A Modified Parallel Learning Vector Quantization Algorithm for Real-Time Hardware Applications

Date

2017-10-01

Author

Alkim, Erdem
AKLEYLEK, SEDAT
KILIÇ, ERDAL

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This work is licensed under a 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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Citation Formats

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.