This textbook provides a general introduction to the field of neural networks, concentrating on networks for modeling brain processes involved in cognitive and behavioral functions.
This textbook provides a general introduction to the field of neural networks, concentrating on networks for modeling brain processes involved in cognitive and behavioral functions.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Daniel S. Levine is Professor of Psychology at the University of Texas at Arlington. He is a Fellow and former President of the International Neural Network Society. His research involves computational modeling of brain processes in decision making and cognitive-emotional interactions.
Inhaltsangabe
Contents Part I: Foundations of Neural Network Theory Chapter 1: Neural Networks for Modeling Behavior Chapter 2: Historical Outline Chapter 3: Associative Learning and Synaptic Plasticity Chapter 4: Competition, Lateral Inhibition, and Short-Term Memory Part II: Computational Cognitive Neuroscience Chapter 5: Progress in Cognitive Neuroscience Chapter 6: Models of Conditioning and Reinforcement Learning Chapter 7: Models of Coding, Categorization, and Unsupervised Learning Chapter 8: Models of Supervised Pattern and Category Learning Chapter 9: Models of Complex Mental Functions Appendices Appendix 1: Mathematical Techniques for Neural Networks Appendix 2: Basic Facts of Neurobiology References
