INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Survey Of Neuromorphic Computing and Neural Networks in Hardware
Authors Name:
Reshma Roy
, Dr. Rahul Shajan
Unique Id:
IJSDR2303254
Published In:
Volume 8 Issue 3, March-2023
Abstract:
Abstract: A biologically inspired method of computing known as "neuromorphic computing" promises to give computers the capacity to learn and adapt in a manner similar to the human brain. With the help of highly connected synthetic neurons and synapses, this technology has the ability to solve difficult machine learning issues and model neuroscientific theories. These systems were developed to address the limitations of traditional von Neumann computers, which rely on sequential processing and are inappropriate for tasks requiring parallelism, low power consumption, and real-time computing. In recent years, the field has made great progress with the emergence of various hardware platforms that use spiking neural networks (SNNs) to perform complex computations. The goal of the field of neuromorphic computing is to create machines that function similarly to the human brain.
Keywords:
Index Terms: Neuromorphic computing, machine learning, neurons, human brain, spiking neural networks, materials science (key words)
Cite Article:
"Survey Of Neuromorphic Computing and Neural Networks in Hardware", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1462 - 1465, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303254.pdf
Downloads:
000337355
Publication Details:
Published Paper ID: IJSDR2303254
Registration ID:204982
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 1462 - 1465
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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