Course Content
Course outline: Introduction to Neuromorphic Engineering; Signalling and operation of Biological neurons, neuron models, signal encoding and statistics; Synapses and plasticity rules, biological neural circuits; Neuromorphic design principles; FETs - device physics and sub-threshold circuits; Analog and digital electronic neuron design; Non-volatile memristive semiconductor devices; Electronic synapse design; Interconnection Networks; Interconnection schemes for large non-spiking and spiking neural networks; Analysis of design, architecture and performance characteristics of demonstrated chips employing Analog neuromorphic VLSI, Digital neuromorphic VLSI, Electronic synapses and other neuromorphic systems.
Text / References
- 1 Shih-Chii Liu, J303266rg Kramer, Giacomo Indiveri, Tobias Delbr303274ck, Rodney Douglas, Analog VLSI: circuits and principles, MIT press, 2002 ISBN 02621225532.Carver Mead, Analog VLSI and neural systems, Addison-Wesley, 1989, ISBN01102010599243.Eric Kandel, James Schwartz, Thomas Jessell, Steven Siegelbaum, A.J. Hudspeth, Principles of neural science, , McGraw Hill 2, ISBN 0071390111 4.Dale Purves, Neuroscience, Sinauer, 2008, ISBN 0878936971