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;