面向智能应用的分布式神经网络的adn分析与开发

J. Arcand, Sophie-Julie Pelletier
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引用次数: 3

摘要

本文首先解释分布式神经网络的概念。然后,它继续提出一个程序库,旨在支持这种网络的发展。在这种情况下,分布式神经网络被视为由许多可以相互通信的子网络组成的超级网络。这种超级网络旨在促进复杂和异构现实的建模。根据学习算法或控制它的算法,每个子网都独立于其他子网进行训练。一旦训练完毕,子网络就以这样一种方式相互连接,以便在整个网络中传播信息。分布式网络图书馆是这一领域研究的一个应用。它允许创建分布式网络、单独训练子网以及子网之间的通信。这个库的接口使它既是一个研究工具,也是一个为外行开发神经网络的程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ADN-analysis and development of distributed neural networks for intelligent applications
This article begins by explaining the concept of distributed neural networks. It then goes on to present a program library designed to support the development of such networks. In this context, distributed neural networks are seen as supernetworks comprising a number of subnetworks that can communicate with one another. Such supernetworks are intended to facilitate the modeling of complex and heterogeneous realities. Each subnetwork is trained independently of the others, according to the learning algorithm or algorithms that govern it. Once trained, the subnetworks are interconnected in such a way as to circulate information through the network as a whole. The distributed network library is an application of research in this area. It allows for the creation of distributed networks, the individual training of subnetworks, and communication between subnetworks. The library's interface makes it as much a tool for research as it is a program for neural network development for the uninitiated.<>
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