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\section{Conclusion}
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Within this paper a novel approach for rapid approximation of the KDE was presented.
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This is achieved by considering the discrete convolution structure of the BKDE and thus elaborate its connection to digital signal processing, especially the Gaussian filter.
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Using a box filter as an appropriate approximation results in an efficient computation scheme with a fully linear complexity and a negligible overhead, as confirmed by the utilized experiments.
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This is achieved by considering the discrete convolution structure of the BKDE and thus elaborating its connection to digital signal processing, especially the Gaussian filter.
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Using a box filter as an appropriate approximation results in an efficient computation scheme with a fully linear complexity and a negligible overhead, as demonstrated by the utilized experiments.
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The analysis of the error showed that the method exhibits an similar error behaviour compared to the BKDE.
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The analysis of the error showed that the method shows an similar error behaviour compared to the BKDE.
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In terms of calculation time, our approach outperforms other state of the art implementations.
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Despite being more efficient than other methods, the algorithmic complexity still increases in its exponent with increasing number of dimensions.
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Despite being more efficient than other methods, the algorithmic complexity still increases in its exponent with an increasing number of dimensions.
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%future work kurz
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Finally, such a fast computation scheme makes the KDE more attractive for real time use cases.
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