Development of Neural Networks for Noise Reduction

This paper describes the development of neural network models for noise reduction. The networks used to enhancethe performance of modeling captured signals by reducing the effect of noise. Both recurrent and multi-layer Backpropagationneural networks models are examined and compared with different training algorithms. The paper presented is to illustratethe effect of training algorithms and network architecture on neural network performance for a given application