tensorflow backend

Suggestion from Tim Blakely (Google):

"Depending on the use case, calculating the channels on the fly may be practical (and likely much cheaper). Along those lines, if most/all of the calculations can be expressed as a series of matrix operations, it might be worth some engineering effort to see if the calculations could be ported to [TensorFlow](https://www.tensorflow.org/). It's the machine learning toolkit we use internally at Google, and while it's mainly used for deep learning and analysis it's actually a generalized platform for doing arbitrary tensor computations (e.g. n-d matrix operations). The reason it might be interesting for your project is that TensorFlow works on both CPUs and GPUs. The latter is particularly useful since 1) it can perform streaming matrix multiplications orders of magnitude faster than CPUs, 2) you can get [GCE instances with GPUs in them](https://cloudplatform.googleblog.com/2017/02/GPUs-are-now-available-for-Google-Compute-Engine-and-Cloud-Machine-Learning.html) today, and 3) it may allow for much-closer-to-real-time calculation of SuperEEG channels. Only a suggestion, however; it's by no means a requirement for the project."