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Very recently, a little work with respect to the dynamic behavior of neural networked system driven by fBm have been reported in [29, 30, 31].
It would be interesting to extend the results here obtained to more general neural networked models incorporating the presence of a delay in neuron interconnections.
In this paper, the existence, uniqueness and asymptotic behavior of mild solutions have been discussed for stochastic neural networked systems driven by fractional Brownian motion.
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A deep neural network copies this arrangement.
The job involved using neural networks.
The second neural network works differently.
One such approach involves "progressive neural networks".
"Neural networks are like black boxes," Pomerleau says.
The neural network then went back and tried again.
"Other people have built hardware models of neural networks.
"That's the bizarre thing about neural networks," Thrun said.
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