Analog methods generally are more favorable when you're doing edge processing on analog sensor data, and can avoid data conversion overheads. But you still have to contend with mismatch and temperature variation!
I think that hybrid methods that leverage some analog and some digital processing will probably win out at the edge.
one of my professors who works on neuromorphic computing says that the only place where it will make
sense is when you’re processing analog signals - edge computing for neural acquisition systems for example. thoughts?
Analog methods generally are more favorable when you're doing edge processing on analog sensor data, and can avoid data conversion overheads. But you still have to contend with mismatch and temperature variation!
I think that hybrid methods that leverage some analog and some digital processing will probably win out at the edge.