Map Similarity Testing Using Matrix Decomposition
The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find an objective method for measuring similarity. This paper presents a method based on Singular Value Decomposition (SVD).
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Published in | 2009 International Conference on Intelligent Networking and Collaborative Systems pp. 290 - 294 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.11.2009
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Subjects | |
Online Access | Get full text |
ISBN | 9781424451654 1424451655 |
DOI | 10.1109/INCOS.2009.74 |
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Abstract | The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find an objective method for measuring similarity. This paper presents a method based on Singular Value Decomposition (SVD). |
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AbstractList | The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find an objective method for measuring similarity. This paper presents a method based on Singular Value Decomposition (SVD). |
Author | Snáel, Václav Voenílek, Vít Dvorský, Jirí |
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Snippet | The similarity of two maps can be most easily compared visually. In this case, the degree of similarity is very subjective. It is therefore necessary to find... |
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SubjectTerms | air temperature climatic maps Intelligent networks International collaboration Matrix decomposition Payloads Real time systems Singular Value Decomposition Streaming media Telecommunication traffic Testing Unicast Web and internet services |
Title | Map Similarity Testing Using Matrix Decomposition |
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