Difficulty detecting peak points in PSD graph using derivative method
I’m working on a signal processing task where I need to detect peak points in a Power Spectral Density (PSD) graph within specific frequency ranges (Freqs[0] to Freqs[2]). I’m using Python and calculating the derivative to find where the slope changes from positive to negative, which I expect to correspond to peaks. However, my code doesn’t seem to reliably catch the peaks, especially within the regions where I’ve plotted red, green, and blue lines on the graph. It is okay the peak is in range of +- 0.2Hz in Freqs[0] to Freqs[2]
detecting and quantifying periodicity in a data set
I have a dataset that looks like this
Python Algorithm to Extract “Real Test” Samples from Array of Mixed Data Types Based on Value Patterns
I’m working with an array of current samples collected from some hardware. The array contains a mix of different types of data: “readiness”, “real test”, and “stop” phases. I need to develop an algorithm to identify and extract only the “real test” samples from this array.