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@INPROCEEDINGS{Feiler:1037900,
author = {Feiler, Florian and Neftci, Emre and Bouhadjar, Younes},
title = {{U}nsupervised {L}earning of {S}patio-{T}emporal {P}atterns
in {S}piking {N}euronal {N}etworks},
reportid = {FZJ-2025-01038},
pages = {366 - 370},
year = {2024},
abstract = {The ability to predict future events or patterns based on
previous experience is crucial for many applications such as
traffic control, weather forecasting, or supply chain
management. While modern supervised Machine Learning
approaches excel at such sequential tasks, they are
computationally expensive and require large training data. A
previous work presented a biologically plausible sequence
learning model, developed through a bottom-up approach,
consisting of a spiking neural network and unsupervised
local learning rules. The model in its original formulation
identifies only a specific type of sequence elements
composed of synchronous spikes by activating a subset of
neurons with identical stimulus preference. In this work, we
extend the model to detect and learn sequences of various
spatio-temporal patterns (STPs) by incorporating plastic
connections in the input synapses. We showcase that the
model is able to learn and predict high-order sequences. We
further study the robustness of the model against different
input settings and parameters.},
month = {Jul},
date = {2024-07-30},
organization = {International Conference on
Neuromorphic Systems (ICONS),
Arlington, Virginia (USA), 30 Jul 2024
- 2 Aug 2024},
cin = {PGI-15 / PGI-7},
cid = {I:(DE-Juel1)PGI-15-20210701 / I:(DE-Juel1)PGI-7-20110106},
pnm = {5234 - Emerging NC Architectures (POF4-523) / BMBF
16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien
der künstlichen Intelligenz für die Elektronik der Zukunft
- NEUROTEC II - (BMBF-16ME0398K) / BMBF 16ME0399 -
Verbundprojekt: Neuro-inspirierte Technologien der
künstlichen Intelligenz für die Elektronik der Zukunft -
NEUROTEC II - (BMBF-16ME0399)},
pid = {G:(DE-HGF)POF4-5234 / G:(DE-82)BMBF-16ME0398K /
G:(DE-82)BMBF-16ME0399},
typ = {PUB:(DE-HGF)8},
url = {https://juser.fz-juelich.de/record/1037900},
}