2012Tikrit Journal of Engineering SciencesOpen access

Studying The Effect of Window Type on Power Spectrum Based on Mat Lab

Soad T. Abed, Zena. E. Dallalbashi, Faten. A. Taha

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Abstract

The representation that describes signal’s frequency behavior can be divided into two categories: linear representation such as the Fourier-transform and quadratic representation such as power spectrum. Power spectrum characterizes the signal’s energy distribution in the frequency domain, and can answer whether most of the power of the signal resides at low or high frequencies. By performing spectral analysis, some important features of signals can be discovered that are not obvious in the time waveform of the signal. One problem with spectrum analysis is that the duration of the signals is finite, although adjustable. Applying the FFT method to finite duration sequences can produce inadequate results because of “spectral leakage”, to reduce the spectral leakage FFT window function is applied. Power spectrum parameters are window size, window type, window over lap and number of FFT. The aim of this work is to demonstrate the effect of varying window type on the power spectrum using Mat Lab software. Five windows have been compared to study their effect on the spectrum of a typical data.

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The representation that describes signal’s frequency behavior can be divided into two categories: linear representation such as the Fourier-transform and quadratic representation such as power spectrum. Power spectrum characterizes the signal’s energy distribution in the frequency domain, and can answer whether most of the power of the signal resides at low or high frequencies. By performing spectral analysis, some important features of signals can be discovered that are not obvious in the time waveform of the signal. One problem with spectrum analysis is that the duration of the signals is finite, although adjustable. Applying the FFT method to finite duration sequences can produce inadequate results because of “spectral leakage”, to reduce the spectral leakage FFT window function is applied. Power spectrum parameters are window size, window type, window over lap and number of FFT. The aim of this work is to demonstrate the effect of varying window type on the power spectrum using Mat Lab software. Five windows have been compared to study their effect on the spectrum of a typical data.

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Available abstract

The representation that describes signal’s frequency behavior can be divided into two categories: linear representation such as the Fourier-transform and quadratic representation such as power spectrum. Power spectrum characterizes the signal’s energy distribution in the frequency domain, and can answer whether most of the power of the signal resides at low or high frequencies. By performing spectral analysis, some important features of signals can be discovered that are not obvious in the time waveform of the signal. One problem with spectrum analysis is that the duration of the signals is finite, although adjustable. Applying the FFT method to finite duration sequences can produce inadequate results because of “spectral leakage”, to reduce the spectral leakage FFT window function is applied. Power spectrum parameters are window size, window type, window over lap and number of FFT. The aim of this work is to demonstrate the effect of varying window type on the power spectrum using Mat Lab software. Five windows have been compared to study their effect on the spectrum of a typical data.

Key concepts: Fast Fourier transform, Window function, Spectral density, Spectral leakage, Frequency domain, Window (computing), Waveform, Mathematics

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