Biology has evolved highly optimised solutions that allows animals to sense their environment, make decisions based on the information from their sensors, and take actions important for survival of the organism. The central principle of neuromorphic engineering is to use their neural system as an inspiration for electronic sensing and decision making.
Some of the core principles identified for this biological processing are: distributed information processing, salience based time encoded processing, and the utilisation of noise and emergent network dynamics for improved performance. By focussing on specific applications, at ICNS, we build sensing systems that operate under similar constraints of functionality, efficiency, and performance as biological systems. This approach therefore aims to converge to the same solutions as those developed by evolution when pressed to match biological systems in real world applications.