wnetreg.m

新的神经网络算法源程序

function [th, mseif, flopif, timeif]= ...
         wnetreg(y, x, nbwavelon, max_epoch, initmode, min_nbw, levels);
%Wnetreg: Compute static nonlinear regression models using WaveNet
%
% THETA = wnetreg(y, x, nbwavelon, max_epoch, initmode, min_nbw, levels)
%
% THETA: returned as the estimated parameters of the WaveNet-Regression model
% (y, x): training data
%         output y : a column vector.
%         inputs x : for single input case, x is a column vector,
%                    for multi-inputs case, x=[x1 x2 ... xm], each xi is a
%                    column vector.
%
% nbwavelon: number of wavelets used to construct the WaveNet
% max_epoch: maximum number of epochs of training
% initmode: Initialization mode, default is 2
%             initmode=1:  residual based selection
%             initmode=2:  stepwise selection by orthogonalization
%             initmode=3:  backward elimination
%           If initmode=THETA, a matrix containing WaveNet parameters,
%           then these parameters are used to initialize the WaveNet.
%           This mode is useful for retrain WaveNets.
%
% min_nbw: minimum number of input patterns each wavelon should "cover"
% levels: number of scale levels scanned during initialization
%
%The arguments min_nbw and levels are optional.

%By Qinghua Zhang. March, 1994.

if nargin < 3, nbwavelon = []; end;
if nargin < 4, max_epoch = []; end;
if nargin < 5, initmode = []; end;
if nargin < 6, min_nbw = []; end;
if nargin < 7, levels = []; end;

[yr,yc]=size(y); [xr,xc]=size(x);

if yr<yc, y=y'; end
if xr<xc, x=x'; end

if length(initmode) > 1
  [t0,d0,w0,c0,b0] = decompth(initmode); nbwavelon=length(w0);
  initmode = 0;
else
  t0=[]; d0=[]; w0=[]; c0=[]; b0=[];
end

[t,d,w,c,b, mseif, flopif, timeif] = trainwn(x', y', nbwavelon, max_epoch, ...
                  initmode, min_nbw, levels, t0, d0, w0, c0, b0);

nbwavelon = length(w);

nbvar = length(c);
thr = 2*nbvar + 5;

nn=[0 ones(1,nbvar) zeros(1,nbvar)];

nnlen = size(nn,2);
thc = max([3+nnlen nbwavelon  nbvar+1 7]);

th = zeros(thr, thc);

th(1,1:(3+nnlen)) = [nbwavelon nbvar nnlen nn];
if nbwavelon>0
  th(2:nbvar+1,1:nbwavelon) = t;
  th(nbvar+2:2*nbvar+1,1:nbwavelon) = d;
  th(2*nbvar+2,1:nbwavelon) = w;
end
th(2*nbvar+3, 1:nbvar) = c;
th(2*nbvar+3, nbvar+1) = b;
th(2*nbvar+4, 1:6) = clock;
th(2*nbvar+5,1:7) = abs('WNETREG');