A Study on Brain Computing Interface

Brain computing, or neuromorphic computing, is a revolutionary field inspired by the human brain's parallel processing and energy efficiency. Unlike traditional computers that separate memory and processing, brain-inspired systems integrate these functions, enabling faster, more efficient data handling.The core of this technology is the use of artificial neural networks (ANNs) and specialized neuromorphic hardware. ANNs mimic the brain's structure, while hardware like spiking neural networks (SNNs) and memristors physically replicate the brain's synaptic behavior. These systems excel at tasks like pattern recognition and machine learning, where adaptability is key. However, the field faces significant challenges. Developing scalable hardware that matches the brain's complexity and creating effective software to train these systems are major hurdles. Additionally, we need a deeper understanding of the brain's own computational principles to unlock the full potential of this technology.Despite these challenges, brain computing is poised to transform various sectors, including artificial intelligence, robotics, and healthcare, by creating a new generation of cognitive systems that can learn and reason in a more human-like way.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-20
DOI
https://doi.org/10.1051/epjconf/202534101016/pdf
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

A Study on Brain Computing Interface

Springer Link (Chiba Institute of Technology)
Advanced Memory and Neural Computing
article

A Study on Brain Computing Interface

article en

Abstract

Brain computing, or neuromorphic computing, is a revolutionary field inspired by the human brain's parallel processing and energy efficiency. Unlike traditional computers that separate memory and processing, brain-inspired systems integrate these functions, enabling faster, more efficient data handling.The core of this technology is the use of artificial neural networks (ANNs) and specialized neuromorphic hardware. ANNs mimic the brain's structure, while hardware like spiking neural networks (SNNs) and memristors physically replicate the brain's synaptic behavior. These systems excel at tasks like pattern recognition and machine learning, where adaptability is key. However, the field faces significant challenges. Developing scalable hardware that matches the brain's complexity and creating effective software to train these systems are major hurdles. Additionally, we need a deeper understanding of the brain's own computational principles to unlock the full potential of this technology.Despite these challenges, brain computing is poised to transform various sectors, including artificial intelligence, robotics, and healthcare, by creating a new generation of cognitive systems that can learn and reason in a more human-like way.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 45%
Advanced Memory and Neural Computing
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