AUDIO SIEVING USING SIGNAL FILTERS
A project under V.6.2 – Signals and System Engineering
Yatharth Aggarwal Sagar Mayank Chauhan Rajan
Table of Contents
Introduction ...... 2 Filters ...... 4 Butterworth Filter ...... 7 Chebyshev Filter (Type 1) ...... 9 Chebyshev Filter (Type 2) ...... 11 Filter performance...... 13 Bibliography ...... 15
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Introduction
Noise-cancellation feature in headphones measure the external ambient noise with a microphone, and generate a signal that matches the noise, but with the opposite amplitude. This “anti-noise” (filter) is added to the original music signal and effectively interfere destructively with the ambient noise. This addition of anti-noise might also depend upon certain mathematical function which is known as filtering process. The motivation for the project came from a question paper of University of Colorado of ECE department. With that lead we will: Design a bandstop filter with the following specifications: Passbands: 0 – 1400 Hz and 1,900 – 5,512.5Hz Stopband: 1,600 - 1,700Hz Tolerance in the passband: 0.5 dB Maximum gain in the stopband: 100 dB. And will implement the filter using each of the following design methods: Butterworth Chebyshev Type I Chebyshev Type II
For a noisy signal(sound file) given here [1] The software tool used here is MATLAB provided by Mathworks[2].
The purpose of this assignment is to compare the above mentioned bandstop filters with the same cut-off frequencies, transition band, and ripple.
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The sound file consists of a song which we need and filter out rest of the other sounds which in this is heard at maximum decibels. The following graphs are that of noisy sound signal.
Frequency
Figure I: Graph (top) is x(t) versus time and bottom graph represents the fourier transform X(f) and f (frequency)
The x(t) graph seems to periodic at some point indicating the sound is repetitive. The second graph left part (beginning from x-axis = 6000) should not be considered as it is made just for numerical values by the software.
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Filters
In signal processing, a filter is a device or process that removes from a signal some unwanted component or feature[3]. Filtering is a class of signal processing, which involves the designing of filters in such a manner that they either do complete or partial suppression of some aspect of the signal. Filters can be classified in several different groups, depending on what criteria are used for classification. The two major types of digital filters are finite impulse response digital filters (FIR filters) and infinite impulse response digital filters (IIR). Some basic terminology: