Lab 10 Signal noise compression

Paper Review

      Paper topic: Adaptive noise cancellation using LMS algorithm.
     Paper was based on the minimization of the squared Euclidean norm of the difference weight vector under a stability constraint to remove the noise from sample. To this purpose, the Lagrangian methodology has been used in order to propose a nonlinear adaptation rule defined in terms of the product of differential inputs and errors which means a generalization of the normalized (N)LMS algorithm. The proposed method yields better tracking ability in this context as shown in the experiments which are carried out on the AURORA 2 and 3 speech database.

Patent rewiev:
Patent no. 5,682,341
Topic:
           Adaptive signal processing using NETWORK/LMS algorithm
          
    In this patent Newton/least mean square algorithm was adapted to remove signal distortion and noise. The adaptive signal processor is used to get the autocorrelation matrix by executing DFT and IDFT,and to apply the derived inverse matrix to an adaptive signal processing thereby reducing the computation to derive the inverse matrix reducing the cost.
Paper link-https://drive.google.com/open?id=0B9yXRTSFouTyaXRYUEVVNVJtMHM

Plagarism report-https://drive.google.com/open?id=0B9yXRTSFouTyaXRYUEVVNVJtMHM