gusucode.com > 用粒子滤波算法进行跟踪的matlab代码 > gmm_utilities/Contents.m
% Tim Bailey's Gaussian Mixture Model and Gaussian Kernel MatLab Utilities % Version 1.0, 2006. % % http://www.acfr.usyd.edu.au/homepages/academic/tbailey/software/software.html % % approximate_gauss_by_gmm - Create a set of N gmms to approximate a single Gaussian % approximate_gauss_by_kernels- Create a set of N kernels to approximate a single Gaussian % % covariance_intersect - Perform the covariance intersection of two Gaussians % gauss_divide - Compute a/b, where a,b are Gaussians % gauss_multiply - Multiply two Gaussians returning the result and the normalising weight % % gmm_addition - Compute c = a+b, where PDFs p(a),p(b) are gmms (equivalent to gmm_convolve) % gmm_conditional - % gmm_convolve - Convolve two Gaussian mixtures % gmm_correlate - Cross-correlate two Gaussian mixtures % gmm_covariance_intersect - "Generalised" CI for gmms % gmm_display_1D - % gmm_display_2D_contour - % gmm_distance_bayes - Bayesian distance between two gmms - normalising constant after multiplication % gmm_distance_bhattacharyya- Bhattacharyya distance between two gmms (Monte Carlo) % gmm_distance_KLD - Kullback-Leibler divergence between two gmms (Monte Carlo) % gmm_divide - Compute a/b, where a,b are gmms % gmm_em - % gmm_em_auto - % gmm_evaluate - Evaluate gmm at discrete points % gmm_marginal - % gmm_multiply - Multiply two gmms % gmm_normalise - Make integral of gmm equal to one and return normalising constant % gmm_reduce_merge - Reduce number of gmm components by joining % gmm_reduce_truncate - Reduce number of gmm components by eliminating those with small weights % gmm_remove_zeros - % gmm_samples - Generate samples from gmm % gmm_subtract - Compute c = a-b, where PDFs p(a),p(b) are gmms (equivalent to gmm_correlate) % gmm_to_gaussian - Compute mean and variance of gmm % gmm_transform - Apply a linear transform to gmm, y = Hx % gmm_update - Perform a Kalman update on a gmm PDF given a gmm likelihood % gmm_update_linearised - % % kernel_convolve - % kernel_distance_bayes - % kernel_distance_bhattacharyya- % kernel_distance_KLD - % kernel_evaluate - % kernel_multiply - % kernel_normalise - % kernel_reduce_merge - % kernel_reduce_truncate - % kernel_samples - % kernel_to_gaussian - % kernel_transform - % kernel_update - % % KF_update_w - Kalman update that also returns the normalising weight of the multiplication % KF_update_w_simple - Same as KF_update_w but simpler implementation