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Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Abstract: Pseudo-random binary sequence (PRBS) has been used for internal impedance identification and shown to be faster and easier to implement than analogue multiple frequency signals. To implement ...

It has been proposed by E. Gelenbe in 1989. A Random Neural Network is a compose of Random Neurons and Spikes that circulates through the network. According to this model, each neuron has a positive ...

Install this module from the REDCap External Module Repository and enable it. A debug mode can be enable in the module's project settings. When enabled, some information about the module's actions ...