Comparison of neuronal and behavioural thresholds implies a nearly one-to-one transformation of visual neuron performance to the visuo-motor output.
Fig. 1 The neuron performance in mathematic language [6].
Now, Fig. 1 indicates the neuron performance, mathematically.
This feature restricts neuron performance for modeling the complex nonlinear problems.
Because of multi-layer network architectures with stochastic neurons, GSN performance depends on the selected architecture and network training.
Due to the limited operating range of visual neurons, such performance requires extremely efficient regulation mechanisms.
When there were more than 13 neurons, the performance of the trained neural network on output sample in the testing set began to deteriorate.
As illustrated in Figure 5, voiding two to three parameters or neurons reduced the performance of all four ANNs.
Out of 60 different network architecture, In-trigram based pattern recognition network with 20 neurons produced outstanding performance with 85.72% accuracy.
We performed the quantification of Tat released from infected cells and taken up by neurons using high performance capillary electrophoresis.
