Hidden-layer redundancy method of RBF neural networks

被引：0

作者：

Xu, Li-Qin ^{[1
]}

Hu, Dong-Cheng ^{[1
]}

机构：

[1] Dept. of Automat., Tsinghua Univ., Beijing 100084, China

来源：

Kongzhi yu Juece/Control and Decision | 2001年 / 16卷 / 05期

关键词：

Algorithms - Architecture - Computer simulation - Fault tolerant computer systems - Fault tree analysis - Redundancy - Theorem proving;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

A hidden-layer neuron redundancy architecture of RBF network is presented. Performance of the network are analyzed under both single-fault and universal faults. The performance of the network under faults can be improved significantly with this redundancy architecture. Finally, a practical method of redundancy of hidden-layer neurons to gain fault tolerance is presented. Simulation results show the validity of the method.

引用

页码：591 / 594

共 50 条

[41] Investigation of Four-Layer Multi-Layer Perceptron with Glia Connections of Hidden-Layer Neurons
Ikuta, Chihiro
Uwate, Yoko
Nishio, Yoshifumi
2013 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2013,
[42] Physical layer redundancy method for fault-tolerant networks
Lee, JM
Kwon, WH
Kim, YS
Moon, HJ
2000 IEEE INTERNATIONAL WORKSHOP ON FACTORY COMMUNICATION SYSTEMS, PROCEEDINGS, 2000, : 157 - 163
[43] Multiscale Hierarchical Losses to Preserve Hidden-Layer Features for Unsupervised Change Detection
Bergamasco, Luca
Bovolo, Francesca
Bruzzone, Lorenzo
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62
[44] Use of postcritical reflections in solving the hidden-layer problem of seismic refraction work
Sain, K
Reddy, PR
GEOPHYSICS, 1997, 62 (04) : 1285 - 1291
[45] DEGREE OF APPROXIMATION BY NEURAL AND TRANSLATION NETWORKS WITH A SINGLE HIDDEN LAYER
MHASKAR, HN
MICCHELLI, CA
ADVANCES IN APPLIED MATHEMATICS, 1995, 16 (02) : 151 - 183
[46] Simplicity Bias in 1-Hidden Layer Neural Networks
Morwani, Depen
Batra, Jatin
Jain, Prateek
Netrapalli, Praneeth
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023), 2023,
[47] A sequential learning approach for single hidden layer neural networks
Zhang, J
Morris, AJ
NEURAL NETWORKS, 1998, 11 (01) : 65 - 80
[48] Wide Hidden Expansion Layer for Deep Convolutional Neural Networks
Wang, Min
Liu, Baoyuan
Foroosh, Hassan
2020 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), 2020, : 923 - 931
[49] APPROXIMATION BY RIDGE FUNCTIONS AND NEURAL NETWORKS WITH ONE HIDDEN LAYER
CHUI, CK
LI, X
JOURNAL OF APPROXIMATION THEORY, 1992, 70 (02) : 131 - 141
[50] Training neural networks by marginalizing out hidden layer noise
Yanjun Li
Ping Guo
Neural Computing and Applications, 2018, 29 : 401 - 412

← 1 2 3 4 5 →