Neural Advances in Processing Nonlinear Dynamic Signals

Neural Advances in Processing Nonlinear Dynamic Signals


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 for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies

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Anna Esposito, Marcos Faundez-Zanuy, Francesco Carlo Morabito, Eros Pasero
Hardback | 318 pages
155 x 235 x 19.05mm | 664g
Publication date
22 Aug 2018
Springer International Publishing AG
Publication City/Country
Cham, Switzerland
Edition Statement
1st ed. 2019
Illustrations note
61 Illustrations, color; 30 Illustrations, black and white; XII, 318 p. 91 illus., 61 illus. in color.