Titlebook: Neural Advances in Processing Nonlinear Dynamic Signals; Anna Esposito,Marcos Faundez-Zanuy,Eros Pasero Book 2019 Springer International P

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A Low-Complexity Linear-in-the-Parameters Nonlinear Filter for Distorted Speech Signalsnear model yielding the best tradeoff between performance results and required computational resources. Functional link adaptive filters were proved to be an effective model for this problem, providing the best performance when trigonometric expansion is used as a nonlinear transformation. Here, a d

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Hierarchical Temporal Representation in Linear Reservoir Computingf linear recurrent units allows us to bring more evidence on the intrinsic hierarchical temporal representation in deep RNNs through frequency analysis applied to the state signals. The potentiality of our approach is assessed on the class of Multiple Superimposed Oscillator tasks. Furthermore, our

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Convolutional Neural Networks for the Identification of Filaments from Fast Visual Imaging Cameras itructures that arise in the boundary region of the plasma in toroidal nuclear fusion reactors. The images required to train and test the neural model have been synthetically generated from statistical distributions, which reproduce the statistical properties in terms of position and intensity of exp

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