Wavelets are wavelike functions used to transform signals into a representation which has time and frequency domain components. Visually wavelets appear as wave-like oscillations with an amplitude that starts at zero, increases, then returns to zero. Another way to consider a wavelet is as a bandpass filter, which can be applied to a time series under investigation, letting through only components of the time series within a finite range of frequencies to different extents depending on the energy spectrum of the wavelet. Wavelets take the form:
Long term relationships also strengthen, to some extent, around areas indicated as bubbles. The previously observed long term relationship between Google Trends and Bitcoin price [8] can also be seen here, between late 2012 and 2014 (period band 64–256). With the benefit of extra data it can be observed that the relationship disappears around 2014 (for lower period bands) and 2015 (for higher period bands), before the relationships start occurring more consistently in 2016 and 2017 (a region with a number of bubbles identified). The previously observed relationship between Wikipedia views and Bitcoin observed in 2013 (64–128 band), disappears before again returning in mid-2016 and 2017.

Meanwhile, even the most enthusiastic bitcoin evangelists are realizing that a retooling is in order. Michael J. Casey, a senior adviser for blockchain research at MIT’s Digital Currency Initiative, recently wrote about how the crypto-winter has arrived, but it may lead to better things down the line:
Cook didn't specify which coin he owns, like bitcoin or ethereum, but he said Tuesday that the space is something he's been interested in for a while.