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diff --git a/src/TNetLib/.svn/text-base/ObjFun.h.svn-base b/src/TNetLib/.svn/text-base/ObjFun.h.svn-base
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+#ifndef _TNET_OBJ_FUN_H
+#define _TNET_OBJ_FUN_H
+
+#include <cassert>
+#include <limits>
+#include <cmath>
+
+#include "Matrix.h"
+#include "Vector.h"
+
+namespace TNet {
+
+  /**
+   * General interface for objective functions
+   */
+  class ObjectiveFunction
+  {
+    public:
+    /// Enum with objective function types
+    typedef enum { 
+      OBJ_FUN_I = 0x0300, 
+      MEAN_SQUARE_ERROR, 
+      CROSS_ENTROPY, 
+    } ObjFunType;
+    
+    public:
+      /// Factory for creating objective function instances
+      static ObjectiveFunction* Factory(ObjFunType type);
+    
+    //////////////////////////////////////////////////////////////
+    // Interface specification
+    protected:
+      ObjectiveFunction() { }; /// constructor
+    public:
+      virtual ~ObjectiveFunction() { };  /// destructor
+
+      virtual ObjFunType GetType() = 0;
+      virtual const char* GetName() = 0;
+      virtual ObjectiveFunction* Clone() = 0; 
+
+      ///calculate error of network output
+      virtual void Evaluate(const Matrix<BaseFloat>& net_out, const Matrix<BaseFloat>& target, Matrix<BaseFloat>* err) = 0;
+ 
+      ///get the accumulated error
+      virtual double GetError() = 0;
+      ///the number of processed frames 
+      virtual size_t GetFrames() = 0;
+       
+      ///report the error to string 
+      virtual std::string Report() = 0;     
+
+      ///sum the frame counts from more instances
+      virtual void MergeStats(const ObjectiveFunction& inst) = 0;
+  };
+
+
+
+  /**
+   * Mean square error function
+   */
+  class MeanSquareError : public ObjectiveFunction
+  {
+   public:
+    MeanSquareError()
+     : ObjectiveFunction(), frames_(0), error_(0)
+    { }
+
+    ~MeanSquareError()
+    { }
+
+    ObjFunType GetType()
+    { return MEAN_SQUARE_ERROR; }
+
+    const char* GetName()
+    { return "<MeanSquareError>"; }
+
+    ObjectiveFunction* Clone()
+    { return new MeanSquareError(*this); }
+    
+    void Evaluate(const Matrix<BaseFloat>& net_out, const Matrix<BaseFloat>& target, Matrix<BaseFloat>* err);
+
+    size_t GetFrames()
+    { return frames_; }
+    
+    double GetError()
+    { return error_; }
+
+    std::string Report();    
+     
+    void MergeStats(const ObjectiveFunction& inst) { 
+      const MeanSquareError& mse = dynamic_cast<const MeanSquareError&>(inst);
+      frames_ += mse.frames_; error_ += mse.error_; 
+    }
+   
+   private:
+    size_t frames_;
+    double error_;
+
+  };
+
+
+  /**
+   * Cross entropy error function
+   */
+  class CrossEntropy : public ObjectiveFunction
+  {
+   public:
+    enum ConfusionMode { NO_CONF=0, MAX_CONF, SOFT_CONF, DIAG_MAX_CONF, DIAG_SOFT_CONF };
+
+   public:
+    CrossEntropy()
+     : ObjectiveFunction(), frames_(0), error_(0), corr_(0), confusion_mode_(NO_CONF), output_label_map_(NULL)
+    { }
+
+    ~CrossEntropy()
+    { }
+
+    ObjFunType GetType()
+    { return CROSS_ENTROPY; }
+
+    const char* GetName() 
+    { return "<cross_entropy>"; }
+
+    ObjectiveFunction* Clone()
+    { return new CrossEntropy(*this); }
+
+    void Evaluate(const Matrix<BaseFloat>& net_out, const Matrix<BaseFloat>& target, Matrix<BaseFloat>* err);
+
+    size_t GetFrames()
+    { return frames_; }
+    
+    double GetError()
+    { return error_; }
+
+    void SetConfusionMode(enum ConfusionMode m)
+    { confusion_mode_ = m; }
+
+    void SetOutputLabelMap(const char* map)
+    { output_label_map_ = map; }
+
+    std::string Report();    
+     
+    void MergeStats(const ObjectiveFunction& inst);   
+   private:
+    size_t frames_;
+    double error_;
+    size_t corr_;
+ 
+    ConfusionMode confusion_mode_;
+    Matrix<float> confusion_;
+    Vector<int> confusion_count_;
+    Vector<double> diag_confusion_;
+    const char* output_label_map_;
+  };
+ 
+
+} //namespace TNet
+
+
+#endif