Neuromorphic Control: Designing Multiscale Mixed-Feedback Systems
Luka Ribar, Rodolphe Sepulchre
Abstract
Neuromorphic electronic engineering takes inspiration from the biological organization of nervous systems to rethink the technology of computing, sensing, and actuating (see “Summary”). It started three decades ago with the realization by Carver Mead, a pioneer of very large-scale integration (VLSI) technology, that the operation of a conventional transistor in the analog regime closely resembles the biophysical operation of a neuron <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> . Mead envisioned a novel generation of electronic circuits that would operate far more efficiently than conventional VLSI technology and would allow for a new generation of biologically inspired sensing devices. Three decades later, active vision has become a technological reality <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> , and neuromorphic computing has emerged as a promising avenue to reduce the energy requirements of digital computers <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> – <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"/> <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"/> <xref ref-type="bibr" rid="ref7" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[7]</xref> . These two applications could just be the tip of the iceberg. Neuromorphic circuit architectures call for new computing, signal processing, and control paradigms.