We set up a dynamical fuzzy neural network system, i.e. the so-called max-min fuzzy HopΓΏeld network in the paper, and prove the Lyapunov stability of the equilibrium points (attractor) of the system. Also, we discuss the uniform stability of the system and show some su cient conditions, with which t
Identification and testing of an efficient hopfield neural network magnetostriction model
β Scribed by A.A. Adly; S.K. Abd-El-Hafiz
- Book ID
- 114226201
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 162 KB
- Volume
- 263
- Category
- Article
- ISSN
- 0304-8853
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract In the associate memory model based on the Hopfield neural network, the memorized pattern must satisfy a certain kind of orthogonal condition. However, in general, it is very difficult to satisfy this condition, which has been a great drawback in the application of the associative memor
The present paper demonstrates the suitability of artificial neural network (ANN) for modelling of a FinFET in nano-circuit simulation. The FinFET used in this work is designed using careful engineering of source-drain extension, which simultaneously improves maximum frequency of oscillation f max b
The focus of this study is how we can efficiently implement the neural network backpropagation algorithm on a network of computers (NOC) for concurrent execution. We assume a distributed system with heterogeneous computers and that the neural network is replicated on each computer. We propose an arc
## Abstract The application of DNA microarray technology for analysis of gene expression creates enormous opportunities to accelerate the pace in understanding living systems and identification of target genes and pathways for drug development and therapeutic intervention. Parallel monitoring of th