Neural Advances in Processing Nonlinear Dynamic Signals
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Beschreibung
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
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
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
Autor*in
Anna Esposito
Themen in »Neural Advances in Processing Nonlinear Dynamic Signals«
Financial and Industrial Process Speech Enhancement Machine Learning Methods Neural Networks Nonlinear Signal Processing Decision Making in Economic and Finance Evolutionary Algorithms complexity