📄 normald.m
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function [p]=normald(X,mi,sigma)
% [p]=normald(X,mi,sigma)
%
% NORMALD calculates the value of many-dimensional probability density
% of the normal (Gaussian) distribution for given vectors in the
% matrix X and parameters of the normal distribution mi, sigma.
%
% Input:
% x [NxK] - matrix K of input vectors for which the density is calculated
% mi [Nx1] - vector of mean values
% sigma [NxN] - covariance matrix
%
% where N is the dimension of the feature space.
%
% Output:
% p[1xK] - the value of the probability density
%
% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cmp.felk.cvut.cz
% Written Vojtech Franc (diploma thesis) 19.03.2000
% Modifications
% 24. 6.00 V. Hlavac, comments changed to English.
DIM=size(X,1);
p=exp(-1/2*mahalan(X,mi,sigma))/((2*pi)^(DIM/2) * sqrt(det(sigma)));
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