A probabilistic neural network for earthquake magnitude prediction

By Hojjat Adeli, Ashif Panakkat. Neural Networks, 2009

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A comparative study of wavelet families for EEG signal classification (2011, background): “The sole purpose of feature extraction, is to extract salient characteristics from digitized data collected from the data acquisition phase [3] followed by classification based on the extracted features [4] [5] [6] [7] [8].”
A New Neural Dynamic Classification Algorithm (2017, positive): “PNN has been widely used for many applications, such as health monitoring of prestressed concrete pile [15] and earthquake magnitude prediction [12], Based on the Bayesian concept [16], PNN employs a Gaussian probability density function (pdf) and the Euclidean distance between the data points (feat”
Enhanced probabilistic neural network with local decision circles: A robust classifier (2010, neutral): “ing [13], hydrology [86],ocean engineering [50], image”
Application of Recurrence Quantification Analysis for the Automated Identification of Epileptic EEG Signals (2011, background): “The second layer is the competitive layer that sums these contributions for each input classes and produces a vector of probabilities as its output.(8,11) The ‘compete’ transfer function at the output of the second layer selects the maximum of these probabilities, and assigns a 1 for that selected c”