A Review On: Neuromorphic Computing
Abstract
New approaches new algorithms helps to form a good bond between the human brain and with the world. Artificial Intelligence mainly depends upon data analysis, as we know still our modern science computers are inefficient in fulfilling the three task analyzing, classifying and recognizing the information. Neuromorphic computing is a new way to cover this gap by emulating certain aspects of brain function. The structure of brain is a combination of both computation and memory emulating neurons and synapses has the potential to achieve all requirements of next generation.
This new technology uses algorithms to support real-time learning with structure built on novel computing hardware to access specific user application. The main promise of this technology is to create a brain that has ability to learn and adapt in any atmosphere like human brain do. Neuromorphic structure is a combination of heteromorphic structure which shows the connection of chip and wires in the form of logic gates like our brain have neurons so the involvement of this structure give rise of neuromorphic structure .
Mainly the neuromorphic computing focus on matching a human brain flexibility, efficiency and ability to learn and grab the things from physical environment with the energy efficiency of human brain. The computational building blocks within neuromorphic computing system are logically analogous to neurons. Spiking neural networks (SNNs) are a model for arranging those elements to emulate natural networks that exists in biological brains. The first generation of AI was rules base and emulated conventional judgment to draw reasoned wrapping up within a specific closely defined domain. It was well suited for monitor procedure and increase the competence and the second generation is principally focus on sensing and perception such as deep learning network to appraise the content of video frame. So principally we achieve that neuromorphic computing is helpful in making machine that is as much as competent like human brain. They are as early payment as human brain in all aspects.
How to cite this article:
Sharma AK, Rathore M, Kishore I et al. A Review on: Neuromorphic Computing. J Adv Res Embed Sys 2020; 7(2):11-13.
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