MATLAB ONLY) (MATLAB ONLY) (MATLAB

ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB

ONLY) (MATLAB ONLY) (MATLAB ONLY) ONLY) (MATLAB ONLY) (MATLAB ONLY) ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB (MATLAB ONLY) (MATLAB ONLY) (MATLAB (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) ONLY) (MATLAB ONLY) (MATLAB ONLY)

(MATLAB ONLY) (MATLAB ONLY) (MATLAB

(MATLAB ONLY) (MATLAB ONLY) (MATLAB

(MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY)

ONLY) (MATLAB ONLY) (MATLAB ONLY)

ONLY) (MATLAB ONLY) (MATLAB ONLY)

ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB ONLY) (MATLAB

(MATLAB ONLY) (MATLAB ONLY) (MATLAB

(MATLAB ONLY) MATLAB ONLY)

using the first id:1001368

second id:1002109

Project Description: This project aims to consider different signal processing techniques to analyze signals in both time domain and frequency domain, taking into consideration factors that will be tackled by implementing the following: Import an audio file of your choice by using audioread(). a) Signal Echo 1. Plot the original audio signal in the time and frequency domains (in one figure). 2. Generate a shifted version of the original signal (original signal with a phase shift). Plot it in the time and frequency domains (in one figure). 3. Add it to the original unshifted signal. 4. Play the output audio sound. b) Noise Addition 1. Generate a noise signal: 0.1*cos(2*pi*50*d1*t) + 0.1*cos(2*pi*50*d2*t) + 0.1*cos(2*pi*50*d3*t), where d1, d2 and d3 are the project members' ID number. (Let d1=d2 in case you are only 2 members) 2. Plot the noise signal in both time and frequency domains (in one figure). 3. Add the noise to the audio signal and plot it in the time and frequency domains (in one figure). 4. Calculate the SNR (using the SNR function embedded in MATLAB) 5. Play the output audio sound. c) Noise Cancellation 1. Generate a filter of any method to eliminate the noise effect from the signal of the previous point. 2. Plot the filter response. 3. Plot the retrieved signal after filtering out the noise (in one figure with the filter response). 4. Play the output audio sound. HINT: Use the subplot() function to plot more than one signal in one figure. Project Description: This project aims to consider different signal processing techniques to analyze signals in both time domain and frequency domain, taking into consideration factors that will be tackled by implementing the following: Import an audio file of your choice by using audioread(). a) Signal Echo 1. Plot the original audio signal in the time and frequency domains (in one figure). 2. Generate a shifted version of the original signal (original signal with a phase shift). Plot it in the time and frequency domains (in one figure). 3. Add it to the original unshifted signal. 4. Play the output audio sound. b) Noise Addition 1. Generate a noise signal: 0.1*cos(2*pi*50*d1*t) + 0.1*cos(2*pi*50*d2*t) + 0.1*cos(2*pi*50*d3*t), where d1, d2 and d3 are the project members' ID number. (Let d1=d2 in case you are only 2 members) 2. Plot the noise signal in both time and frequency domains (in one figure). 3. Add the noise to the audio signal and plot it in the time and frequency domains (in one figure). 4. Calculate the SNR (using the SNR function embedded in MATLAB) 5. Play the output audio sound. c) Noise Cancellation 1. Generate a filter of any method to eliminate the noise effect from the signal of the previous point. 2. Plot the filter response. 3. Plot the retrieved signal after filtering out the noise (in one figure with the filter response). 4. Play the output audio sound. HINT: Use the subplot() function to plot more than one signal in one figure