www.gusucode.com > som-bp混合神经网络的matlab程序源码 > matlab_emulator/SOM_00.m
%------ SOM test -------- clear clc echo off % --------------- initial the parameter out_num = 2; % 输出节点数目 input_num = 7; % 输入节点数目 Epochs = 100; % 训练周期 % --------------- read data from the file base_path = 'E:\SOMBP\data_source\feature02\'; I1 = load([base_path,'apen.txt']); % 1 >> 2 1.2563 1.8150 I2 = load([base_path,'kc.txt']); % 0 >> 1 0.6299 0.9611 I3 = load([base_path,'mir.txt']); % 0 >> 5 0.4802 4.0544 I4 = load([base_path,'asm.txt']); % 0 >> 0.01 0.0004 0.0037 I5 = load([base_path,'idm.txt']); % 0 >> 0.5 0.0663 0.2906 % I1 = load([base_path,'apen2.txt']); % I2 = load([base_path,'kc2.txt']); % I3 = load([base_path,'mir2.txt']); % I4 = load([base_path,'asm2.txt']); % I5 = load([base_path,'idm2.txt']); P = [I1';I2';I3';I4';I5']; MinMaxValue = minmax(P); % NEWSOM ---- create the som net net = newsom( MinMaxValue,[out_num]); net.trainParam.epochs = Epochs; % TRAIN ----- train the net begin_time = clock; [net,tr,Y,E,Pf,Af] = train(net,P); cost_time = etime(clock,begin_time) % OOTPUT ----- out put the som data which made as the bp input data SOMresult = net.IW{1}*P; save SOMresult.mat SOMresult;