Abstract:
In this project work, we have used two algorithms of Neural Network (NN): Backpropagation and
Hopfield NN to de-noise speech signal. The backpropagation algorithm is found suitable to
remove random noise but very poor in the removal of awgn (Additive White Gaussian Noise). The
Hopfield NN shows completely reverse performance i.e. suitable for awgn but very poor for
random noise. The performance of both algorithms is measured graphically with an original
recovered signal, MSE, the convergence of regression and error histogram.
Description:
This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electronics and Telecommunication Engineering of East West University, Dhaka, Bangladesh
