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BLG 609E - Advanced Topics in Comp. Eng.

Course Objectives

1- Understanding neuromorphic computational paradigms of intelligent systems in nature
2- Understanding and performance measure of information processing in neuromorphic systems
3- Design of Spiking Neural Networks depending on neuron and neural system models
4- Design of neuromorphic systems for computation and machine learning
5- Implementation methods of neuromorphic information processing systems (Memristors,BNNs etc.)

Course Description

Due to development of AI applications, performing the cognitive functions by using nature inspired computational paradigms has become a major trend for increasing the power and data efficiency. Neuromorphic computing is based on investigation, modeling and emulation of biological neural systems and the brain-connectome structure. This course covers neuromorphic learning in brain-nerve-connectome structures, spiking neural networks and their artificial implementation, neuromorphic coding, basics of stochastic computing, biomimetic neural networks, cognitive functions and neuromorphic system applications.

Course Coordinator
Burak Berk Üstündağ
Course Language
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