典型文献
A spintronic memristive circuit on the optimized RBF-MLP neural network
文献摘要：
A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its pa-rameters are set appropriately.However,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as well.In view of this,a novel radial basis neural network(RBF-MLP)is proposed in this article.By connecting two networks to work cooperatively,the RBF's parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating error.Furthermore,a genetic algorithm is used to optimize the network's hidden layer to confirm the optimal neurons(basis function)number automatically.In addition,a memri stive circuit model is proposed to realize the neural network's operation based on the characteristics of spin memristors.It is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33％accuracy in the processing of the Modified National Institute of Standards and Technology(MNIST)dataset classification task.The experimental results show that the method has considerable applica-tion value.
文献关键词：
中图分类号：
作者姓名：
Yuan Ge;Jie Li;Wenwu Jiang;Lidan Wang;Shukai Duan
作者机构：
School of Artificial Intelligence,Southwest University,Chongqing 400715,China;Chongqing Brain Science Collaborative Innovation Center,Chongqing 400715,China;Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory,Chongqing 400715,China;National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology,Chongqing 400715,China
文献出处：
引用格式：
[1]Yuan Ge;Jie Li;Wenwu Jiang;Lidan Wang;Shukai Duan-.A spintronic memristive circuit on the optimized RBF-MLP neural network)[J].中国物理B（英文版）,2022(11):305-316
A类：
memri,stive
B类：
spintronic,memristive,circuit,optimized,RBF,MLP,neural,radial,basis,function,has,excellent,generalization,ability,approximation,accuracy,when,its,are,appropriately,However,relying,only,traditional,methods,difficult,obtain,optimal,parameters,construct,stable,model,well,view,this,novel,proposed,article,By,connecting,networks,cooperatively,can,adjusted,adaptively,by,structure,multi,layer,perceptron,realize,effect,backpropagation,updating,error,Furthermore,genetic,algorithm,used,hidden,confirm,neurons,number,automatically,addition,operation,characteristics,memristors,It,verified,that,outstanding,robustness,stably,achieve,processing,Modified,National,Institute,Standards,Technology,MNIST,dataset,classification,task,experimental,results,show,considerable,applica,value
AB值：
0.57049
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