Help on estimation the gradient of a sigal sequence

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SUMMARY

The discussion focuses on estimating the gradient of a decreasing signal affected by noise. Maria suggests using a least-squares fit for curve fitting, which can be performed in Excel. Additionally, she recommends characterizing the noise spectrum and applying digital filtering techniques to enhance the signal-to-noise ratio. The book "Designing Digital Filters" by Williams is highlighted as a valuable resource for understanding digital signal processing (DSP).

PREREQUISITES
  • Understanding of least-squares fitting techniques
  • Familiarity with Excel for data analysis
  • Basic knowledge of digital signal processing (DSP)
  • Concept of signal-to-noise ratio (SNR)
NEXT STEPS
  • Research least-squares fitting methods in Excel
  • Explore digital filtering techniques in DSP
  • Read "Designing Digital Filters" by Williams
  • Learn about characterizing noise spectra in time series data
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Data analysts, signal processing engineers, and anyone involved in time series analysis and noise reduction techniques.

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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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