DocumentCode
328917
Title
Weighting function in neural network
Author
Zhang, Yongjun ; Chen, Zongahi
Author_Institution
Inst. of Electron., Acad. Sinica, Beijing, China
Volume
2
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
1454
Abstract
The recurrent correlation neural networks have high-capacity associative memory when the weighting function satisfies certain condition. But this always causes the high dynamics in the neural network and the hardware realization is difficult. This paper gives the relationship between the capacity and dynamics and provides a general principle for the choice of the weighting function and give a kind of weighting function. It has high-capacity and avoids the high dynamics. Finally, the simulated results are given.
Keywords
content-addressable storage; correlation theory; recurrent neural nets; high-capacity associative memory; recurrent correlation neural networks; weighting function; Biological neural networks; Equations; Identity-based encryption; Intelligent networks; Neural network hardware; Neural networks; Neurons; Recurrent neural networks; State estimation; Tellurium;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.716819
Filename
716819
Link To Document