Neural network based audio signal denoising

In this paper, a novel filter is proposed by applying back propagation neural network (BPNN) ensemble where the noisy signal and the reference one are the same in a learning process. This neural network (NN) ensemble filter not only well reduces additive and multiplicative white noise inside signals, but also preserves signals' characteristics. It is proved that the reduction of noise using NN ensemble filter is better than the improved ε nonlinear filter and single NN filter while signal to noise ratio is low. The performance of the NN ensemble filter is demonstrated in the audio signals processing.

[1]  L. Montgomery Smith,et al.  Roundoff noise reduction in cascade realizations of FIR digital filters , 2000, IEEE Trans. Signal Process..

[2]  Bernardo Spagnolo,et al.  NONLINEAR RELAXATION IN POPULATION DYNAMICS , 2003 .

[3]  Hujun Yin,et al.  Image denoising using self-organizing map-based nonlinear independent component analysis , 2002, Neural Networks.

[4]  Hiroshi Harashima,et al.  ϵ‐separating nonlinear digital filter and its applications , 1982 .

[5]  T. Fechner.  Nonlinear noise filtering with neural networks: comparison with Weiner optimal filtering , 1993 .

[6]  Bernard Mulgrew,et al.  The use of ICA in multiplicative noise , 2006, Neurocomputing.

[7]  Qinyu Zhang,et al.  Additive and Multiplicative Noise Reduction by Back Propagation Neural Network , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  B. Spagnolo,et al.  NONLINEAR RELAXATION IN POPULATION DYNAMICS , 2002 .

[9]  R. Srinivasan,et al.  Removal of ocular artifacts from EEG using an efficient neural network based adaptive filtering technique , 1999, IEEE Signal Processing Letters.

[10]  Jian Yang,et al.  Speckle filtering in polarimetric SAR data based on the subspace decomposition , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[11]  M. A. Muñoz,et al.  Multiplicative Noise in Non-equilibrium Phase Transitions: A tutorial , 2003, cond-mat/0303650.

[12]  Jian Cheng,et al.  Applying a Wavelet Neural Network to Impulse Noise Removal , 2005, 2005 International Conference on Neural Networks and Brain.

[13]  M.T. Hagan,et al.  Multireference adaptive noise canceling applied to the EEG , 1997, IEEE Transactions on Biomedical Engineering.

[14]  X. Feng,et al.  Identification of high noise time series signals using hybrid ARMA modeling and neural network approach , 1993, IEEE International Conference on Neural Networks.

[15]  S. W. Piche,et al.  Steepest descent algorithms for neural network controllers and filters , 1994, IEEE Trans. Neural Networks.

[16]  P Rhodes,et al.  Publication. , 1983, Encyclopedic Dictionary of Archaeology.