Real-Time Noise Cancellation Using Adaptive Algorithms

ABSTRACT: The contamination of a signal of interest by other undesired signals (noise) is a problem encountered in many applications. The conventional linear digital filters with fixed coefficients exhibit a satisfactory performance in extracting the desired signal when the signal and noise occupy fixed and separate frequency bands. However, in most applications, the desired signal has changing characteristics which requires an update in the filter coefficients for a good performance in the signal extraction. Since the conventional digital filters with fixed coefficients do not have the ability to update their coefficients, adaptive digital filters are used to cancel the noise. The mean square error (MSE) technique is used as a measure of the noise reduction. The adaptive filter generally uses finite impulse response (FIR) least-mean-square (LMS) and normalized LMS (NLMS) algorithms in signal processing or infinite impulse response (IIR) recursive-least-squares (RLS) algorithm in adaptive control for the noise cancellation applications. The main aim of this thesis is to investigate the implementation of a real time noise cancellation application. The real time implementation is carried out by a Texas Instruments (TI) TMS320C6416T Digital Signal Processor (DSP). First, the LMS, NLMS and RLS algorithms are simulated using SIMULINK of MATLAB. Then, these algorithms have been transferred to the DSP board which let, them to work alone in real time independent of MATLAB. Furthermore, the performance of the aforementioned algorithms has been compared in different problem settings. Keywords: Adaptive Filters, FIR Filters, IIR Filters, LMS Algorithm, NLMS Algorithm, RLS Algorithm. …………………………………………………………………………………………………………