This book describes new theories and applications of artificial neural networks, with a special focus on neural computation, cognitive science and machine learning. It discusses cutting-edge research at the intersection between different fields, from topics such as cognition and behavior, motivation and emotions, to neurocomputing, deep learning, classification and clustering. Further topics include signal processing methods, robotics and neurobionics, and computer vision alike. The book includes selected papers from the XIX International Conference on Neuroinformatics, held on October 2-6, 2017, in Moscow, Russia.
Includes selected papers from the XIX International Conference on Neuroinformatics, held on October 2–6, 2017, in Moscow, Russia
Reports on both the theory and applications of artificial neural networks
Presents topics ranging from advances in machine learning to evolutionary programming and neuroimaging/neurobiologyOffers a multidisciplinary perspective on neuroinformatics
Boris Kryzhanovsky
Neural Excitability Cellular Mechanisms Cognition and Behavior Learning and Memory Motivation and Emotion Bayesian Networks Kernel Methods Generative Models Deep Learning Networks Memristor Based Neural Networks Random Neural Networks Modeling Dynamical Systems Brain Reverse Engineering Biomedical Signal Processing Modeling of Cognitive Evolution