Artificial Neural Net Based Noise Cancellor

This paper p r e s e n t s a new n o i s e c a n c e l l a t i o n with an Neural Network. The network feedforward one with t h r e e method for A r t i f i c i a l used is a l a y e r s . The backpropagati on and s tas ti cal Cauchy’ s 1 ear n i ng a1 gor i t hms are empl oyed for a d a p t a t i o n of t h e i n t e r n a l parameters of t h e network. The c o n s t r a i n e d tangent hyperbol ic f u n c t i o n is used t o a c t i v a t e t h e neurons and t o provide t h e d e s i r e d non-1 i n e a r i t y . Promi s i n g si m u l a t i on r e s u l t s f o r n o i s e c a n c e l l a t i o n i n t e n s i f y t h e val i d i t y of superseding t h e proposed scheme f o r many e x i s t i n g techniques. To demonstrate t h e e f f e c t i v e n e s s . t h e proposed method is app l i ed t o . d i f f e r e n t i n p u t c o n d i t i o n s with varying S N R s . With incomplete s i g n a l samples t h e net is found t o produce output having a s t r i k i n g resemblance with t h a t of t h e d e s i r e d ones. A performance comparision of t h e t w o a lgo r i thms is presented i n t h e paper f o r b e t t e r a p p r a i s a l .