Paper Contents
Abstract
Neuromorphic computing is a way of designing computers that takes inspiration from how our brains work. This method mimics the brain's structure and processes by using artificial neurons and synapses. Unlike traditional computers, which operate in a more rigid manner, neuromorphic systems process information in a way that feels more like human thinking. This approach is exciting because it could lead to computers that can learn and adapt in a brain-like way, which would be amazing for solving complex problems and understanding how our brains work. However, there are huge challenges. We need to figure out how the brain actually works, find new materials and ways to build these brain-like devices, create software that allows them to learn, and then build applications that can use these brain-like abilities. This paper provides a complete overview of neuromorphic computing, looking back at 35 years of research. We'll explore the different areas of research, including the brain-inspired models, the algorithms and learning methods, the hardware and devices, the supporting systems, and the applications. Finally, we'll talk about what needs to be done in the future to make neuromorphic computing a reality. The main goals are to give a thorough look at all the research that's been done in this field and to point out where more research is needed. Essentially, we want to see where we are and what we need to do to build these brain-like computers.
Copyright
Copyright © 2025 Prashansa BHurbhure. This is an open access article distributed under the Creative Commons Attribution License.
