gusucode.com > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM源码程序 > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM\stprtool\linear\anderson\gatx0.m

    function [x0] = gatx0( alpha, theta, mi, sigma )
% GATX0 compute point x0 (Generalized Andeson's task).
%  [x0] = gatx0( alpha, theta, mi, sigma )
%
% GATX0 computes a point on lying on the hyperplane having
%  the shortest Mahalanobis distance from given Gaussian
%  distribution (point mi and covariance matrix sigma).
%
% Input:
%  alpha [Dx1] normal vector of hyperplane.
%  theta [1x1] threshold of hyperplane.
%  mi [Dx1] mean value vector.
%  sigma [DxD] covariance matrix.
%
% Output:
%  x0 [Dx1] found point.
%


% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cmp.felk.cvut.cz
% Written Vojtech Franc (diploma thesis) 24.10.1999, 27.02.2000
% Modifications:
%  03-May-2001, V. Franc, created

x0 = mi - ((alpha' * mi ) - theta )*(sigma*alpha) / (alpha'*sigma*alpha);

return;