Help on estimation the gradient of a sigal sequence

AI Thread Summary
To estimate the gradient of a decreasing time series signal affected by noise, a least-squares curve fitting approach is recommended, which can be easily executed in Excel. Additionally, characterizing the noise spectrum and applying a digital filter can enhance the signal-to-noise ratio, leading to a more accurate gradient estimation. Resources like "Designing Digital Filters" by Williams can provide valuable insights into digital signal processing techniques. These methods will help in obtaining a clearer understanding of the average reduction in the measured quantity. Effective noise management is crucial for accurate gradient estimation in fluctuating signals.
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Dear All,

I have a signal, which is a time series from measuring some quantity. The trend of the signal is decreasing. However, due to noise, the signal is fluctuating. Is there some method to get a good estimation of the gradient of the signal, i.e. the average reduction of the quantity? Thanks a lot!

Maria
 
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The easiest would be to do a least-squares fit of a curve to the data. You can even do that in Excel -- just use the online Help function in Excel to guide you through the process.

Another way would be to characterize the spectrum of the noise versus the signal, and do a digital filter of the data to improve your signal-to-noise ratio. "Designing Digital Filters" by Williams is an excellent introductory book to DSP.
 

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