           H = min( C, C + alphas[j] - alphas[i] );
         } /* end else */
 
+  //      printf("L %f H %f\n",L,H);
+
         if( L == H ) continue;
 
         eta = 2.0f * K[INDX(i,j,trainingSize)] 
                    - K[INDX(i,i,trainingSize)] 
                    - K[INDX(j,j,trainingSize)];
+
+   //     printf("eta %f\n",eta);
 
         if( eta >= 0.0f ) continue;
 

  int featureVectorSize = FEATURE_VECTOR_SIZE;
  int trainingSize = TRAINING_SIZE;
  int *resultVector, *trainingMatrix;
  int passes=0, maxPasses=5, numChangedAlphas;
  float *X, *y, *K, *E, *alphas;
  float b=0.0f, eta=0.0f, L=0.0f, H=0.0f, tol=1.0e-3;
  float C=0.1f;

        while( j == i ) 
          j = ceil( (float) trainingSize * 
                      float( rand() ) / ( float(RAND_MAX) + 1.0f ) );
//        j = 3918;
 //       printf("j is %d\n",j);

        for( int k = 0; k < trainingSize; k++ )
        {  
