Neural Advances in Processing Nonlinear Dynamic Signals

TRAMA

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

SOMMARIO

Processing Nonlinearities.- Temporal Artifacts from Edge Accumulation in Social Interaction.- Data Mining by Evolving Agents for Clusters Discovery and Metric Learning.- Error Resilient Neural Networks on Low-Dimensional Manifolds.- On 4-Dimensional Hypercomplex Algebras in Adaptive Signal Processing.- Growing Curvilinear Component Analysis (GCCA) for Stator Fault Detection in Induction Machines.- Convolutional Neural Networks for the Identification of Filaments from Fast Visual Imaging Cameras in Tokamak Reactors.- Appraisal of Enhanced Surrogate Models for Substrate Integrate Waveguide Devices Characterization.- An Improved PSO for Flexible Parameters Identification of Lithium Cells Equivalent Circuit Models.- New Challenges in Pension Industry: Proposals of Personal Pension Products.- A Method Based on OWA Operator for Scientific Research Evaluation.- A Cluster Analysis Approach for Rule Base Reduction.

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9783030069773
• Collana: Smart Innovation, Systems and Technologies
• Dimensioni: 235 x 155 mm
• Formato: Brossura
• Illustration Notes: XII, 318 p. 91 illus., 61 illus. in color.
• Pagine Arabe: 318
• Pagine Romane: xii