Levenberg-Marquardt方法在脉冲神经网络训练中的应用

2005 International Conference on Neural Networks and Brain Pub Date : 2006-10-30 DOI:10.1109/IJCNN.2006.246919

Sergio Silva, A. Ruano

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引用次数: 19

摘要

一些神经网络的一个基本方面是它们试图尽可能地近似它们的生物对应物。目标是实现一个简单而强大的网络，易于理解，能够在计算水平上模拟人类大脑。本文通过引入一种新的编码方案，对Spikepro算法进行了改进，并举例说明了Levenberg Marquardt算法在第三代神经网络中的应用

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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Application of Levenberg-Marquardt method to the training of spiking neural networks

One of the basic aspects of some neural networks is their attempt to approximate as much as possible their biological counterparts. The goal is to achieve a simple and robust network, easy to comprehend and capable of simulating the human brain at a computational level. This paper presents improvements to the Spikepro algorithm, by introducing a new encoding scheme, and illustrate the application of the Levenberg Marquardt algorithm to this third generation of neural network

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2005 International Conference on Neural Networks and Brain

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