Temporally learning floating-gate VLSI synapses

We present a floating-gate synaptic circuit that updates its weight according to the Spike-Timing-Dependent Plasticity (STDP) rule. The weight (or floating-gate voltage) is updated only if the time difference between the pre- and post-synaptic spikes falls within a learning window. The update is imp...

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Bibliographic Details
Main Authors: Shih-Chii Liu, Mockel, Rico
Format: Conference Proceeding
Language:English
Subjects:
Analog memory
Leakage current
Learning systems
Nonvolatile memory
Pulse circuits
Pulse generation
Tunneling
Unsupervised learning
Very large scale integration
Voltage
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Description
Summary:We present a floating-gate synaptic circuit that updates its weight according to the Spike-Timing-Dependent Plasticity (STDP) rule. The weight (or floating-gate voltage) is updated only if the time difference between the pre- and post-synaptic spikes falls within a learning window. The update is implemented through tunneling and injection mechanisms which can be tuned for very long time constants up to seconds. The novelty of this circuit is that the tunneling and injection mechanisms are turned on only when the correlation of the pre and postsynaptic activity is significant. The additional benefit of this non-volatile technology is that synaptic weights can be stored locally on chip. We present experimental results that show the learning and normalization effects from the fabricated circuits.
ISSN:0271-4302
2158-1525
DOI:10.1109/ISCAS.2008.4541877