regularisation.h

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00001 /***************************************************************************
00002  *   Copyright (C) 2005 by Robot Group Leipzig                             *
00003  *    martius@informatik.uni-leipzig.de                                    *
00004  *    fhesse@informatik.uni-leipzig.de                                     *
00005  *    der@informatik.uni-leipzig.de                                        *
00006  *                                                                         *
00007  *   This program is free software; you can redistribute it and/or modify  *
00008  *   it under the terms of the GNU General Public License as published by  *
00009  *   the Free Software Foundation; either version 2 of the License, or     *
00010  *   (at your option) any later version.                                   *
00011  *                                                                         *
00012  *   This program is distributed in the hope that it will be useful,       *
00013  *   but WITHOUT ANY WARRANTY; without even the implied warranty of        *
00014  *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         *
00015  *   GNU General Public License for more details.                          *
00016  *                                                                         *
00017  *   You should have received a copy of the GNU General Public License     *
00018  *   along with this program; if not, write to the                         *
00019  *   Free Software Foundation, Inc.,                                       *
00020  *   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.             *
00021  ***************************************************************************
00022  *                                                                         *
00023  *  DESCRIPTION                                                            *
00024  *                                                                         *
00025  *  This file contains activation function and there derivatives in        *
00026  *  different regularised versions                                         *
00027  *                                                                         *
00028  *                                                                         *
00029  *   $Log: regularisation.h,v $
00030  *   Revision 1.10  2008/12/22 14:36:48  martius
00031  *   undo of ralf's changes on g_s and g_ss_div_s
00032  *   created g_s_soft and g_ss_div_s_soft with this implementations
00033  *
00034  *   Revision 1.9  2008/11/21 13:52:59  martius
00035  *   changed g_s back to less regularization since there is the g_derivative version
00036  *
00037  *   Revision 1.8  2008/05/02 17:20:04  martius
00038  *   *** empty log message ***
00039  *
00040  *   Revision 1.7  2008/02/05 10:08:47  der
00041  *   new function g_derivative
00042  *
00043  *   Revision 1.6  2008/01/29 09:38:02  der
00044  *   function g_s changed
00045  *
00046  *   Revision 1.5  2007/04/03 16:37:57  der
00047  *   *** empty log message ***
00048  *
00049  *   Revision 1.4  2007/02/23 09:25:52  der
00050  *   regularisation with taylor expansion
00051  *
00052  *   Revision 1.3  2006/11/29 16:22:43  martius
00053  *   name is a variable of configurable and is used as such
00054  *
00055  *   Revision 1.2  2006/10/23 10:47:59  martius
00056  *   g and derivatives and inverses
00057  *
00058  *   Revision 1.1  2006/10/20 15:22:15  martius
00059  *   regularisation terms for g
00060  *
00061  *   Revision 1.2  2006/07/14 12:23:56  martius
00062  *   selforg becomes HEAD
00063  *
00064  *   Revision 1.1.2.1  2005/12/06 17:38:21  martius
00065  *   *** empty log message ***
00066  *
00067  *                                                                 *
00068  ***************************************************************************/
00069 #ifndef __REGULARISATION_H
00070 #define __REGULARISATION_H
00071 
00072 #include <cmath>
00073 #include <selforg/controller_misc.h>
00074 
00075 double inline sqr(double x) { 
00076   return x*x; 
00077 }
00078 
00079 /// neuron transfer function
00080 double inline g(double z)
00081 {
00082   return tanh(z);
00083 };
00084 
00085 /// first dervative
00086 double inline g_s(double z)
00087 {
00088   double k=tanh(z); 
00089   return 1.025 - k*k; 
00090   //  return 1/((1+0.5 * z*z)*(1+0.5 * z*z));    // softer
00091   //return 1/(1+log(1+z*z)); // even softer
00092 };
00093 
00094 
00095 /// first dervative with smoothing for large z
00096 double inline g_derivative(double z)
00097 {  
00098    return 1/((1+0.5 * z*z)*(1+0.5 * z*z));  
00099 };
00100 
00101 /// inverse of the first derivative
00102 double inline g_s_inv(double z)
00103 {
00104   double k=tanh(z);
00105    return 1/(1.025 - k*k);
00106   // return 1+z*z; // softer
00107   //return 1+log(1+z*z); // even softer
00108 };
00109 
00110 /** \f[ g'(z+xsi) = 1-(tanh(z+xsi))^2 \f] with additional clipping */
00111 double inline g_s(double z, double xsi) {
00112   double Z = clip(z, -3.0, 3.0) + clip(xsi, -1.0, 1.0);  
00113   double k=tanh(Z);  // approximation with Mittelwertsatz 
00114   return 1 - k*k;
00115 };
00116 
00117 
00118 /** soft version: \f[ g'(z+xsi) = 1/(1+(z+xsi)^2 \f] with additional clipping */
00119 double inline g_s_soft(double z, double xsi) {
00120   double Z = clip(z, -3.0, 3.0) + clip(xsi, -1.0, 1.0);  
00121   return 1/(1 + Z*Z);//TEST
00122 };
00123 
00124 
00125 /// an exact formula for g''/g'= -2g(Z), with clipped Z = z+xsi
00126 double inline g_ss_div_s(double z, double xsi) { 
00127   // for consistency reasons we use the same clipped z as for g'.
00128   double Z = clip(z, -3.0, 3.0) + clip(xsi, -1.0, 1.0);  
00129   // approximation with Mittelwertsatz (z is clipped)
00130   return -2*g(Z);
00131 };
00132 
00133 /// an soft formula for g''/g' = -2Z, with clipped Z = z+xsi
00134 double inline g_ss_div_s_soft(double z, double xsi) { 
00135   // for consistency reasons we use the same clipped z as for g'.
00136   double Z = clip(z, -3.0, 3.0) + clip(xsi, -1.0, 1.0);  
00137   return -2*Z;//TEST
00138 };
00139 
00140 /** with \f[ g'(z) = 1-(g(z+\xi))^2 \f] we get 
00141     \f[\frac{\partial}{\partial z} \frac{1}{g'(Z)} = \frac{g''}{g'^2} \f] 
00142     again with clipped Z
00143  */
00144 double inline derive_g_s_inv_exact_clip(double z, double xsi){
00145   double Z = clip(z, -3.0, 3.0) + clip(xsi, -1.0, 1.0);  
00146   double k=tanh(Z);  // approximation with Mittelwertsatz 
00147   return -2*k/(1-k*k);
00148 }
00149 
00150 /** \f[ g'(z) = 1-(z+\xi)^2 \f] which is the series expansion to the second order
00151 */ 
00152 double inline g_s_expand2(double z, double xsi){
00153   double Z = z + clip(xsi, -fabs(z), fabs(z));  
00154   return 1/(1+sqr(Z));
00155 }
00156 
00157 /** \f[ \frac{1}{g'(z)} \approx 1+(z+\xi)^2 \f] with geometric series approximation
00158 */ 
00159 double inline g_s_inv_expand2(double z, double xsi){
00160   double Z = z + clip(xsi, -fabs(z)/2.0, fabs(z)/2.0);  
00161   return 1+sqr(Z);
00162 }
00163 
00164 /** \f[ \frac{g''(z)}{g'(z)} \approx 2(z+\xi)(1+(z+\xi)^2) \f] with geometric series approximation
00165 */ 
00166 double inline g_ss_div_s_expand2(double z, double xsi){
00167   double Z = z + clip(xsi, -fabs(z)/2.0, fabs(z)/2.0);  
00168   //  double Z = z + clip(xsi, -fabs(z), fabs(z));  
00169   return -2*tanh(Z); 
00170 }
00171 
00172 
00173   /// squashing function (-0.1 to 0.1), to protect against to large weight updates
00174 double inline squash(double z)
00175   {
00176     return clip(z, -0.1, 0.1);
00177     //return 0.1 * tanh(10.0 * z);
00178   };
00179  
00180   /// squashing function with adjustable clipping size, to protect against too large weight updates
00181 double inline squash(void* d, double z) {
00182     double size = *((double*)d);
00183     return clip(z, -size, size);
00184   };
00185 
00186 
00187 
00188 #endif
00189 

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