Adaptive filtering in adaptive feedback cancellation for PA systems

Bachelor thesis (2020)

Authors

C.H. Kos Electrical Engineering, Mathematics and Computer Science
M.C. Bekkering Electrical Engineering, Mathematics and Computer Science

Contributors

R.C. Hendriks Signal Processing Systems - EEMCS (supervisor 1)
Jorge Martinez Electrical Engineering Education - EEMCS (supervisor 1)
S. Izadkhast Electrical Engineering Education - EEMCS (supervisor 2)
J.E.J. Schmitz Electrical Engineering, Mathematics and Computer Science (supervisor 2)
M. Çalış Signal Processing Systems - EEMCS (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2020 C.H. Kos, M.C. Bekkering
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Published Date

03-07-2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This report is written as part of the Bachelor Graduation Project in the third year of the Electrical Engineering Bachelor programme at the Delft University of Technology. This report is made by a subgroup that is part of a larger project dedicated to finding a solution to frequency feedback in electroacoustic systems, also known as the Larsen effect.

This problem has a long history of literature and many solutions to this problem have been presented. For this project, the focus lies on the application of Adaptive Feedback Cancellation (AFC). This technique uses estimations of the Room Impulse Response (RIR) to minimise the feedback component. This report focuses on estimating such a RIR in the case of a PA system. Several methods will be discussed and compared by implementing and testing them in a simulation environment built in Matlab. The different methods are subjected to a set of performance measurements that provide the necessary information to see for each method and situation if and how the results measure up against a set of predetermined system requirements. From the researched algorithms, one is chosen as the one to be implemented in the final design of the group. At last, some considerations and recommendations are given for implementing one of the algorithms into software and hardware components.