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diff --git a/src/CuTNetLib/cuNetwork.h b/src/CuTNetLib/cuNetwork.h
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+#ifndef _CUNETWORK_H_
+#define _CUNETWORK_H_
+
+#include "cuComponent.h"
+
+#include "cuBiasedLinearity.h"
+//#include "cuBlockLinearity.h"
+//#include "cuBias.h"
+//#include "cuWindow.h"
+
+#include "cuActivation.h"
+
+#include "cuCRBEDctFeat.h"
+
+#include "Vector.h"
+
+#include <vector>
+
+/**
+ * \file cuNetwork.h
+ * \brief CuNN manipulation class
+ */
+
+/// \defgroup CuNNComp CuNN Components
+
+namespace TNet {
+  /**
+   * \brief Nural Network Manipulator & public interfaces
+   *
+   * \ingroup CuNNComp
+   */
+  class CuNetwork
+  {
+    //////////////////////////////////////
+    // Typedefs
+    typedef std::vector<CuComponent*> LayeredType;
+      
+      //////////////////////////////////////
+      // Disable copy construction, assignment and default constructor
+    private:
+      CuNetwork(CuNetwork&); 
+      CuNetwork& operator=(CuNetwork&);
+       
+    public:
+      CuNetwork() { }
+      CuNetwork(std::istream& rIn); 
+      ~CuNetwork();
+
+      void AddLayer(CuComponent* layer);
+
+      int Layers()
+      { return mNetComponents.size(); }
+
+      CuComponent& Layer(int i)
+      { return *mNetComponents[i]; }
+
+      /// forward the data to the output
+      void Propagate(CuMatrix<BaseFloat>& in, CuMatrix<BaseFloat>& out);
+
+      /// backpropagate the error while updating weights
+      void Backpropagate(CuMatrix<BaseFloat>& globerr); 
+
+      void ReadNetwork(const char* pSrc);     ///< read the network from file
+      void WriteNetwork(const char* pDst);    ///< write network to file
+
+      void ReadNetwork(std::istream& rIn);    ///< read the network from stream
+      void WriteNetwork(std::ostream& rOut);  ///< write network to stream
+
+      size_t GetNInputs() const; ///< Dimensionality of the input features
+      size_t GetNOutputs() const; ///< Dimensionality of the desired vectors
+
+      /// set the learning rate
+      void SetLearnRate(BaseFloat learnRate, const char* pLearnRateFactors = NULL); 
+      BaseFloat GetLearnRate();  ///< get the learning rate value
+      void PrintLearnRate();     ///< log the learning rate values
+
+      void SetMomentum(BaseFloat momentum);
+      void SetWeightcost(BaseFloat weightcost);
+      void SetL1(BaseFloat l1);
+
+      void SetGradDivFrm(bool div);
+      
+      /// Reads a component from a stream
+      static CuComponent* ComponentReader(std::istream& rIn, CuComponent* pPred);
+      /// Dumps component into a stream
+      static void ComponentDumper(std::ostream& rOut, CuComponent& rComp);
+
+      
+    private:
+      /// Creates a component by reading from stream
+      CuComponent* ComponentFactory(std::istream& In);
+
+
+    private:
+      LayeredType mNetComponents; ///< container with the network layers
+      CuComponent* mpPropagErrorStopper;
+      BaseFloat mGlobLearnRate; ///< The global (unscaled) learn rate of the network
+      const char* mpLearnRateFactors; ///< The global (unscaled) learn rate of the network
+      
+
+    //friend class NetworkGenerator; //<< For generating networks...
+
+  };
+    
+  //////////////////////////////////////////////////////////////////////////
+  // INLINE FUNCTIONS 
+  // CuNetwork::
+  inline 
+  CuNetwork::
+  CuNetwork(std::istream& rSource)
+    : mpPropagErrorStopper(NULL), mGlobLearnRate(0.0), mpLearnRateFactors(NULL)
+  {
+    ReadNetwork(rSource);
+  }
+
+
+  inline
+  CuNetwork::
+  ~CuNetwork()
+  {
+    //delete all the components
+    LayeredType::iterator it;
+    for(it=mNetComponents.begin(); it!=mNetComponents.end(); ++it) {
+      delete *it;
+      *it = NULL;
+    }
+    mNetComponents.resize(0);
+  }
+
+  
+  inline void 
+  CuNetwork::
+  AddLayer(CuComponent* layer)
+  {
+    if(mNetComponents.size() > 0) {
+      if(GetNOutputs() != layer->GetNInputs()) {
+        Error("Nonmatching dims");
+      }
+      layer->SetPrevious(mNetComponents.back());
+      mNetComponents.back()->SetNext(layer);
+    }
+    mNetComponents.push_back(layer);
+  }
+
+
+  inline void
+  CuNetwork::
+  Propagate(CuMatrix<BaseFloat>& in, CuMatrix<BaseFloat>& out)
+  {
+    //empty network => copy input
+    if(mNetComponents.size() == 0) { 
+      out.CopyFrom(in); 
+      return;
+    }
+
+    //check dims
+    if(in.Cols() != GetNInputs()) {
+      std::ostringstream os;
+      os << "Nonmatching dims"
+         << " data dim is: " << in.Cols() 
+         << " network needs: " << GetNInputs();
+      Error(os.str());
+    }
+    mNetComponents.front()->SetInput(in);
+    
+    //propagate
+    LayeredType::iterator it;
+    for(it=mNetComponents.begin(); it!=mNetComponents.end(); ++it) {
+      (*it)->Propagate();
+    }
+
+    //copy the output
+    out.CopyFrom(mNetComponents.back()->GetOutput());
+  }
+
+
+
+
+  inline void 
+  CuNetwork::
+  Backpropagate(CuMatrix<BaseFloat>& globerr) 
+  {
+    mNetComponents.back()->SetErrorInput(globerr);
+
+    // back-propagation
+    LayeredType::reverse_iterator it;
+    for(it=mNetComponents.rbegin(); it!=mNetComponents.rend(); ++it) {
+      //stopper component does not propagate error (no updatable predecessors)
+      if(*it != mpPropagErrorStopper) {
+        //compute errors for preceding network components
+        (*it)->Backpropagate();
+      }
+      //update weights if updatable component
+      if((*it)->IsUpdatable()) {
+        CuUpdatableComponent& rComp = dynamic_cast<CuUpdatableComponent&>(**it); 
+        if(rComp.LearnRate() > 0.0f) {
+          rComp.Update();
+        }
+      }
+      //stop backprop if no updatable components precede current component
+      if(mpPropagErrorStopper == *it) break;
+    }
+  }
+
+      
+  inline size_t
+  CuNetwork::
+  GetNInputs() const
+  {
+    if(!mNetComponents.size() > 0) return 0;
+    return mNetComponents.front()->GetNInputs();
+  }
+
+
+  inline size_t
+  CuNetwork::
+  GetNOutputs() const
+  {
+    if(!mNetComponents.size() > 0) return 0;
+    return mNetComponents.back()->GetNOutputs();
+  }
+
+} //namespace
+
+#endif
+
+