Extracting time series features: a powerful method from a obscure paper [pdf]

Often it seems that old papers are the most insightful. Back then, the research cycle was shorter and scientists had more institutional support. They had more time to think.

This paper has always amazed me. It's an incredibly creative means to getting the characteristics of a recurring shape from a noisy time series signal. It's sort of like what wavelet analysis does. It's remarkably effective.

The author skips a lot of steps in his work in the paper. Here is a link to a stepwise derivation of the method.

https://drive.google.com/file/d/1ytbqe-zL9j7hddm4TTU3egXdnm7...

These ramp functions are actual quite powerful and beautiful sounding when implemented in analog electronic synthesizers - by controlling the ratio of the quiescent and moving phase, and by controlling the ratio of the rise and fall times in the moving phase, you can achieve all sorts of very beautiful, rich timbral modulations with interesting harmonic behavior - particularly if your pulse generator and the envelope duration are decoupled in terms of durations. Wind, brass, reedy sounds are all possible, some cool undertones can be created, etc etc.

https://github.com/whimsicalraps/Mannequins-Technical-Maps/b...

Can anyone summarize the novelty here (for general time series)? Have these features been referenced recently?