Neuromorphic Computing: Concepts and Hardware Implementations

Related lectures (29)

Page 3 of 3

Explores neural architectures for embodied AI, cognitive systems, and the integration of computing and robotics.

Compares digital and neuromorphic computing, highlighting challenges and future prospects in the field.

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Explores neuronal plasticity, synaptic changes, brain functioning, and unconscious states through various mechanisms.

Covers synaptic plasticity, types of synapses, Hebb's postulate, LTP, LTD, and network oscillations in the hippocampus.

Covers the fundamentals of computational neuroscience, focusing on biophysics and modeling.

Explores electric fields, energy storage, charge displacement, DC currents, and historical aspects of electricity.

Covers modeling electrophysiology at different scales, discussing ion channels, single neurons, and microcircuits.