Power spectrum of short signals

In summary, the conversation discusses the issue of accurately calculating the power spectrum of short signals with variable durations between 200 and 500 ms. The suggestion is to use Matlab and FFT, but the effectiveness of this method is questioned for short segments. Further insights and an understanding of the relationship between segment length and signal bandwidth are needed for improved results.
  • #1
tct212
2
0
I am looking for a way to calculate the power spectrum of short signals of variable duration (between 200 and 500 ms). Standard methods seem wildly inaccurate. Are there any tricks for short segments?

Thanks anyone for a response.
 
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  • #2
If you have access to Matlab, you should be able to take the FFt of the signal, square it and get your power spectrum. Do a google search for Power Spectrum and Matlab and you'll get a load of hits.
 
  • #3
For short signals?

Thank you Dr Transport. Yes I do have access to Matlab and FFT works great for segments longer than 500 ms. When the segments are short, fft does a very bad job. I am looking for some improved algorithm that may be better optimized for short segments. Any insights would be appreciated.
 
  • #4
The length of the segment in ms does not matter. What matters is the length of the segment relative to the longest period of the signal of interest (i.e. the bandwidth of the signal).
You need at sample at least one entirely cycle of each frequency component you are trying to extract in order to get sensible results; my guess would be that you are hitting that "limit" when you go below 500 ms.
 

1. What is a power spectrum?

A power spectrum refers to the distribution of power or energy in a signal across different frequencies. It is a way to analyze and visualize the frequency components of a signal.

2. How is the power spectrum of a short signal different from a long signal?

The power spectrum of a short signal is typically more concentrated and has fewer frequency components compared to a long signal. This is because a short signal has a shorter duration, thus it contains a smaller range of frequencies.

3. How is the power spectrum calculated?

The power spectrum is calculated using a mathematical tool called the Fourier transform. This transforms a time-domain signal into its frequency components, allowing for the calculation of the power at each frequency.

4. What information can be obtained from the power spectrum of a short signal?

The power spectrum of a short signal can provide insight into the dominant frequencies and their corresponding power levels in the signal. This information can be useful in analyzing and understanding the characteristics of the short signal.

5. Can the power spectrum of a short signal be used for feature extraction?

Yes, the power spectrum of a short signal can be used for feature extraction in signal processing and analysis. It can help identify key frequency components that can be used to differentiate between different types of signals or to detect abnormalities in a signal.

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