1. Design Simulation of adaptive filter algorithm (LMS and NLMS) for acoustic echo cancellation
Name : Arum Tri Iswari Purwanti
NPM :
Department : Electrical Engineering
Supervisor : Raden Supriyanto SSi., SKom., MSc.

2. DESIGN AND IMPLEMENTATION
CONTENTS
INTRODUCTION
DESIGN AND IMPLEMENTATION
RESULT AND ANALYSIS
CONCLUSION

3. INTRODUCTION
Echo from the environment automatically added to the signal. In the real world application like hand-free communication, the echo can make the conversation impossible in the extreme condition.

4. Figure 1.1 Reverberation of the signal
INTRODUCTION
Acoustic echo occur when an audio signal is reverberated in a real environment, resulting in the original intended signal plus attenuated and delay time.
Figure 1.1 Reverberation of the signal

5. INTRODUCTION
When the signal is received by a system, its output will come out through the loudspeaker to the free environment.
The signal is reverberated in the environment and back into the system via microphone input.

6. DESIGN AND IMPLEMENTATION
The method used to cancel the echo signal is known as
ADAPTIVE FILTERING
Least Mean Square
(LMS)
Algorithm
Normalized Least Mean Square
(NLMS)
Algorithm

7. Least Mean Square (LMS) Algorithm
Each iteration of the LMS algorithm requires 3 distinct steps in this order:
Output of the FIR filter, y(n) is calculated using
The value of the error estimation is calculated using

8. Least Mean Square (LMS) Algorithm
The tap weights of the FIR vector are updated in preparation for the next iteration, by

9. Normalized Least Mean Square (NLMS) Algorithm
Each iteration of the NLMS algorithm requires these steps in the following order:
Output of the adaptive filter is calculated.
An error signal is calculated as the difference between the desired signal and the filter output.

10. Normalized Least Mean Square (NLMS) Algorithm
The step size value for the input vector is calculated.
The filter tap weights are updated in preparation for the next iteration.

11. DESIGN AND IMPLEMENTATION
The parameters are :
Error Estimation
Mean Square Error (MSE)
Echo Return Loss Enhancement (ERLE)
Attenuation
Accuracy Percentage

12. DESIGN AND IMPLEMENTATION
The configuration of an Acoustic Echo Cancellation

13. DESIGN AND IMPLEMENTATION
H(n) the impulse response between loudspeaker and microphone
d(n) the desired signal which is obtained by convolving the input signal with the impulse response of acoustic environment
y(n) the echo replica which is created at the output of the adaptive filter
e(n) error from the different between desired signal and the echo replica, e(n)=d(n)-y(n)

14. DESIGN AND IMPLEMENTATION
Figure 1.2 Overall system

15. DESIGN AND IMPLEMENTATION
To generate the desired signal, it can be done by convolving between the wav file input and the manipulation of the real impulse response.
To filter the echo, two algorithms (LMS and NLMS) will be compared each other based on their steps.
Each parameter will be calculated to know the better the algorithm between the LMS algorithm and the NLMS algorithm.

16. RESULT AND ANALYSIS
Based on the parameters :
Error Estimation

17. RESULT AND ANALYSIS
Mean Square Error (MSE)

18. RESULT AND ANALYSIS
ERLE, Attenuation, Accuracy Percentage, and Complexity

19. CONCLUSION Both algorithms can cancel the echo with its own algorithm.
The NLMS algorithm has so many advantages than the LMS algorithm such as the smaller values of error estimation, MSE, and attenuation and the higher values of ERLE and accuracy percentage.

20. CONCLUSION
The LMS algorithm also has the advantages such as the smaller value of complexity and better stability.
To implement the algorithm of adaptive filter for echo cancellation, the NLMS algorithm is better than the LMS algorithm

21. THANK YOU FOR YOUR ATTENTION