Non Linear Channel Equalization Using Artificial Neural Network

@inproceedings{KatwalNonLC,
  title={Non Linear Channel Equalization Using Artificial Neural Network},
  author={Swati Katwal and Vinay Bhatia}
}
Channel equalization refers to a process used to combat noise and intersymbol interference. In this paper, we review the application of Artificial Neural Network (ANN) for adaptive channel equalization in a digital communication system using 4-Quadrature Amplitude Modulation (QAM) signal constellation. The literature is associated with different neural network based equalizer such as Legendre functional link ANN and Chebyshev ANN. 

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
Showing 1-10 of 18 references

maity, “Non linear channel equalization for digital communication using DE trained functional link artificial neural networks’’, springer berlin

Gyana rajan patra, Syan
Heidelberg, vol.2, • 2011

shrivastava, “Channel Equalization using neural network

Kavita burse, S.C.R.N Yadav
IEEE. Trans.vol.40, • 2010

N

J. C. Patra, W. B. Poh
S. Chaudhari and A. Das,“ Nonlinear Channel Equalization with QAM Signal Using Chebyshev Artificial Neural Network”, IEE IJCNN Montreal, Canada, pp. 3214-3217, Jul • 2009

Reduced decision feedback FLAN nonlinear channel equalizer for digital equalization systems,’

W. D Weng, C. T. Yen
IEEE Proc. Comm., • 2004
View 1 Excerpt

Anthony Calise , ‘ ‘ Adaptive output feedback control of uncertain nonlinear systems using singlehidden layer neural network

Naria Hovakimyan, Flavio Nardi
2001