{"title":"对 BCM 神经元集群检测特性的分析","authors":"Lawrence C. Udeigwe","doi":"10.1142/s2972370124500028","DOIUrl":null,"url":null,"abstract":"The BCM learning rule was first proposed by Elie Bienenstock, Leon Cooper, and Paul Munro to measure the selectivity of neurons in the primary visual cortex and its dependency on neuronal inputs. 4 We show that an artificial BCM neuron has the ability to detect clusters in a dataset. While paying attention to the qualitative behavior of an underlying system of differential equations, we present an analysis of this cluster-detecting property of such a neuron. We also analyze, and discuss the performance of, a resulting clustering algorithm.","PeriodicalId":472615,"journal":{"name":"Computing Open","volume":" 47","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Analysis of the Cluster-Detecting Property of the BCM Neuron\",\"authors\":\"Lawrence C. Udeigwe\",\"doi\":\"10.1142/s2972370124500028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The BCM learning rule was first proposed by Elie Bienenstock, Leon Cooper, and Paul Munro to measure the selectivity of neurons in the primary visual cortex and its dependency on neuronal inputs. 4 We show that an artificial BCM neuron has the ability to detect clusters in a dataset. While paying attention to the qualitative behavior of an underlying system of differential equations, we present an analysis of this cluster-detecting property of such a neuron. We also analyze, and discuss the performance of, a resulting clustering algorithm.\",\"PeriodicalId\":472615,\"journal\":{\"name\":\"Computing Open\",\"volume\":\" 47\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computing Open\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.1142/s2972370124500028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computing Open","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1142/s2972370124500028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
BCM 学习规则最早由 Elie Bienenstock、Leon Cooper 和 Paul Munro 提出，用于测量初级视觉皮层神经元的选择性及其对神经元输入的依赖性。4 我们的研究表明，人工 BCM 神经元具有在数据集中检测集群的能力。在关注底层二阶方程系统的定性行为的同时，我们对这种神经元的集群检测特性进行了分析。我们还分析并讨论了由此产生的聚类算法的性能。
An Analysis of the Cluster-Detecting Property of the BCM Neuron
The BCM learning rule was first proposed by Elie Bienenstock, Leon Cooper, and Paul Munro to measure the selectivity of neurons in the primary visual cortex and its dependency on neuronal inputs. 4 We show that an artificial BCM neuron has the ability to detect clusters in a dataset. While paying attention to the qualitative behavior of an underlying system of differential equations, we present an analysis of this cluster-detecting property of such a neuron. We also analyze, and discuss the performance of, a resulting clustering algorithm.
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