登录
首页 » matlab » matlab_utilities

matlab_utilities

于 2010-04-01 发布 文件大小:87KB
0 190
下载积分: 1 下载次数: 1

代码说明:

说明:  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)

文件列表:

matlab_utilities\Add_relative_Path\addrelpath.m
matlab_utilities\Add_relative_Path\Add_path.m
matlab_utilities\Add_relative_Path\Add_relative_Path.m
matlab_utilities\Add_relative_Path\remrelpath.m
matlab_utilities\Add_relative_Path\程序使用说明书.txt
matlab_utilities\Add_relative_Path
matlab_utilities\Add_relative_Path.m
matlab_utilities\DataSets\henon.m
matlab_utilities\DataSets\Newdataset2.mat
matlab_utilities\DataSets\NEW_dataset.mat
matlab_utilities\DataSets
matlab_utilities\EXP_demo_files\demo_ekf_filter_EXP.m
matlab_utilities\EXP_demo_files\demo_particle_filter_EXP2.m
matlab_utilities\EXP_demo_files\demo_unscented_filter_EXP.m
matlab_utilities\EXP_demo_files\particle_filter_Real_EXP.m
matlab_utilities\EXP_demo_files
matlab_utilities\gmm_utilities\approximate_gauss_by_gmm.m
matlab_utilities\gmm_utilities\approximate_gauss_by_kernels.m
matlab_utilities\gmm_utilities\Contents.m
matlab_utilities\gmm_utilities\covariance_intersect.m
matlab_utilities\gmm_utilities\gauss_divide.m
matlab_utilities\gmm_utilities\gauss_multiply.m
matlab_utilities\gmm_utilities\gmm_addition.m
matlab_utilities\gmm_utilities\gmm_conditional.m
matlab_utilities\gmm_utilities\gmm_convolve.m
matlab_utilities\gmm_utilities\gmm_correlate.m
matlab_utilities\gmm_utilities\gmm_counting_algorithm.m
matlab_utilities\gmm_utilities\gmm_covariance_intersect.m
matlab_utilities\gmm_utilities\gmm_derivative.m
matlab_utilities\gmm_utilities\gmm_derivative_parameters.m
matlab_utilities\gmm_utilities\gmm_display_1D.m
matlab_utilities\gmm_utilities\gmm_display_2D_contour.m
matlab_utilities\gmm_utilities\gmm_distance_bayes.m
matlab_utilities\gmm_utilities\gmm_distance_bhattacharyya.m
matlab_utilities\gmm_utilities\gmm_distance_KLD.m
matlab_utilities\gmm_utilities\gmm_divide.m
matlab_utilities\gmm_utilities\gmm_em.m
matlab_utilities\gmm_utilities\gmm_em_auto.m
matlab_utilities\gmm_utilities\gmm_entropy.m
matlab_utilities\gmm_utilities\gmm_evaluate.m
matlab_utilities\gmm_utilities\gmm_marginal.m
matlab_utilities\gmm_utilities\gmm_multiply.m
matlab_utilities\gmm_utilities\gmm_normalise.m
matlab_utilities\gmm_utilities\gmm_reduce_merge.m
matlab_utilities\gmm_utilities\gmm_reduce_truncate.m
matlab_utilities\gmm_utilities\gmm_remove_zeros.m
matlab_utilities\gmm_utilities\gmm_samples.m
matlab_utilities\gmm_utilities\gmm_samples_old.m
matlab_utilities\gmm_utilities\gmm_slice.m
matlab_utilities\gmm_utilities\gmm_subtract.m
matlab_utilities\gmm_utilities\gmm_to_gaussian.m
matlab_utilities\gmm_utilities\gmm_transform.m
matlab_utilities\gmm_utilities\gmm_update.m
matlab_utilities\gmm_utilities\gmm_update_linearised.m
matlab_utilities\gmm_utilities\kernel_convolve.m
matlab_utilities\gmm_utilities\kernel_distance_bayes.m
matlab_utilities\gmm_utilities\kernel_distance_bhattacharyya.m
matlab_utilities\gmm_utilities\kernel_distance_KLD.m
matlab_utilities\gmm_utilities\kernel_divide.m
matlab_utilities\gmm_utilities\kernel_evaluate.m
matlab_utilities\gmm_utilities\kernel_multiply.m
matlab_utilities\gmm_utilities\kernel_normalise.m
matlab_utilities\gmm_utilities\kernel_reduce_merge.m
matlab_utilities\gmm_utilities\kernel_reduce_truncate.m
matlab_utilities\gmm_utilities\kernel_samples.m
matlab_utilities\gmm_utilities\kernel_to_gaussian.m
matlab_utilities\gmm_utilities\kernel_transform.m
matlab_utilities\gmm_utilities\kernel_update.m
matlab_utilities\gmm_utilities\KF_update_w.m
matlab_utilities\gmm_utilities\KF_update_w_simple.m
matlab_utilities\gmm_utilities\make_random_gmm.m
matlab_utilities\gmm_utilities\Notes.txt
matlab_utilities\gmm_utilities
matlab_utilities\matlab_utilities\chi_square_bound.m
matlab_utilities\matlab_utilities\chi_square_density.m
matlab_utilities\matlab_utilities\chi_square_mass.m
matlab_utilities\matlab_utilities\chi_square_to_gauss.m
matlab_utilities\matlab_utilities\Contents.m
matlab_utilities\matlab_utilities\Copy_of_demo_particle_filter.m
matlab_utilities\matlab_utilities\demo_bearing_only.m
matlab_utilities\matlab_utilities\demo_chi_square.m
matlab_utilities\matlab_utilities\demo_ekf_filter.m
matlab_utilities\matlab_utilities\demo_kmeans.m
matlab_utilities\matlab_utilities\demo_particle_filter.m
matlab_utilities\matlab_utilities\demo_unscented_filter.m
matlab_utilities\matlab_utilities\distance_bhattacharyya.m
matlab_utilities\matlab_utilities\distance_KLD.m
matlab_utilities\matlab_utilities\distance_KLD_symmetric.m
matlab_utilities\matlab_utilities\distance_mahalanobis.m
matlab_utilities\matlab_utilities\distance_normalised.m
matlab_utilities\matlab_utilities\dist_sqr.m
matlab_utilities\matlab_utilities\dist_sqr_.m
matlab_utilities\matlab_utilities\dist_sqr_v2.m
matlab_utilities\matlab_utilities\EKF_update.m
matlab_utilities\matlab_utilities\ellipse_mass.m
matlab_utilities\matlab_utilities\ellipse_sigma.m
matlab_utilities\matlab_utilities\gauss_evaluate.m
matlab_utilities\matlab_utilities\gauss_likelihood.m
matlab_utilities\matlab_utilities\gauss_regularise.m
matlab_utilities\matlab_utilities\gauss_samples.m

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • feGeometry
    Evaluates the finite element linear basis function. and sets up the geometric data.
    2011-01-21 20:53:23下载
    积分:1
  • ExpandableListViewTest
    Test Target Class Source Code for Andriod.
    2013-11-26 15:11:49下载
    积分:1
  • read_ieee_vector_monthly
    读ncdc风场数据,包括速度场和风应力旋度场(read wind data)
    2012-01-09 15:08:10下载
    积分:1
  • spectral_clustering_cogs118b-master
    1. 按照式计算相似性矩阵 2. 排除自身的相似度 3. 按照式计算归一化矩阵 4. 按照式计算归一化拉普拉斯图矩阵L 5. 计算L的特征向量,将前个特征值最大的向量按列放置成一个矩阵,即依次为前个特征值最大的特征向量 6. 归一化X形成矩阵Y 7. 对矩阵Y按每行为一个数据点,进行k-means聚类,第行所属的类就是原来所属的类。(1. similarity matrix based on formula computation 2. rule out your own similarity. 3. normalized matrix based on formula computation 4. normalized formula Laplasse matrix L according to formula. 5. Calculate the eigenvectors of L. Place the vectors with the largest eigenvalues in columns into a matrix, that is, the eigenvectors with the largest eigenvalues in turn. 6. normalized X formation matrix Y 7. K-means clustering is applied to matrix Y according to one data point per behavior. The first row belongs to the original class.)
    2018-11-16 09:14:48下载
    积分:1
  • fenel_simpson2D
    通过利用辛普森二重积分,求解矩形孔菲涅耳衍射,完全正确的代码。(Through the use of Simpson double integral, Fresnel diffraction Rectangular hole completely correct code.)
    2010-10-21 11:37:14下载
    积分:1
  • Design2-DfilterusingWSE
    说明:  自己编写的用WSE的方法设计的二维数字滤波器,效果不错。(themselves with WSE prepared by the method of two-dimensional design of digital filters, effectiveness.)
    2006-04-07 14:00:59下载
    积分:1
  • Kruskal
    ALGORITHM KRUSKAL s with computational comlexity for 5 to 30 tops. with chart.
    2010-05-06 01:35:37下载
    积分:1
  • Tijana_Jevtic_2zadatak
    object recognition using convolution
    2011-01-11 07:38:10下载
    积分:1
  • gabor.rar
    该代码仅计算了一个101×101尺寸的Gabor函数变换,得到均值和方差。代码采用两种卷积计算方式,从结果中可以看出,快速傅立叶变换卷积的效率是离散二维叠加和卷积的近50倍。 (The code is only the calculation of a 101 × 101 size Gabor function transformation, the mean and variance. Convolutional code using two methods of calculation can be seen from the results, fast Fourier transform convolution efficiency are two-dimensional discrete convolution superposition and nearly 50 times.)
    2009-03-09 18:43:09下载
    积分:1
  • mapminmax
    matlab7.0没有这个函数,求举矩阵的最大最小值问题,下载后放在work目录下即可调用(mapminmax.m function)
    2013-01-23 16:11:34下载
    积分:1
  • 696516资源总数
  • 106668会员总数
  • 21今日下载