Neuromorphic Cognitive Systems, Softcover reprint of the original 1st ed. 2017 A Learning and Memory Centered Approach Intelligent Systems Reference Library Series, Vol. 126
Auteurs : Yu Qiang, Tang Huajin, Hu Jun, Tan Chen Kay
The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed.
The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.
Discusses the computational principles underlying spike-based information processing and cognitive computation with a specific focus on learning and memory
Describes theoretical modeling and analysis as well as practical applications
Presents the computational ability of bio-inspired systems and offers insights into the mechanisms by which the nervous system operates
Provides theories, concepts, methods and applications
Includes supplementary material: sn.pub/extras
Date de parution : 05-2018
Ouvrage de 172 p.
15.5x23.5 cm
Date de parution : 05-2017
Ouvrage de 172 p.
15.5x23.5 cm