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ECE 613 Neuromorphic Computing 3.0 Credits
This course will cover the principles of neuromorphic computing. Topics will cover 1) fundamentals of spiking neural network (SNN), which mimics the computation in mammalian brain; 2) supervised and unsupervised learning algorithms for SNN; 3) novel applications of SNN, including in vision and time series processing; 4) architectures for implementing SNN in hardware, aka neuromorphic hardware; 5) introduction to non-volatile memory technologies to implement synaptic processing in neuromorphic hardware; 6) software stacks for neuromorphic computing; and 7) design challenges in dependable neuromorphic computing.
Repeat Status: Not repeatable for credit
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https://catalog.drexel.edu/graduate/collegeofengineering/mechanicalengineeringandmechanicsphd/
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