Statistical significance of spectral peaks |
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Statistical significance of spectral peaks |
Aug 21 2012, 02:34
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#1
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Group: Members Posts: 6 Joined: 12-January 12 Member No.: 96382 |
Hello forum folks!
I have results of FFT for a number of signals, and I need to check the significance of a certain peak at a certain frequency in each of them. I am sorry for asking so bluntly, but how can this be done? I'm a total dummy to FFT, so I would really appreciate any simple and easy-to-follow directions Thank you all so much! Natalia |
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Aug 21 2012, 04:10
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#2
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Group: Members Posts: 4163 Joined: 2-September 02 Member No.: 3264 |
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Aug 21 2012, 07:28
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#3
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Group: Members Posts: 6 Joined: 12-January 12 Member No.: 96382 |
It means rejecting the null hypothesis, which is that the time series is simply white noise at the given frequency. In other words, proving that the peak at a given frequency is not by chance (noise) by due to periodicity.
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Aug 21 2012, 08:50
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#4
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![]() Group: Members Posts: 3221 Joined: 29-October 08 From: USA, 48236 Member No.: 61311 |
Hello forum folks! I have results of FFT for a number of signals, and I need to check the significance of a certain peak at a certain frequency in each of them. I am sorry for asking so bluntly, but how can this be done? I'm a total dummy to FFT, so I would really appreciate any simple and easy-to-follow directions Thank you all so much! You may find this reference helpful: Frequency response matching criteria from JAES The way that you use this chart is that you first characterize your peak or dip's bandwidth, in terms of a fraction of an octave and center frequency. Then you follow the line that is closest to the bandwidth to your center frequency. Then you see if your peak or dip's height or depth is greater or less than the bandwidth line at that frequency. If it is above the line then it is a sizable fraction of what it takes to be audible. |
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Aug 22 2012, 01:43
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#5
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Group: Members Posts: 6 Joined: 12-January 12 Member No.: 96382 |
Hello forum folks! I have results of FFT for a number of signals, and I need to check the significance of a certain peak at a certain frequency in each of them. I am sorry for asking so bluntly, but how can this be done? I'm a total dummy to FFT, so I would really appreciate any simple and easy-to-follow directions Thank you all so much! You may find this reference helpful: Frequency response matching criteria from JAES The way that you use this chart is that you first characterize your peak or dip's bandwidth, in terms of a fraction of an octave and center frequency. Then you follow the line that is closest to the bandwidth to your center frequency. Then you see if your peak or dip's height or depth is greater or less than the bandwidth line at that frequency. If it is above the line then it is a sizable fraction of what it takes to be audible. Thank you Arnold! But I need some statistical test to prove it, because I need to add this result to the paper. Here's the theory and guidelines as to how to do it in R package: http://stats.stackexchange.com/questions/1...pectral-density I was wondering if anyone knows any other solution. Thank you! |
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Lo-Fi Version | Time is now: 20th June 2013 - 13:41 |