Application of neural network models.
作者信息
Germer H A
出版信息
Biophys J. 1971 Nov;11(11):966-9. doi: 10.1016/S0006-3495(71)86268-9.
Abstract
摘要
相似文献
1
Application of neural network models.神经网络模型的应用。
Biophys J. 1971 Nov;11(11):966-9. doi: 10.1016/S0006-3495(71)86268-9.
2
A hybrid neural network of addressable and content-addressable memory.一种可寻址和内容可寻址存储器的混合神经网络。
Int J Neural Syst. 2003 Jun;13(3):205-13. doi: 10.1142/S0129065703001546.
3
Entropy learning and relevance criteria for neural network pruning.神经网络剪枝的熵学习与相关性准则
Int J Neural Syst. 2003 Oct;13(5):291-305. doi: 10.1142/S0129065703001637.
4
[Physical models of neural networks].[神经网络的物理模型]
Biofizika. 1987 Sep-Oct;32(5):918-28.
5
Complementary learning systems.互补学习系统
Cogn Sci. 2014 Aug;38(6):1229-48. doi: 10.1111/j.1551-6709.2011.01214.x. Epub 2011 Dec 5.
6
On building a memory evolutive system for application to learning and cognition modeling.关于构建用于学习和认知建模的可进化记忆系统。
Adv Exp Med Biol. 2010;657:19-39. doi: 10.1007/978-0-387-79100-5_2.
7
Sparse neural networks with large learning diversity.具有大学习多样性的稀疏神经网络。
IEEE Trans Neural Netw. 2011 Jul;22(7):1087-96. doi: 10.1109/TNN.2011.2146789. Epub 2011 Jun 7.
8
An autoassociative neural network model of paired-associate learning.配对联想学习的自联想神经网络模型。
Neural Comput. 2001 Sep;13(9):2075-92. doi: 10.1162/089976601750399317.
9
Predicting spontaneous recovery of memory.
Nature. 2001 Nov 8;414(6860):167-8. doi: 10.1038/35102676.
10
Computational models of the neural bases of learning and memory.学习与记忆神经基础的计算模型
Annu Rev Neurosci. 1993;16:667-706. doi: 10.1146/annurev.ne.16.030193.003315.
本文引用的文献
1
Association by synaptic facilitation in highly damped neural nets.高阻尼神经网络中通过突触易化实现的关联
Biophys J. 1967 Nov;7(6):689-717. doi: 10.1016/S0006-3495(67)86617-7. Epub 2008 Dec 31.
2
The biochemical basis of long-term memory.长期记忆的生化基础。
Q Rev Biophys. 1969 May;2(2):135-73. doi: 10.1017/s0033583500000937.
Zotero 插件