New bounds of the smoothing parameter for lattices. [PDF]
PLoS ONEThe smoothing parameter on lattices is crucial for lattice-based cryptographic design. In this study, we establish a new upper bound for the lattice smoothing parameter, which represents an improvement over several significant classical findings. For one-
Heng Guo +3 more
doaj +3 more sources
One Value of Smoothing Parameter vs Interval of Smoothing Parameter Values in Kernel Density Estimation [PDF]
Acta Universitatis Lodziensis. Folia Oeconomica, 2017 Ad hoc methods in the choice of smoothing parameter in kernel density estimation, although often used in practice due to their simplicity and hence the calculated efficiency, are characterized by quite big error.
Aleksandra Katarzyna Baszczyńska
doaj +4 more sources
Histogram Filter with Smoothing Parameter Setting
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki, 2023 A histogram filter with smoothing parameter settings is discussed in the article. The histogram filter can be effectively applied in the problems of identification (recognition) of distribution laws for small amounts of data.
A. V. Ausiannikau, V. M. Kozel
doaj +2 more sources
Robust Smoothing: Smoothing Parameter Selection and Applications to Fluorescence Spectroscopy. [PDF]
Comput Stat Data Anal, 2010 Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. We compare various robust smoothing methods for estimating fluorescence emission spectra and data driven methods for the ...
Lee JS, Cox DD.
europepmc +5 more sources
Reservoir characterization and porosity classification using probabilistic neural network (PNN) based on single and multi-smoothing parameters [PDF]
International Journal of Mining and Geo-Engineering, 2022 A probabilistic neural network (PNN) is a feed-forward neural network using a smoothing parameter. We used the PNN algorithm based on single and multi-smoothing parameters for multi-dimensional data classification.
Masood Lashkari Ahangarani +2 more
doaj +1 more source
Smoothing parameter selection in Nadaraya-Watson kernel nonparametric regression using nature-inspired algorithm optimization [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 In the context of Nadaraya-Watson kernel nonparametric regression, the curve estimation is fully depending on the smoothing parameter. At this point, the nature-inspired algorithms can be used as an alternative tool to find the optimal selection. In this
Zinah Basheer, Zakariya Algamal
doaj +1 more source
Smoothing splines with varying smoothing parameter [PDF]
Biometrika, 2013 This paper considers the development of spatially adaptive smoothing splines for the estimation of a regression function with non-homogeneous smoothness across the domain. Two challenging issues that arise in this context are the evaluation of the equivalent kernel and the determination of a local penalty.
Xiao Wang, Pang Du, Jinglai Shen
openaire +4 more sources
Analisis Error Terhadap Peramalan Data Penjualan
Techno.Com, 2021 Tujuan penelitian ini membahas tentang peramalan permintaan lampu LED bermerk Sanyo. Penelitian ini menggunakan metode Moving Average dan Exponential Smoothing.
Alyauma Hajjah, Yulvia Nora Marlim
doaj +1 more source
Smoothness Parameter of Power of Euclidean Norm [PDF]
Journal of Optimization Theory and Applications, 2020 AbstractIn this paper, we study derivatives of powers of Euclidean norm. We prove their Hölder continuity and establish explicit expressions for the corresponding constants. We show that these constants are optimal for odd derivatives and at most two times suboptimal for the even ones.
Rodomanov, Anton, Nesterov, Yurii
openaire +5 more sources
Spline estimator and its asymptotic properties in multiresponse nonparametric regression model [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2020 In applications, we often meet the problem where more than one response variable is observed at several values of predictor variables, and these responses are correlated with each other.
Budi Lestari +2 more
doaj +1 more source