Stanford Seminar - Neuromorphic Chips - Addressing the Nanostransistor Challenge
Stanford University
60 Courses
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Overview
This course aims to teach learners about neuromorphic chips and how they address the nanotransistor challenge. The learning outcomes include understanding the concept of neuromorphic computing, implementing dendritic computation with subthreshold analog, and comparing digital, analog, and neuromorphic computing.
The course covers skills such as approximating dynamic transformations with the Neural Engineering Framework (NEF) and building whole-brain models with spiking neurons.
The teaching method involves a seminar format with a focus on theoretical concepts and practical examples.
This course is intended for individuals interested in advanced topics in computer science, neuromorphic engineering, and artificial intelligence.
University: Stanford University
Provider:
Categories: Electrical Engineering Courses
