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diff --git a/src/CuTNetLib/cuBiasedLinearity.h b/src/CuTNetLib/cuBiasedLinearity.h
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+#ifndef _CUBIASED_LINEARITY_H_
+#define _CUBIASED_LINEARITY_H_
+
+
+#include "cuComponent.h"
+#include "cumatrix.h"
+
+
+#include "Matrix.h"
+#include "Vector.h"
+
+
+namespace TNet {
+  /**
+   * \brief CuBiasedLinearity summation function
+   *
+   * \ingroup CuNNUpdatable
+   * Implements forward pass: \f[ Y_j=\Sigma_{i=0}^{i=N-1}w_ij X_i +{\beta}_j \f]
+   * Error propagation: \f[ E_i = \Sigma_{i=0}^{i=N-1} w_ij e_j \f]
+   *
+   * Weight adjustion: \f[ W_{ij} = (1-D)(w_{ij} - \alpha(1-\mu)x_i e_j - \mu \Delta) \f]
+   * and fot bias: \f[ {\Beta}_i = {\beta}_i - \alpha(1-\mu)e_i - \mu \Delta \f]
+   * where
+   *  - D for weight decay => penalizing large weight
+   *  - \f$ \alpha \f$ for learning rate
+   *  - \f$ \mu \f$ for momentum => avoiding oscillation
+   */
+  class CuBiasedLinearity : public CuUpdatableComponent
+  {
+    public:
+
+      CuBiasedLinearity(size_t nInputs, size_t nOutputs, CuComponent *pPred); 
+      ~CuBiasedLinearity();  
+      
+      ComponentType GetType() const;
+      const char* GetName() const;
+
+      void PropagateFnc(const CuMatrix<BaseFloat>& X, CuMatrix<BaseFloat>& Y);
+      void BackpropagateFnc(const CuMatrix<BaseFloat>& X, CuMatrix<BaseFloat>& Y);
+
+      void Update();
+
+      void ReadFromStream(std::istream& rIn);
+      void WriteToStream(std::ostream& rOut);
+
+    protected:
+      CuMatrix<BaseFloat> mLinearity;  ///< Matrix with neuron weights
+      CuVector<BaseFloat> mBias;       ///< Vector with biases
+
+      CuMatrix<BaseFloat> mLinearityCorrection; ///< Matrix for linearity updates
+      CuVector<BaseFloat> mBiasCorrection;      ///< Vector for bias updates
+
+  };
+
+
+
+
+  ////////////////////////////////////////////////////////////////////////////
+  // INLINE FUNCTIONS 
+  // CuBiasedLinearity::
+  inline 
+  CuBiasedLinearity::
+  CuBiasedLinearity(size_t nInputs, size_t nOutputs, CuComponent *pPred)
+    : CuUpdatableComponent(nInputs, nOutputs, pPred), 
+      mLinearity(nInputs,nOutputs), mBias(nOutputs),
+      mLinearityCorrection(nInputs,nOutputs), mBiasCorrection(nOutputs)
+  { 
+    mLinearityCorrection.SetConst(0.0);
+    mBiasCorrection.SetConst(0.0);
+  }
+
+
+  inline
+  CuBiasedLinearity::
+  ~CuBiasedLinearity()
+  { }
+
+  inline CuComponent::ComponentType
+  CuBiasedLinearity::
+  GetType() const
+  {
+    return CuComponent::BIASED_LINEARITY;
+  }
+
+  inline const char*
+  CuBiasedLinearity::
+  GetName() const
+  {
+    return "<biasedlinearity>";
+  }
+
+
+
+} //namespace
+
+
+
+#endif