the adjustment device configured to take certain technical means.)
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