Detecting Simulated Attacks in Computer Networks Using Resilient Propagation Artificial Neural Networks

If we start from a basically homogeneous data set that is not rotationally aligned, then the classification will group images according to their relative orientation (examples 1 and

Keywords: Artificial neural networks, neural threshold, neural variability, heterogeneity, homogeneity, olfactory system, pattern recognition, generalist neuron, specialist neuron,

Top: ANN output in the control region used to perform the extrapolation with systematic uncertainties included (left), and the ratio between data and simulated events (right) with

Figure 5 illustrates the structure of the neural network with the eleven nodes corresponding to the input or independent variables (main components), the sole hidden layer nodes

Deep Neural Networks, Bayesian Neural Networks, Calibration, Uncertainty, Variational Inference, Generalized Variational Inference, Robust

The quality factors and coupling coefficients needed as training and testing sets for both boxes were computed using the neural network method described in Ref.. In this method,

Computational Methods in Neural Modeling: 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003 Maó, Menorca, Spain,. June 3–6, 2003 Proceedings,

We show three four-layer multiplex networks (and the corresponding network of layers as an inset in the top-left corners) and recall that each interlayer edge connects a node with