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Data Processing and Smoothing Techniques in Code: A Comprehensive Guide

Explore different methods of noise reduction and signal processing in code with examples in audio and image processing domains. Learn about smoothing functions, vector operations, and convolution techniques to enhance data quality. Discover how to differentiate noise from signal and apply effective filtering methods. Gain insights on audio processing, including reading, playing, and manipulating audio files. Dive into practical applications like adding echo effects and removing vocals. Maximize your understanding of high and low-frequency processing to optimize data analysis and enhance signal clarity.

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Data Processing and Smoothing Techniques in Code: A Comprehensive Guide

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  1. L34: Noise and Signal

  2. Announcements • Away next Friday, the class will be taught by …. • No office hours next Wednesday • Assignment 4

  3. Smoothing functions • Audio processing • Image processing

  4. What does this code do? t=linspace(0,2*pi,101); y=sin(t); y=sin(t)+0.1*(rand(size(t))-0.5); y_mod=y; for i=2:length(t)-1 y_mod(i)=(y(i-1)+y(i)+y(i+1))/3; end

  5. Noise vs Signal plots plot(t,y); hold on; plot(t,y_mod,’r’);

  6. Other ways of smoothing • Vector additions y_mod=y; y_mod(2:end-1)=(y(1:end-2)+y(2:end-1)+y(3:end))/3; • Convolution/Filtering y_mod=imfilter(y,[1 1 1]/3);

  7. What does this code do? t=linspace(0,2*pi,101); y=sin(t)+0.1*(rand(size(t))-0.5); y_mod=y; for i=2:length(t)-1 y_mod(i)=y(i)-y(i-1); end plot(t,y_mod);

  8. Other ways of doing the same thing • Vector minus y_mod=y; y_mod(2:end)=y(2:end)-y(1:end-1); • Convolution/Filtering y_mod=imfilter(y,[-1 1]);

  9. Takeaways • Averaging smoothens i.e. suppresses high frequency jitter • Differentiating amplifies noise i.e. suppresses low frequency signal

  10. Audio processing • Reading in a wav file • [audio_var,fs]=wavread(‘hootie.wav’); • Audio variables are just two column matrices: first column is the left channel and the second column is the right channel • Playing audio • soundsc(audio_var,fs); • soundsc(audio_var(:,1),fs); %plays left channel

  11. Vector operations on audio files left=audio_var(:,1); right=audio_var(:,2); plot(left) soundsc(left(end:-1:1,:),fs)

  12. Adding echo N=10000; left_echo=left; for i=N+1:length(left) left_echo=left(i)+left(i-N); end

  13. Removing vocals • Vocals are, in general, recorded on both the left and right channel. So…. • soundsc(left-right, fs)

  14. High frequency (noise) and low frequency (signal) • Suppressing high frequency (smoothing) left_smooth=imfilter(left,ones(10,1)); • Suppressing low frequency (differentiating) left_der=left(2:end)-left(1:end-1);

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