www.gusucode.com > 用粒子滤波算法进行跟踪的matlab代码 > gmm_utilities/approximate_gauss_by_gmm.m
function g = approximate_gauss_by_gmm(x,P,N,type) %function g = approximate_gauss_by_gmm(x,P,N,type) % % INPUTS: % x,P - mean and covariance matrix of a Gaussian % N - number of components in output gmm % type - method used % % OUTPUT: % g - gmm approximation of Gaussian % % This function is in alpha stage of development. % % Tim Bailey 2005. if N == 1, type = 1; elseif nargin == 3, type = 2; end switch type case 1 % Trivial solution g.w = ones(1,N)/N; g.x = repcol(x,N); g.P = repmat(P,[1,1,N]); case 2 % Kernels g = approximate_gauss_by_kernels(x,P,N); g.P = repmat(g.P, [1,1,N]); otherwise error('Invalid type') end % Other ideas: % - splitting algorithm % - using musso's criterion at each step ?? % - split along principal axis, 1/2 covariance at each step