Neural Advances in Processing Nonlinear Dynamic Signals

Anna Esposito (Redaktør) ; Anna Esposito (Redaktør)

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 from arrays of sensors, and perturbations in the automatic control of industrial production processes. Les mer
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1494,-

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Min side | Adobe Digital Editions
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Vår pris: 1494,-

(E-bok)
E-bøker kan leses umiddelbart etter kjøp
Min side | Adobe Digital Editions
E-boken må lastes ned i løpet av 2 år

Om boka

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 from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community.Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques.This book is a valuable resource fora. The academic research communityb. The ICT marketc.  PhD students and early stage researchersd. Companies, research institutese. Representatives from industry and standardization bodies

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