Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods
Abstract The article contains a description of two quantum circuits for pattern recognition. The first approach is realized with use of k nearest neighbors algorithm and the second with support vector machine. The task is to distinguish between Hermitian and non-Hermitian matrices. The quantum circu...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2018-05-01
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| Series: | Vietnam Journal of Computer Science |
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| Online Access: | http://link.springer.com/article/10.1007/s40595-018-0115-y |
| _version_ | 1818902673094606848 |
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| author | Joanna Wiśniewska Marek Sawerwain |
| author_facet | Joanna Wiśniewska Marek Sawerwain |
| author_sort | Joanna Wiśniewska |
| collection | DOAJ |
| description | Abstract The article contains a description of two quantum circuits for pattern recognition. The first approach is realized with use of k nearest neighbors algorithm and the second with support vector machine. The task is to distinguish between Hermitian and non-Hermitian matrices. The quantum circuits are constructed to accumulate elements of a learning set. After this process, circuits are able to produce a quantum state which contains the information if a tested element fits to the trained pattern. To improve the efficiency of presented solutions, the matrices were uniquely labeled with feature vectors. The role of the feature vectors is to highlight some features of the objects which are crucial in the process of classification. The circuits were implemented in Python programming language and some numeric experiments were conducted to examine the capacity of presented solutions in pattern recognition. |
| first_indexed | 2024-12-19T20:39:23Z |
| format | Article |
| id | doaj.art-e2428c063f794c2cbac650b5977abc8f |
| institution | Directory Open Access Journal |
| issn | 2196-8888 2196-8896 |
| language | English |
| last_indexed | 2024-12-19T20:39:23Z |
| publishDate | 2018-05-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | Vietnam Journal of Computer Science |
| spelling | doaj.art-e2428c063f794c2cbac650b5977abc8f2022-12-21T20:06:27ZengWorld Scientific PublishingVietnam Journal of Computer Science2196-88882196-88962018-05-0153-419720410.1007/s40595-018-0115-yRecognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methodsJoanna Wiśniewska0Marek Sawerwain1Institute of Information Systems, Faculty of Cybernetics, Military University of TechnologyInstitute of Control and Computation Engineering, University of Zielona GóraAbstract The article contains a description of two quantum circuits for pattern recognition. The first approach is realized with use of k nearest neighbors algorithm and the second with support vector machine. The task is to distinguish between Hermitian and non-Hermitian matrices. The quantum circuits are constructed to accumulate elements of a learning set. After this process, circuits are able to produce a quantum state which contains the information if a tested element fits to the trained pattern. To improve the efficiency of presented solutions, the matrices were uniquely labeled with feature vectors. The role of the feature vectors is to highlight some features of the objects which are crucial in the process of classification. The circuits were implemented in Python programming language and some numeric experiments were conducted to examine the capacity of presented solutions in pattern recognition.http://link.springer.com/article/10.1007/s40595-018-0115-yQuantum circuitsPattern recognitionSupervised machine learningHamming distance |
| spellingShingle | Joanna Wiśniewska Marek Sawerwain Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods Vietnam Journal of Computer Science Quantum circuits Pattern recognition Supervised machine learning Hamming distance |
| title | Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods |
| title_full | Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods |
| title_fullStr | Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods |
| title_full_unstemmed | Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods |
| title_short | Recognizing the pattern of binary Hermitian matrices by quantum kNN and SVM methods |
| title_sort | recognizing the pattern of binary hermitian matrices by quantum knn and svm methods |
| topic | Quantum circuits Pattern recognition Supervised machine learning Hamming distance |
| url | http://link.springer.com/article/10.1007/s40595-018-0115-y |
| work_keys_str_mv | AT joannawisniewska recognizingthepatternofbinaryhermitianmatricesbyquantumknnandsvmmethods AT mareksawerwain recognizingthepatternofbinaryhermitianmatricesbyquantumknnandsvmmethods |