Diff: SRNN.cpp

Revision:

2:d623e7ef4dca

Parent:

1:da597cb284a2

Child:

4:9d94330f380a

--- a/SRNN.cpp	Sun Feb 15 04:05:35 2015 +0000
+++ b/SRNN.cpp	Sun Feb 15 09:27:31 2015 +0000
@@ -51,12 +51,9 @@
 
 SRNN::~SRNN(void)
 {
-    delete [] sample;
-    delete [] sample_maxmin;
-    delete [] predict_signal;
-    delete [] Win_mid;
-    delete [] Wmid_out;
-    delete [] expand_in_signal;
+    delete [] sample; delete [] sample_maxmin;
+    delete [] predict_signal; delete [] Win_mid;
+    delete [] Wmid_out; delete [] expand_in_signal;
     delete [] expand_mid_signal;
 }
 
@@ -73,8 +70,7 @@
 void SRNN::predict(float* input)
 {
     float *norm_input = new float[this->dim_signal];
-
-
+    
     // output signal
     float* out_signal = new float[dim_signal];
     // value of network in input->hidden layer
@@ -184,15 +180,15 @@
 
     // 前回の二乗誤差値:収束判定に用いる.
     float prevError;
-
+    squareError = FLT_MAX;
     /* 学習ループ */
     while (1) {
 
         // 終了条件を満たすか確認
         if (!end_flag) {
-            end_flag = !(iteration < this->maxIteration
-                         && (iteration <= this->len_seqence
-                             || this->squareError > this->goalError)
+            end_flag = !(iteration < maxIteration
+                         && (iteration <= len_seqence
+                             || squareError > goalError)
                         );
         }
 
@@ -260,7 +256,7 @@
                                               MATRIX_AT(sample_maxmin,2,i,0),
                                               MATRIX_AT(sample_maxmin,2,i,1));
         }
-        printf("predict : %f %f %f \r\n", predict_signal[0], predict_signal[1], predict_signal[2]);
+        // printf("predict : %f %f %f \r\n", predict_signal[0], predict_signal[1], predict_signal[2]);
 
         // print_mat(Wmid_out, row_mid_out, col_mid_out);
 
@@ -366,3 +362,9 @@
 
     return squareError;
 }
+
+// サンプルの（リ）セット
+void SRNN::set_sample(float* sample_data)
+{
+    memcpy(sample, sample_data, sizeof(float) * len_seqence * dim_signal);
+}