Quantitative Assessment of Direction-Alignment of Fuzzy Vectors for Pattern Classification and Matching-Reference-Cited by-同舟云学术

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Quantitative Assessment of Direction-Alignment of Fuzzy Vectors for Pattern Classification and Matching

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
language:
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Author:

Konar Dipanjan¹,laha Mousumi²,Konar Amit²,Nagar Atulya K.³

Affiliation:

1. Electronics & Telecommunication Engineering Department, Calcutta University, India

2. Electronics & Telecommunication Engineering Department, Jadavpur University, India

3. Department of Math and Computer Science, Liverpool Hope University, Liverpool, UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9882530/9882539/09882616.pdf?arnumber=9882616

Reference29 articles.

1. Different Representations of Fuzzy Vectors

2. Supervised machine learning: A review of classification techniques;kotsiantis;Emerg Artif Intell Appl Comput Eng,2007

3. A direct LDA algorithm for high-dimensional data — with application to face recognition

4. Comparison of k-nearest neighbor, quadratic discriminant and linear discriminant analysis in classification of electromyogram signals based on the wrist-motion directions

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