Topological Analysis of Artificial Neural Network
By: Sharma, Deepshikha
.
Contributor(s): Kashyap, Sunil Kumar.
Publisher: New Delhi Journals Pub 2019Edition: Vol.5(1), Jan-Jun.Description: 17-21p.Subject(s): EXTC EngineeringOnline resources: Click here
In:
International journal of embedded systems and emerging technologiesSummary: ABSTRACT This paper analyzes the Artificial Neural Network (ANN) over the metric. The dimension, curvature and mappings are the three characteristics of analysis. The impact of ANN in finite and infinite space is also considered. The Euclidean metric is the limit of generalization. The structure of neuron and its mapping are presented over the finite dimension. The discrete and continuous structure of neurons is studied mathematically and its formulation is proposed with minimized errors for the application context. Hence, this topological study opens several doors of application in discrete spaces.
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2020124 |
ABSTRACT This paper analyzes the Artificial Neural Network (ANN) over the metric. The dimension, curvature and mappings are the three characteristics of analysis. The impact of ANN in finite and infinite space is also considered. The Euclidean metric is the limit of generalization. The structure of neuron and its mapping are presented over the finite dimension. The discrete and continuous structure of neurons is studied mathematically and its formulation is proposed with minimized errors for the application context. Hence, this topological study opens several doors of application in discrete spaces.
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