Neural advances in processing nonlinear dynamic signals / Anna Esposito, Marcos Faundez-Zanuy, Francesco Carlo Morabito, Eros Pasero, editors.
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 c...
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| Other Authors: | , , , |
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| Format: | Ebook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
[2019]
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| Series: | Smart innovation, systems, and technologies ;
v. 102. |
| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | 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--Provided by publisher. |
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| Physical Description: | 1 online resource. |
| ISBN: | 3319950975 3319950983 9783319950976 9783319950983 |