Multidisciplinary Approaches to Neural Computing (eBook, PDF)
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Provides fundamental insights for cross-fertilization: machine learning, artificial neural networks (ANNs) (algorithms and models), social and biometric data for applications in human-computer interactions, and neural networks-based approaches to industrial processesIdentifies features from dynamic realistic signal exchanges and invariant machine representations to automatically identify, detect, analyze, and process them in related applicationsSimplifies automatic signal processing and its exploitation in realistic applications devoted to improving the quality of life of the end usersFeatures...
Provides fundamental insights for cross-fertilization: machine learning, artificial neural networks (ANNs) (algorithms and models), social and biometric data for applications in human-computer interactions, and neural networks-based approaches to industrial processes
Identifies features from dynamic realistic signal exchanges and invariant machine representations to automatically identify, detect, analyze, and process them in related applications
Simplifies automatic signal processing and its exploitation in realistic applications devoted to improving the quality of life of the end users
Features contributions from computer science, physics, psychology, statistics, mathematics, electrical engineering, and communication science
Identifies features from dynamic realistic signal exchanges and invariant machine representations to automatically identify, detect, analyze, and process them in related applications
Simplifies automatic signal processing and its exploitation in realistic applications devoted to improving the quality of life of the end users
Features contributions from computer science, physics, psychology, statistics, mathematics, electrical engineering, and communication science
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