期刊论文

Lin, Qiuzhen;Todo, Yuki

英文

IEEE Transactions on Neural Networks and Learning Systems

2162-237X

2021

32

11

5194-5207

10.1109/TNNLS.2020.3027298

Guangdong Basic and Applied Basic Research Fund Project [2019A1515111139]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61876110, 61876162]; Japan Society for the Promotion of Science JSPS KAKENHIMinistry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Japan Society for the Promotion of ScienceGrants-in-Aid for Scientific Research (KAKENHI) [JP19K12136]; Joint Funds of the National Natural Science Foundation of China under Key Program [U1713212]

本校为其他机构

An approximate logic neural model (ALNM) is a novel single-neuron model with plastic dendritic morphology. During the training process, the model can eliminate unnecessary synapses and useless branches of dendrites. It will produce a specific dendritic structure for a particular task. The simplified structure of ALNM can be substituted by a logic circuit classifier (LCC) without losing any essential information. The LCC merely consists of the comparator and logic NOT, AND, and OR gates. Thus, it can be easily implemented in hardware. However, the architecture of ALNM affects the learning capac...