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The Noise Eliminator Using Fast Fourier Transform in CCStudios and MatLab. Presented to: Dr Li By: Megan Myles & David Jackson. The Noise Eliminator. Researching Project Idea Visited Various DSP Websites Implemented idea in MatLab to test the concept

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the noise eliminator using fast fourier transform in ccstudios and matlab

The Noise Eliminator Using Fast Fourier Transform in CCStudios and MatLab

Presented to: Dr Li

By: Megan Myles & David Jackson

the noise eliminator
The Noise Eliminator

Researching Project Idea

  • Visited Various DSP Websites
  • Implemented idea in MatLab to test the concept
  • Interviewed Dr. Li and other engineers about the noise eliminator
steps followed in matlab
Steps followed in MatLab
  • Input wave file into MatLab as a vector
  • Run noisy signal through a Fourier Transform
  • Change all values of the signal points to zero except the first and last few.
  • Run signal through an inverse Fourier transform
  • Take only real part of ifft
  • This final signal will be the clear signal extracted from the noise
matlab code
MatLab Code

fs=22050;

s=20000;

x=wavread('5000noisywav.wav');

wavplay(x,fs);

f=fft(x);

f(s+1:220500-s,:)=0;

i=real(ifft(f));

wavplay(i,fs);

isrs c in cc studio
ISRs.c in CC Studio

#include "..\..\..\Common_Code\DSK_Config.h“

#include "math.h"

#include "frames.h"

// frame buffer declarations

#define BUFFER_COUNT 1024 // buffer length in McBSP samples (L+R)

#define BUFFER_LENGTH BUFFER_COUNT*2 // two shorts read from

s = 100;

for(i=s;i < BUFFER_COUNT-s;i++){

x[i].real = 0.0;

x[i].imag = 0.0;

what we learned
What We Learned
  • Fast Fourier Transform - Chapter 8

FFT is a fast way for computers to calculate the Fourier transform.

The difference between the FFT and IFFT is simply the division by N and the negative powers of the twiddle factors.

The algorithm can be used for both the FFT and IFFT.

learning contd
Learning Contd.
  • Using the FFT for filtering

As the order of a filter increases the time required to calculate the output value associated with each input sample also increases.

  • Frame based filtering helps increase the overall efficiency of the filtering and reduces the time required to pass various samples. (Chapter 7)
conclusion
Conclusion

Noise filters have many uses:

  • Filter engine noise from car audio
  • Filter static from cell phone transmissions
  • Even filter an image for better clarity
  • Noise filters improve the quality of life around the world