Neuromorphic Engineering

References

• Neuromorphic Computing Wikipedia Article

Notes

Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. [...] Recent advances have even discovered ways to mimic the human nervous system through liquid solutions of chemical systems.

A key aspect of neuromorphic engineering is understanding how the morphology of individual neurons, circuits, applications, and overall architectures creates desirable computations, affects how information is represented, influences robustness to damage, incorporates learning and development, adapts to local change (plasticity), and facilitates evolutionary change.

Neuromorphic engineering is an interdisciplinary subject that takes inspiration from biology, physics, mathematics, computer science, and electronic engineers to design artificial neural systems.

Neuromorphic engineering is set apart by the inspiration it takes from what we know about the structure and operations of the brain. Neuromorphic engineering translates what we know about the brain's function into computer systems. The goal of biological processes of neurons and their synapses are dauntingly complex, and thus very difficult to artificially simulate.

The goal of neuromorphic computing is not to perfectly mimic the brain and all of its functions, but instead to extract what is known of its structure and operations to be used in practical computing system.

The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors, spintronic memories, threshold switches, transistors, among others.

• A memristor is a non-linear two-terminal electrical component relating electrical charge and magnetic flux linkage. It was described and named in 1971 by Leon Chua.