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Maybe better to do your first (beginner) signal processing on a conventional computer. Use Matlab, C, or whatever. That allows you to get right to the heart of whether your "algorithm" works before having to deal with mcu/fpga tooling.
I do hope all those AI (well mostly CNN) chips being developed by many bigger players will come to the masses soon. That will be fun in.
Quote from: BBBbbb on April 23, 2018, 07:44:22 pmI do hope all those AI (well mostly CNN) chips being developed by many bigger players will come to the masses soon. That will be fun in.The beauty of NN is that once trained they require very little juice. The difficulty of NN is training so let's see what that would take:Bath the sensors in room, turn off the fuse box and all the machines, tell the NN this is ambient noise and sit there for a days to handle night and day time ambient people activity. Then come back in, turn on the fuse box and tell the NN this is the fuse box with ambient noise, let it iterate for a while. Same for motor #1, motor #2, both motors. continue with all the permutations and then take off the training wheel and let the NN figure out what's on. There's got to be a better way that doesn't require baby sitting or sensing the EM field in some faraday cage.
Still, NN hardware for you https://www.amazon.com/Intel-NCSM2450-DK1-Movidius-Neural-Compute/dp/B076751BN8/ref=sr_1_2?ie=UTF8&qid=1524645314&sr=8-2&keywords=Intel%C2%AE+Movidius%E2%84%A2+Neural+Compute+StickHow do I approch parametric? Or SVM with code? I see these graphs and lines and then formulas and my mind good *poof*