392249 ISY Project: Learning in memristive systems (Pj) (SoSe 2020)
Contents, comment
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In recent years various learning algorithms for spike-based neural networks have been proposed including Hebbian learning and spike-timing dependent plasticity (STDP). At the same time the behavior of state-changing memristive devices shows promissing results for their integration in neural networks.
In this project we seek to advance the implementation of stochastic memristive devices as synaptic building blocks and their ability to reproduce learning models. Based on models obtained from physical devices you will simulate neural networks consisting of memristive devices and integrate-and-fire neurons. Different network topologies and learning performances will be evaluated on common machine learning tasks.
In case this would not find enough interest for a team project, this project proposal would be also offered (in reduced/modified form)
[x] as individual project
[x] as project for 2-3 students
Requirements for participation, required level
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- good programming skills in Python
- basic knowledge of spiking neural networks
Teaching staff
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-M-Inf-GP Grundlagenprojekt Intelligente Systeme | Gruppenprojekt | Ungraded examination
|
Student information |
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