Matlab Simulation of Cordic based Adaptive Filtering for Noise Reduction using Sensors Array

Abstract

The process of suppressing noise and interference in any type of signal for transmission has created challenges in the area of digital signal processing. Apart from mobile communication devices, there are a huge number of applications, in which it is difficult to have a good acoustic interface for accurate voice control or smooth audio communication. So for this it is very essential to enhance the signal by removing its noise.For this a cordic based adaptive algorithm has been designed and simulated for digital signal processing. When the input signals statistics to the filter are time varying or unknown and the design requirements for fixed filters cannot easily be specified then adaptive filter is useful. Examples of such applications are system identification, channel, equalization /identification, noise reduction in digital signal processing. These algorithms are also used in case of beamforming. Array of sensors (microphones) play an important role in noise reduction and speech enhancement. In this paper a cordic based qrd_rls adaptive (CQR_RLS) algorithm is developed and simulated using MATLAB. Instead of taking signal from one sensor here array of sensor is used for signal as well as interference.Matlab simulation results are calculated and compared for different iteration. General TermsAdaptive algorithm, Matlab

Improving the SNR of the underwater acoustic signal affected by wind driven ambient noise using RLS algorithm

“…The RLS approach offers faster convergence and smaller error with respect to the unknown system, at the expense of requiring more computations as compare to LMS algorithm [10]. The main drawback of the LMS algorithm is that it is very sensitive towards the scaling of its input sequence vector [11].…”