Patent attributes
The present disclosure relates to systems and methods for creating and training neural networks. The method includes collecting a set of signals from a database; applying a transform to each signal to create a modified set of signals, wherein signals of the modified set of signals are wavelets; iteratively, for each of a subset of the modified signals: training the neural network using a modified signal of the subset by adding at least one node to the neural network in response to an error function of an analysis of the modified signal exceeding a threshold; removing nodes from the neural network with activation rates below an activation rate threshold; and grouping each node into a lobe among a plurality of lobes, wherein nodes belonging to a lobe have a common characteristic.
