Memristive Hebbian Plasticity Model: Device Requirements for the Emulation of Hebbian Plasticity Based on Memristive Devices
Autor: | Thorsten Bartsch, Hermann Kohlstedt, Mirko Hansen, Martin Ziegler, Christoph Riggert |
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Rok vydání: | 2015 |
Předmět: |
Neurons
Engineering Emulation Neuronal Plasticity Artificial neural network business.industry Models Neurological Transistor Biomedical Engineering Plasticity law.invention Synaptic weight Hebbian theory Neuromorphic engineering Biomimetics law Synapses Electronic engineering Humans Nanotechnology Neural Networks Computer Electronics Electrical and Electronic Engineering business |
Zdroj: | IEEE Transactions on Biomedical Circuits and Systems. 9:197-206 |
ISSN: | 1940-9990 1932-4545 |
Popis: | In this work we present a phenomenological model for synaptic plasticity suitable to describe common plasticity measurements of memristive devices. We show evidence that the presented model is basically compatible with advanced biophysical plasticity models, which account for a large body of experimental data on spike-timing-depending plasticity (STDP) as an asymmetric form of Hebbian learning. The basic characteristics of our model are a saturation of the synaptic weight growth and a weight dependent learning rate. Moreover, it accounts for common resistive switching behaviors of memristive devices under voltage pulse application and allows to study essential requirements of individual memristive devices for the emulation of Hebbian plasticity in neuromorphic circuits. In this respect, memristive devices based on mixed ionic/electronic and one exclusively electronic mechanism are explored. The ionic/electronic devices consist of the layer sequence metal/isolator/metal and represent today's most popular devices. The electronic device is a MemFlash-cell which is based on a conventional floating gate transistor in a diode configuration wiring scheme exhibiting a memristive (pinched) I-V characteristic. |
Databáze: | OpenAIRE |
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