Neuromorphic engineering

Neuromorphic engineering or neuromorphic computing is a concept developed by Carver Mead, in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system. In recent times the term neuromorphic has been used to describe analog, digital, and mixed-mode analog/digital VLSI and software systems that implement models of neural systems (for perception, motor control, or sensory processing).

A key aspect of neuromorphic engineering is understanding how the morphology of individual neurons, circuits, and overall architectures create desirable computations, affect how information is represented, influences robustness to damage, incorporates learning and development, and facilitates evolutionary change.

Neuromorphic engineering is a new interdisciplinary discipline that takes inspiration from biology, physics, mathematics, computer science and engineering to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems.

An example of neuromorphic computer hardware is the Neurogrid board built by the Brains in Silicon group at Stanford University.

See also

	Computer science portal
	Electronics portal
	Neuroscience portal

• Analog computer
• Biomorphic
• Physical neural network
• Optical flow sensor
• Vision chip
• Computation and Neural Systems

External links

• Neuromorphic Engineering Workshop
• Institute of Neuromorphic Engineering
• INE news site.
• Center for Neuromorphic Systems Engineering at the California Institute of Technology.
• Computation and Neural Systems department at the California Institute of Technology.