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A Modified Parallel Learning Vector Quantization Algorithm for Real-Time Hardware Applications
Date
2017-10-01
Author
Alkim, Erdem
AKLEYLEK, SEDAT
KILIÇ, ERDAL
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In this study a modified learning vector quantization (LVQ) algorithm is proposed. For this purpose, relevance LVQ (RLVQ) algorithm is effciently combined with a reinforcement mechanism. In this mechanism, it is shown that the proposed algorithm is not affected constantly by both relevance-irrelevance input dimensions and the winning of the same neuron. Hardware design of the proposed scheme is also given to illustrate the performance of the algorithm. The proposed algorithm is compared to the corresponding ones with regard to success rate and running time.
Subject Keywords
FPGA
,
LVQ
,
GLVQ
,
Reinforcement mechanism
URI
https://hdl.handle.net/11511/66720
Journal
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
DOI
https://doi.org/10.1142/s0218126617501560
Collections
Graduate School of Applied Mathematics, Article
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E. Alkim, S. AKLEYLEK, and E. KILIÇ, “A Modified Parallel Learning Vector Quantization Algorithm for Real-Time Hardware Applications,”
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
, pp. 0–0, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66720.