Neural Advances in Processing Nonlinear Dynamic Signals
Editors: Esposito, A., Faundez-Zanuy, M., Morabito, F.C., Pasero, E. (Eds.)
Free Preview- Presents neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generations, filtering, equalization, signals from arrays of sensors, and perturbation in the automatic control of industrial production processes
- Proposes approaches to measure and highlight the importance of the use of intelligent tools in the investigation of economic/financial and industrial processes
- Covers different scientific areas in computational intelligence and related techniques in financial, industrial, and information and communications technology (ICT) engineering
- Includes contributions from leading experts
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- About this book
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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
- Table of contents (28 chapters)
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Processing Nonlinearities
Pages 3-7
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Temporal Artifacts from Edge Accumulation in Social Interaction Networks
Pages 11-21
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Data Mining by Evolving Agents for Clusters Discovery and Metric Learning
Pages 23-35
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Neural Beamforming for Speech Enhancement: Preliminary Results
Pages 37-47
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Error Resilient Neural Networks on Low-Dimensional Manifolds
Pages 49-59
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Table of contents (28 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Neural Advances in Processing Nonlinear Dynamic Signals
- Editors
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- Anna Esposito
- Marcos Faundez-Zanuy
- Francesco Carlo Morabito
- Eros Pasero
- Series Title
- Smart Innovation, Systems and Technologies
- Series Volume
- 102
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG, part of Springer Nature
- eBook ISBN
- 978-3-319-95098-3
- DOI
- 10.1007/978-3-319-95098-3
- Hardcover ISBN
- 978-3-319-95097-6
- Softcover ISBN
- 978-3-030-06977-3
- Series ISSN
- 2190-3018
- Edition Number
- 1
- Number of Pages
- XII, 318
- Number of Illustrations
- 30 b/w illustrations, 61 illustrations in colour
- Topics
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