sc_moneone_snn.m

神经网络的工具箱, 神经网络的工具箱,

function [y, sc] = sc_moneone_snn(x, parameters, s)
%SC_MONEONE_SNN scaling function; scale data to [-1, 1].
%
% Syntax
%
%  1. Initial scaling:
%    [y, sc] = sc_moneone_snn(x)
%       x  - values to be scaled.
%       y  - scaled values.
%       sc - sc_struct containing scaling information.
%
%  2. Scale using parameters of initial scaling:
%    y = sc_moneone_snn(x, sc.parameters)
%       x             - values to be scaled.
%       sc.parameters - parameters containing scaling parameters.
%       y             - scaled values.
%
%  3. Inverse scaling:
%    x = sc_moneone_snn(y, sc.parameters, 'inv');
%       y             - scaled values.
%       sc.parameters - parameters containing scaling parameters.
%       x             - inversed values.
%
% See also
%
%  SCALE_SNN
%

if (nargin == 1)
  sc.name = 'sc_moneone_snn';
  sc.parameters.min = min(x);
  sc.parameters.max = max(x);
  y = (2*x - sc.parameters.min - sc.parameters.max) ...
      / (sc.parameters.max - sc.parameters.min);
elseif (nargin == 2)
  y = (2*x - parameters.min - parameters.max) ...
      / (parameters.max - parameters.min);
elseif (nargin == 3)
  if strcmp('inv', s)
     y = (x * (parameters.max - parameters.min) ...
          + parameters.min + parameters.max ) / 2;
  else
     error('SC_MONEONE_SNN: 3rd argument must be ''inv''.');
  end
else
  error('SC_MONEONE_SNN: incorrect number of input arguments.');
end