Sentence examples for recurrent neuron network from inspiring English sources
There are many SVM supervector reconstruction algorithms such as recurrent neuron network (RNN) SVM supervector reconstruction [24].
1000 neuron network is run.
The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns.
The Liquid State Machine is a recurrent neural network of spiking neurons where only the output layer is trained.
The paper deals with a discrete-time recurrent neural network designed with dynamic neuron models.
The goal of a network-level analysis is to predict emergent computational properties in populations and recurrent networks of neurons from the properties of their component cells.
... We investigated the enteric circuits that regulate segmentation focusing on a central feature of the ENS: a recurrent excitatory network of intrinsic sensory neurons (ISNs) which are characterized by prolonged after-hyperpolarizing potentials (AHPs) following their action potentials.
The content of conscious experience (11) is then viewed as being processed through a recurrent horizontal network of cortical pyramidal neurons with long-distance connections assembling thalamocortical regions, particularly prefrontal and higher association areas, parietotemporal and cingulate cortices (12) referred to here as GNW circuits (8,9).
We investigated the enteric circuits that regulate segmentation focusing on a central feature of the ENS: a recurrent excitatory network of intrinsic sensory neurons (ISNs) which are characterized by prolonged after-hyperpolarizing potentials (AHPs) following their action potentials.
At the next scale up in the modeling of neural tissue, a central goal is to predict emergent computational properties in populations and recurrent networks of neurons (Gerstner and van Hemmen 1993; Brunel and Hakim 1999; Gerstner 2000; Brunel and Wang 2003; Gigante et al. 2007) from the properties of their component cells.
It is also necessary to model the spiking responses of neurons within their recurrent network.
