| /* Copyright (c) 2008-2011 Octasic Inc. |
| Written by Jean-Marc Valin */ |
| /* |
| Redistribution and use in source and binary forms, with or without |
| modification, are permitted provided that the following conditions |
| are met: |
| |
| - Redistributions of source code must retain the above copyright |
| notice, this list of conditions and the following disclaimer. |
| |
| - Redistributions in binary form must reproduce the above copyright |
| notice, this list of conditions and the following disclaimer in the |
| documentation and/or other materials provided with the distribution. |
| |
| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
| ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
| LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
| A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE FOUNDATION OR |
| CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
| EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
| PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR |
| PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF |
| LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING |
| NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS |
| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| */ |
| |
| #ifndef _MLP_TRAIN_H_ |
| #define _MLP_TRAIN_H_ |
| |
| #include <math.h> |
| #include <stdlib.h> |
| |
| double tansig_table[501]; |
| static inline double tansig_double(double x) |
| { |
| return 2./(1.+exp(-2.*x)) - 1.; |
| } |
| static inline void build_tansig_table(void) |
| { |
| int i; |
| for (i=0;i<501;i++) |
| tansig_table[i] = tansig_double(.04*(i-250)); |
| } |
| |
| static inline double tansig_approx(double x) |
| { |
| int i; |
| double y, dy; |
| if (x>=10) |
| return 1; |
| if (x<=-10) |
| return -1; |
| i = lrint(25*x); |
| x -= .04*i; |
| y = tansig_table[250+i]; |
| dy = 1-y*y; |
| y = y + x*dy*(1 - y*x); |
| return y; |
| } |
| |
| static inline float randn(float sd) |
| { |
| float U1, U2, S, x; |
| do { |
| U1 = ((float)rand())/RAND_MAX; |
| U2 = ((float)rand())/RAND_MAX; |
| U1 = 2*U1-1; |
| U2 = 2*U2-1; |
| S = U1*U1 + U2*U2; |
| } while (S >= 1 || S == 0.0f); |
| x = sd*sqrt(-2 * log(S) / S) * U1; |
| return x; |
| } |
| |
| |
| typedef struct { |
| int layers; |
| int *topo; |
| double **weights; |
| double **best_weights; |
| double *in_rate; |
| } MLPTrain; |
| |
| |
| #endif /* _MLP_TRAIN_H_ */ |