文件名称:matlab_utilities

  • 所属分类:
  • 数值算法/人工智能
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 87kb
  • 下载次数:
  • 1次
  • 提 供 者:
  • 薛*
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  • 下载说明:
  • 别用迅雷下载,失败请重下,重下不扣分!

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粒子滤波、无迹粒子滤波算法程序,高斯混合模型参数设置等详细代码-Particle filter, unscented particle filter program, Gaussian mixture model parameter settings, and more code
(系统自动生成,下载前可以参看下载内容)

下载文件列表

matlab_utilities\Add_relative_Path\addrelpath.m

................\.................\Add_path.m

................\.................\Add_relative_Path.m

................\.................\remrelpath.m

................\.................\程序使用说明书.txt

................\Add_relative_Path

................\Add_relative_Path.m

................\DataSets\henon.m

................\........\Newdataset2.mat

................\........\NEW_dataset.mat

................\DataSets

................\EXP_demo_files\demo_ekf_filter_EXP.m

................\..............\demo_particle_filter_EXP2.m

................\..............\demo_unscented_filter_EXP.m

................\..............\particle_filter_Real_EXP.m

................\EXP_demo_files

................\gmm_utilities\approximate_gauss_by_gmm.m

................\.............\approximate_gauss_by_kernels.m

................\.............\Contents.m

................\.............\covariance_intersect.m

................\.............\gauss_divide.m

................\.............\gauss_multiply.m

................\.............\gmm_addition.m

................\.............\gmm_conditional.m

................\.............\gmm_convolve.m

................\.............\gmm_correlate.m

................\.............\gmm_counting_algorithm.m

................\.............\gmm_covariance_intersect.m

................\.............\gmm_derivative.m

................\.............\gmm_derivative_parameters.m

................\.............\gmm_display_1D.m

................\.............\gmm_display_2D_contour.m

................\.............\gmm_distance_bayes.m

................\.............\gmm_distance_bhattacharyya.m

................\.............\gmm_distance_KLD.m

................\.............\gmm_divide.m

................\.............\gmm_em.m

................\.............\gmm_em_auto.m

................\.............\gmm_entropy.m

................\.............\gmm_evaluate.m

................\.............\gmm_marginal.m

................\.............\gmm_multiply.m

................\.............\gmm_normalise.m

................\.............\gmm_reduce_merge.m

................\.............\gmm_reduce_truncate.m

................\.............\gmm_remove_zeros.m

................\.............\gmm_samples.m

................\.............\gmm_samples_old.m

................\.............\gmm_slice.m

................\.............\gmm_subtract.m

................\.............\gmm_to_gaussian.m

................\.............\gmm_transform.m

................\.............\gmm_update.m

................\.............\gmm_update_linearised.m

................\.............\kernel_convolve.m

................\.............\kernel_distance_bayes.m

................\.............\kernel_distance_bhattacharyya.m

................\.............\kernel_distance_KLD.m

................\.............\kernel_divide.m

................\.............\kernel_evaluate.m

................\.............\kernel_multiply.m

................\.............\kernel_normalise.m

................\.............\kernel_reduce_merge.m

................\.............\kernel_reduce_truncate.m

................\.............\kernel_samples.m

................\.............\kernel_to_gaussian.m

................\.............\kernel_transform.m

................\.............\kernel_update.m

................\.............\KF_update_w.m

................\.............\KF_update_w_simple.m

................\.............\make_random_gmm.m

................\.............\Notes.txt

................\gmm_utilities

................\matlab_utilities\chi_square_bound.m

................\................\chi_square_density.m

................\................\chi_square_mass.m

................\................\chi_square_to_gauss.m

................\................\Contents.m

................\................\Copy_of_demo_particle_filter.m

................\................\demo_bearing_only.m

................\................\demo_chi_square.m

................\................\demo_ekf_filter.m

................\................\demo_kmeans.m

................\.

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