Analytical Signal Processing Tutorial Using Savitzky-Golay from Python Scipy

In this informative video tutorial, I will be explaining how to use Scipy, a popular Python library, to enhance signals using the signal processing Savitzky-Golay method. The Savitzky-Golay filter is a powerful tool that can help smooth out noisy signals, improve the signal-to-noise ratio, and extract relevant features from the data.
Throughout the video, I will provide a step-by-step guide on how to use Scipy to implement the Savitzky-Golay filter, including how to select the appropriate parameters and visualize the results. I will also discuss some common use cases and best practices for using this method in signal processing applications.
By the end of the video, you will have a solid understanding of how to use Scipy and the Savitzky-Golay filter to improve the quality of your signals and extract meaningful insights from your data. Whether you are a seasoned engineer or just starting out in signal processing, this video will provide you with practical tools and techniques to help you achieve your goals.
Github: github.com/chr...
peak_picking: • 2 Methods to Find Peak...
baseline correction: • How to Baseline Correc...
Signal Filtering: • Analytical Signal Proc...

[@yangguo1512]

I was trying to plot some UV-vis spectrum that had noise in it and your video was very helpful for me❤

[@CJP3]

It doesn’t get much better than that!! Thank you for sharing!! 🙏🏽

[@BarbaraAboagye]

Great video Christopher. This was really helpful. How did you draw on the screen? Did you just add it during editing? Your voice is also soothing and I love the pace you speak

[@CJP3]

Hi Barbara thanks for the kind words! I drew on the screen using my iPad and combined during editing. I recorded My iPad using OBS so it would all be Synced. I hope this helps!

[@theuselessworker3485]

love ur video. Thx man

[@CJP3]

Thank you very much!

[@kahnzo]

Thank you. Your videos are always so interesting. I'm wondering if it might be helpful to run some real world data sets and perhaps differentiate some use cases. Thank you for your very clear videos. They are appreciated.

[@CJP3]

Hi Aaron! Thanks for kind words! And yes.. I actually have two videos (Saturday and next Tuesday) on processing real mass spectrometry data for peak picking and baseline correction. I’ll continue to do even more in the near future!!

[@sparshasherke250]

To the point. Thanks!

[@CJP3]

Thanks for watching Sparsha! I hope the videos are valuable :)

[@monaallam130]

Hi Christopher , thank you for this video, I need your email pls, i have some issues in my data, thank you

[@CJP3]

Interesting, what kind of data?