in this paper, linear matrix inequality (lmi) approach for synchronization of chaotic fuzzy cellular neural networks (fcnns) with discrete and unbounded distributed delays based on sampled-data controlis investigated. lyapunov-krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of...

We show how eld-programable gate arrays can be used to eeciently implement neural nets. By implementing the training phase in software and the actual application in hardware, connicting demands can be met: training beneets from a fast edit-debug cycle, and once the design has stabilized, a hardware implementation results in higher performance. While neural nets have been implemented in hardware...

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...

ÐAesthetically appealing patterns are produced by the dynamical behavior of arti®cial neural networks with randomly chosen connection strengths. These feed-forward networks have a single hidden layer of neurons and a single output, which is fed back to the input to produce a scalar time series that is always bounded and often chaotic. Sample attractors are shown and simple computer code is prov...

Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. For this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. The ...

artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. this paper mainly intends to offer a novel method for finding a solution of a fuzzy equation that supposedly has a real solution. for this scope, we applied an architecture of fuzzy neural networks such that the corresponding connection weights are real numbers. the sugg...

The genotype-phenotype relat ion for the 256 elementary cellular automata is studied using neura l networks. Neural networks are trained to learn the mapping from each genotype rule to its corresponding Li-Packard phenotype class. By invest igating learning curves and networks pruned with Optimal Brain Damage on all 256 rules, we find that there is a correspondence between the complexity of the...