ARTIFICIAL NEURAL NETWORK

Mohammad Ehteshamullah
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引用次数: 2

Abstract

Artificial Neural Networking or ANN is the way by which computers can mimic the biological nervous system by building a huge number of simulated neurons, which are joined together in a number of ways to form networks. A neural network has multiple processors instead of just one central processor and thus is very task efficient. They cannot be made to perform a specific task because they learn via experience, which is unlike any other computer processor. They follow certain learning laws while receiving feedback from the environment. This paper gives an overview of Artificial Neural Network, its working and training.
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人工神经网络
人工神经网络(Artificial Neural Networking,简称ANN)是计算机通过构建大量模拟神经元来模拟生物神经系统的一种方法,这些神经元以多种方式连接在一起形成网络。神经网络有多个处理器,而不是只有一个中央处理器,因此任务效率很高。它们不能执行特定的任务,因为它们通过经验学习,这与任何其他计算机处理器不同。它们在接受环境反馈的同时遵循一定的学习规律。本文概述了人工神经网络及其工作原理和训练方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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