An Analysis of the Cluster-Detecting Property of the BCM Neuron
The BCM learning rule, named for Elie Bienenstock, Leon Cooper, and Paul Munro, was first proposed to measure the selectivity of neurons in the primary visual cortex and its dependency on neuronal inputs. We show that an artificial BCM neuron has the ability to detect clusters in a dataset. By explo...
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| Language: | English |
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World Scientific Publishing
2024-01-01
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| Series: | Computing Open |
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| Online Access: | https://www.worldscientific.com/doi/10.1142/S2972370124500028 |
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| author | Lawrence Udeigwe |
| author_facet | Lawrence Udeigwe |
| author_sort | Lawrence Udeigwe |
| collection | DOAJ |
| description | The BCM learning rule, named for Elie Bienenstock, Leon Cooper, and Paul Munro, was first proposed to measure the selectivity of neurons in the primary visual cortex and its dependency on neuronal inputs. We show that an artificial BCM neuron has the ability to detect clusters in a dataset. By exploring the qualitative behaviors of an underlying system of differential equations, we present a rigorous mathematical analysis of this cluster-detecting property. While the focus of this work is not to develop a robust state-of-the-art clustering method, we also analyze and discuss the performance of a resulting preliminary clustering algorithm. |
| format | Article |
| id | doaj-art-15ee40b5df2f43acb86b5c4d627d957f |
| institution | Kabale University |
| issn | 2972-3701 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | Computing Open |
| spelling | doaj-art-15ee40b5df2f43acb86b5c4d627d957f2025-02-04T03:24:11ZengWorld Scientific PublishingComputing Open2972-37012024-01-010210.1142/S2972370124500028An Analysis of the Cluster-Detecting Property of the BCM NeuronLawrence Udeigwe0Department of Mathematics, Manhattan College, 4513 Manhattan College Parkway, Riverdale, NY 10471, USAThe BCM learning rule, named for Elie Bienenstock, Leon Cooper, and Paul Munro, was first proposed to measure the selectivity of neurons in the primary visual cortex and its dependency on neuronal inputs. We show that an artificial BCM neuron has the ability to detect clusters in a dataset. By exploring the qualitative behaviors of an underlying system of differential equations, we present a rigorous mathematical analysis of this cluster-detecting property. While the focus of this work is not to develop a robust state-of-the-art clustering method, we also analyze and discuss the performance of a resulting preliminary clustering algorithm.https://www.worldscientific.com/doi/10.1142/S2972370124500028NeuronBCM learning ruleclustering |
| spellingShingle | Lawrence Udeigwe An Analysis of the Cluster-Detecting Property of the BCM Neuron Computing Open Neuron BCM learning rule clustering |
| title | An Analysis of the Cluster-Detecting Property of the BCM Neuron |
| title_full | An Analysis of the Cluster-Detecting Property of the BCM Neuron |
| title_fullStr | An Analysis of the Cluster-Detecting Property of the BCM Neuron |
| title_full_unstemmed | An Analysis of the Cluster-Detecting Property of the BCM Neuron |
| title_short | An Analysis of the Cluster-Detecting Property of the BCM Neuron |
| title_sort | analysis of the cluster detecting property of the bcm neuron |
| topic | Neuron BCM learning rule clustering |
| url | https://www.worldscientific.com/doi/10.1142/S2972370124500028 |
| work_keys_str_mv | AT lawrenceudeigwe ananalysisoftheclusterdetectingpropertyofthebcmneuron AT lawrenceudeigwe analysisoftheclusterdetectingpropertyofthebcmneuron |