www.gusucode.com > 用matlab仿真0到9十个数字的语音识别源码程序 > Speech-Recogenition/mk_stochastic.m
function [T,Z] = mk_stochastic(T) % MK_STOCHASTIC Ensure the argument is a stochastic matrix, i.e., the sum over the last dimension is 1. % [T,Z] = mk_stochastic(T) % % If T is a vector, it will sum to 1. % If T is a matrix, each row will sum to 1. % If T is a 3D array, then sum_k T(i,j,k) = 1 for all i,j. % Set zeros to 1 before dividing % This is valid since S(j) = 0 iff T(i,j) = 0 for all j if (ndims(T)==2) & (size(T,1)==1 | size(T,2)==1) % isvector [T,Z] = normalise(T); elseif ndims(T)==2 % matrix Z = sum(T,2); S = Z + (Z==0); norm = repmat(S, 1, size(T,2)); T = T ./ norm; else % multi-dimensional array ns = size(T); T = reshape(T, prod(ns(1:end-1)), ns(end)); Z = sum(T,2); S = Z + (Z==0); norm = repmat(S, 1, ns(end)); T = T ./ norm; T = reshape(T, ns); end