Concept
Bio-inspired computing
Related lectures (16)
General Introduction to Artificial Neural Networks
Covers the history and inspiration behind artificial neural networks, the structure of neurons, learning through synaptic connections, and the mathematical description of artificial neurons.
Bio-Inspired Learning: Neural Networks, Genetic Algorithms
Explores bio-inspired learning with neural networks and genetic algorithms, covering structure, training, and practical applications.
Neuromorphic Computing: Challenges & Future
Compares digital and neuromorphic computing, highlighting challenges and future prospects in the field.
Neuromorphic Computing: Challenges and Future
Discusses the challenges and future of neuromorphic computing, comparing digital computers and specialized hardware, such as SpiNNaker and NEST, while exploring the Human Brain Project's Neuromorphic Computing Platform.
Building Physical Neural Networks
Discusses challenges in building physical neural networks, focusing on depth, connections, and trainability.
Learning to Find a Goal
Delves into a biologically inspired version of Reinforcement Learning, focusing on maze navigation and the implementation of spiking neurons.
Biophysical Understanding of Neuronal Behavior
Explores the biophysical understanding of neuronal behavior, focusing on action potentials, neuron modeling challenges, and dendritic inhibition.
Neuromorphic Computing: Concepts and Hardware Implementations
Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.