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高斯滤波器 matlab toolbox For GMMs and Gaussian kernels

% 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