An adaptive implementation of a dynamically reconfigurable K-nearest neighbour classifier on FPGA

@article{Hussain2012AnAI,
  title={An adaptive implementation of a dynamically reconfigurable K-nearest neighbour classifier on FPGA},
  author={Hanaa M. Hussain and Khaled Benkrid and Huseyin Seker},
  journal={2012 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)},
  year={2012},
  pages={205-212}
}
K-nearest neighbour (KNN) is a supervised classification technique that is widely used in many fields of study to classify unknown queries based on some known information about the dataset. KNN is known to be robust and simple to implement when dealing with data of small size. However it performs slowly when data are large and have high dimensions. Therefore, KNN classifiers can benefit from the parallelism offered by Field Programmable Gate Arrays (FPGAs) to accelerate the algorithm. In… CONTINUE READING
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Manolakos and I . Stamoulias , “ IP - cores design for the kNN classifier

  • K. Benkrid Hussain, H. Seker

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