[skinney_uce]

The behaviors that emerge — hysteresis, oscillation, bistable memory — are the same computational primitives you see in biological neural circuits, but they come from constraint satisfaction over conserved quantities instead of simulating neurons. The architecture doesn't model neurons at all. It produces the same outputs through a different mechanism. Whether that still counts as "neuromorphic" is debatable — I use the term because the output behaviors map directly to the same hardware substrates (Loihi, SpiNNaker, etc).

[rramadass]

Can you recommend some good books/papers/articles/videos to better understand Neuromorphic Computing and its Applications?

[skinney_uce]

Carver Mead's "Analog VLSI and Neural Systems" for where neuromorphic computing started. Intel's Loihi papers (Mike Davies et al.) for where it is now. Our paper takes a different path — constraints instead of neurons.

[rramadass]

Thank You. I see those (and more) at the wikipedia entry for NC.

Any books you can recommend? I see a bunch on Amazon but not sure which are the good technical ones. Something with more information about the various hardware approaches (eg. non-ISA/hybrid/etc.) would be welcome.

[skinney_uce]

Event-Based Neuromorphic Systems" (Liu, Delbrück, Indiveri, Whatley, Douglas — Wiley 2014). For current silicon, read the Loihi 2, TrueNorth, and SpiNNaker 2 primary papers directly — books can't keep up with where the hardware is actually moving.

[rramadass]

Thank You.