Multistability and complete convergence analysis on high-order neural networks with a class of nonsmooth activation functions-Reference-Cited by-同舟云学术

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Multistability and complete convergence analysis on high-order neural networks with a class of nonsmooth activation functions

Published:2015-03 Issue: Volume:152 Page:222-230
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Wang Lili,Chen Tianping

Funder

National Natural Sciences Foundation of China

Innovation Program of Shanghai Municipal Education Commission

Shanghai Young College Teachers Program

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference27 articles.

1. Structural properties of gradient recurrent high-order neural networks;Kosmatopoulos;IEEE Trans. Circuits Syst. II,1995

2. Learning, invariance, and generalization in high-order neural networks;Giles;Appl. Opt.,1987

3. High-order absolutely stable neural networks;Dembo;IEEE Trans. Circuits Syst.,1991

4. Global properties for a class of dynamical neural circuits;Fang;J. Frank. Inst.,1998

5. Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit;Hahnloser;Nature,2000

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