• A.M.Prasanna Kumar
• K.Ramesha

Noise in an audio signal has become major problem and hence mobile communication systems are demanding noise-free signal. In order to achieve noise-free signal various research communities have provided significant techniques. Adaptive noise cancellation (ANC) is a kind of technique which helps in estimation of un-wanted signal and remove them from corrupted signal. This paper introduces an Intelligent Adaptive Filter Based Noise Cancellation System (AFNCS) that incorporates a hybrid back propagation learning for the adaptive noise cancellation in mobile applications. The proposed hybrid algorithm consists all the significant features of Least Mean Square (LMS) and Gradient Adaptive Lattice (GAL) algorithms. The performance analysis of the method is performed by considering convergence complexity and Bit Error Rate (BER) parameters. The outcomes suggests the errors are reduced significantly when the number of epochs are increased. Also, incorporation of less hidden layers resulted in negligible computational delay along with effective utilization of memory.

Adaptive Filter, Noise Cancellation, Convergence Complexity, Bit Error Rate (BER), Adaptive noise cancellation, Mobile Communication.

"AFNCS: An Intelligent Adaptive Filter Based Noise Cancellation System for Mobile Communications ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.644-650, September-2018, Available :http://www.jetir.org/papers/JETIR1809130.pdf

"AFNCS: An Intelligent Adaptive Filter Based Noise Cancellation System for Mobile Communications ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp644-650, September-2018, Available at : http://www.jetir.org/papers/JETIR1809130.pdf