Adaptive Digital Filter Design for Linear Noise Cancellation Using Neural Networks

Noise is the most serious issue in the filters and adaptive filters are subjected to this unwanted component. This paper deals with the problem of the adaptive noise and various adaptive algorithms functions which when implemented practically shows that the noise is cancelled or removed by the neural network approach using the exact random basis function. The adaptive filters are used to control the noise and it has a linear input and output characteristics. This approach is done so as to get the minimum possible error so that to obtain the error free desired signal. The designed filter will reduce this noise from measured signal by a reference signal which is highly correlated with the noise signal. This approach gives excellent result for this signal processing technique that removes or eliminates the linear noise from the different functions. The simulation results are also mentioned so as to gives a vivid idea of reduced noise using neural networks algorithm.