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Memristor-based multi-synaptic spiking neuron circuit for spiking neural network

Chinese Physics B 2022年第4期31卷 225-233页

作者： Wenwu Jiang Jie Li Hongbo Liu Xicong Qian Yuan Ge Lidan Wang Shukai Duan College of Artificial Intelligence Southwest UniversityChongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China

spiking neural networks(SNNs) are widely used in many fields because they work closer to biological ***,due to its computational complexity,many SNNs implementations are limited to computer ***,this paper proposes a multi-synaptic circuit(MSC) based on memristor,which realizes the multi-synapse connection between neurons and the multi-delay transmission of pulse *** synapse circuit participates in the calculation of the network while transmitting the pulse signal,and completes the complex calculations on the software with ***,a new spiking neuron circuit based on the leaky integrate-and-fire(LIF) model is designed in this *** amplitude and width of the pulse emitted by the spiking neuron circuit can be adjusted as *** combination of spiking neuron circuit and MSC forms the multi-synaptic spiking neuron(MSSN).The MSSN was simulated in PSPICE and the expected result was obtained,which verified the feasibility of the ***,a small SNN was designed based on the mathematical model of *** the SNN is trained and optimized,it obtains a good accuracy in the classification of the IRIS-dataset,which verifies the practicability of the design in the network.

关键词： memristor multi-synaptic circuit spiking neuron spiking neural network(SNN)

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Sailboat navigation control system based on spiking neural networks

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Control Theory and Technology 2023年第4期21卷 489-504页

作者： Nelson Santiago Giraldo Sebastián Isaza Ricardo Andrés Velásquez Department of Electronics and Telecommunications Engineering University of Antioquia67 stMedellin050010AntioquiaColombia

In this paper,we presented the development of a navigation control system for a sailboat based on spiking neural networks(SNN).Our inspiration for this choice of network lies in their potential to achieve fast and low-energy computing on specialized *** train our system,we use the modulated spike time-dependent plasticity reinforcement learning rule and a simulation environment based on the BindsNET library and USVSim *** objective was to develop a spiking neural network-based control systems that can learn policies allowing sailboats to navigate between two points by following a straight line or performing tacking and gybing strategies,depending on the sailing scenario *** presented the mathematical definition of the problem,the operation scheme of the simulation environment,the spiking neural network controllers,and the control strategy *** a result,we obtained 425 SNN-based controllers that completed the proposed navigation task,indicating that the simulation environment and the implemented control strategy work ***,we compare the behavior of our best controller with other algorithms and present some possible strategies to improve its performance.

关键词： Sailboat Control spiking neuron Reinforcement learning BindsNet USVSim

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Light-stimulated adaptive artificial synapse based on nanocrystalline metal-oxide film

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Opto-Electronic Science 2023年第10期2卷 1-11页

作者： Igor S.Balashov Alexander A.Chezhegov Artem S.Chizhov Andrey A.Grunin Konstantin V.Anokhin Andrey A.Fedyanin Faculty of Physics Lomonosov Moscow State UniversityMoscow 119991Russia Faculty of Chemistry Lomonosov Moscow State UniversityMoscow 119991Russia Institute for Advanced Brain Studies Lomonosov Moscow State UniversityMoscow 119991Russia P.K.Anokhin Research Institute of Normal Physiology Moscow 125315Russia.

Artificial synapses utilizing spike signals are essential elements of new generation brain-inspired *** this paper,we realize light-stimulated adaptive artificial synapse based on nanocrystalline zinc oxide *** artificial synapse photoconductivity shows spike-type signal response,long and short-term memory(LTM and STM),STM-to-LTM transition and paired-pulse *** is also retaining the memory of previous exposures and demonstrates spike-frequency adaptation properties.A way to implement neurons with synaptic depression,tonic excitation,and delayed accelerating types of response under the influence of repetitive light signals is *** developed artificial synapse is able to become a key element of neuromorphic chips and neuromorphic sensorics systems.

关键词： neuromorphic photonics synaptic adaptation spiking neuron neuromorphic computing optoelectronic synaptic devises nanocrystalline metal-oxide film

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