LITE-SNN: Leveraging Inherent Dynamics to Train Energy-Efficient Spiking Neural Networks for Sequential Learning

IF 5 3区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Cognitive and Developmental Systems Pub Date : 2024-05-03 DOI:10.1109/tcds.2024.3396431

Nitin Rathi, Kaushik Roy

引用次数: 0

查看原文本刊更多论文

LITE-SNN：利用固有动态性训练高能效尖峰神经网络以进行序列学习

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Cognitive and Developmental Systems Computer Science-Software

CiteScore

7.20

自引率

10.00%

发文量

170

期刊介绍： The IEEE Transactions on Cognitive and Developmental Systems (TCDS) focuses on advances in the study of development and cognition in natural (humans, animals) and artificial (robots, agents) systems. It welcomes contributions from multiple related disciplines including cognitive systems, cognitive robotics, developmental and epigenetic robotics, autonomous and evolutionary robotics, social structures, multi-agent and artificial life systems, computational neuroscience, and developmental psychology. Articles on theoretical, computational, application-oriented, and experimental studies as well as reviews in these areas are considered.