感知器
人工神经网络
计算机科学
人工智能
领域(数学)
多层感知器
钥匙(锁)
财产(哲学)
机器学习
图层(电子)
数学
哲学
化学
计算机安全
有机化学
认识论
纯数学
作者
Jaswinder Singh,Rajdeep Hazra Banerjee
标识
DOI:10.1109/iccmc.2019.8819775
摘要
Perceptron is the most basic model among the various artificial neural nets, has historically impacted and initiated the research in the field of artificial nets, with intrinsic learning algorithm and classification property. It has boosted the world of neural networks and profoundly impacted the numerous advancements. From the very beginning it has proved to be the key to the way machines perceive, making them artificially intelligent through extensive training processes. In this study, the ideology of perceptron learning, its concepts, working, applications and a very brief introduction to multilayer perceptron has been discussed.
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