Park, Jongkil Jung, Sang-Don 2024-01-19T17:32:00Z 2024-01-19T17:32:00Z 2021-09-04 2020-06 1549-8328 https://pubs.kist.re.kr/handle/201004/118589 Learning plays an important role in the brain to make it adaptive to dynamical environments. This paper presents a presynaptic spike-driven spike timing-dependent plasticity (STDP) learning rule in the address domain for a neuromorphic architecture using a synaptic connectivity table in an external memory at a local routing node. We contribute two aspects to the implementation of the learning rule for extended large-scale neuromorphic systems. First, we reduced buffer sizes required for tracing a spike train which is required to pair all presynaptic and postsynaptic spike for an STDP time window. This method implements an exponential decay STDP function with two parameters: the latest timestamp and the synaptic modification rate at the latest timestamp. It reduces the required buffer size compared to previous works. Second, we resolve a lack of reverse lookup table issue with the presynaptic spike-driven algorithm. The proposed algorithm holds causal updates at postsynaptic spikes until a next presynaptic spike arrival. This approach removes the need of a reverse lookup table required at a postsynaptic spike. We show the implementation of the proposed algorithm in an FPGA device and validate it with a spiking neural network configuration. The experiment results show the proposed algorithm is comparable qualitatively with a conventional STDP learning rule. English IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC SYNAPTIC PLASTICITY MODEL NETWORK NEURONS STDP Presynaptic Spike-Driven Spike Timing-Dependent Plasticity With Address Event Representation for Large-Scale Neuromorphic Systems Article 10.1109/TCSI.2020.2966884 1 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, v.67, no.6, pp.1936 - 1947 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 67 6 1936 1947 scie scopus 000543062600014 2-s2.0-85086011247 Engineering, Electrical & Electronic Engineering Article SYNAPTIC PLASTICITY MODEL NETWORK NEURONS STDP Neurons Neuromorphics Hardware Field programmable gate arrays Routing Heuristic algorithms Random access memory Address domain column selectivity reverse lookup table STDP synaptic table