General and stable emulation of finite state machines with spiking neural networks

General and stable emulation of finite state machines with spiking neural networks

Finite state machines (FSMs) are fundamental models widely used in a variety of domains for state control. However, they face challenges in modeling complex especially black-box systems without explicit state descriptions. Neural networks, conversely, excel at modeling implicit and continuous system...

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Bibliographic Details
Main Authors: Ziyang Sun, Zhong Zheng, Binying Zhang, Hanle Zheng, Zikai Wang, Hao Guo, Lei Deng
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Neuromorphic Computing and Engineering
Subjects:
spiking neural networks (SNNs)
finite state machine (FSM)
discrete-time spiking recurrent neural networks (DTSRNNs)
discrete-time recurrent neural networks ( DTRNNs)
temporal stability
Online Access:https://doi.org/10.1088/2634-4386/adc32d
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https://doi.org/10.1088/2634-4386/adc32d

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