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 Signalsifferent functional expansion is adopted based on the Chebyshev polynomials in order to reduce the overall computational complexity of the model, while achieving good results in terms of perceived quality of processed speech. The proposed model is assessed in the presence of nonlinearities for both simulated and real speech signals.

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2190-3018 financial signals, feedback loops, waveform generations, fi.This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals

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On 4-Dimensional Hypercomplex Algebras in Adaptive Signal Processingrions of choice between one algebra or another. This paper proposes a simple comparison between two isodimensional algebras (quaternions and tessarines) and shows by simulations how different choices may determine the system performance. Some general information about both algebras is also supplied.