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Hardware implementations of spiking neural networks for real-time behaving cognitive systems - Giacomo Indiveri
Speaker:
Giacomo Indiveri
This tutorial will cover the design of large-scale networks of spiking
neurons in VLSI technology, for real-time behaving systems.
It will begin with an introduction to motivate the approaches followed,
a description of potential applications and a comprehensive overview of
the state-of-the-art in the field, including the presentation of
standard models for spiking neural networks. We will provide basic
notions on sub-threshold and above threshold MOSFET operation and
analogies between the biophysics of biological neurons and the physics
of transistor channels, and summarize the characteristics of basic MOS
circuits, crucial for implementing spiking neural networks.
We will describe spike-based learning circuits and show how to build
large-scale multi-chip systems, that can carry out sensory processing in
real-time and provide fast control/motor outputs to robotic actuators.
