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Development of tool condition monitoring system in end milling process using wavelet features and Hoelder’s exponent with machine learning algorithms

, 2020
An effort was made to monitor the flank wear using wavelet analysis by extracting the Hoelder’s exponent as a feature and using various machine learning algorithms to forecast the tool condition.
T. Mohanraj +4 more
semanticscholar +1 more source

Calculus of the Exponent of Kurdyka–Łojasiewicz Inequality and Its Applications to Linear Convergence of First-Order Methods

Foundations of Computational Mathematics, 2016
In this paper, we study the Kurdyka–Łojasiewicz (KL) exponent, an important quantity for analyzing the convergence rate of first-order methods. Specifically, we develop various calculus rules to deduce the KL exponent of new (possibly nonconvex and ...
Guoyin Li, Ting Kei Pong
semanticscholar +1 more source

Kurdyka–Łojasiewicz Exponent via Inf-projection

Foundations of Computational Mathematics, 2021
Peiran Yu, Guoyin Li, Ting Kei Pong
semanticscholar +1 more source

Variable Exponent, Linear Growth Functionals in Image Restoration

SIAM Journal on Applied Mathematics, 2006
Yunmei Chen, Stacey Levine, M. Rao
semanticscholar +1 more source

Compact effective potentials and efficient shared‐exponent basis sets for the first‐ and second‐row atoms

, 1984
W. J. Stevens, H. Basch, M. Krauss
semanticscholar +1 more source

Nonlinear elliptic equations with variable exponent: Old and new

, 2015
Vicentiu D. Rădulescu
semanticscholar +1 more source

Angstrom exponent and bimodal aerosol size distributions

, 2006
G. Schuster, O. Dubovik, B. Holben
semanticscholar +1 more source

Approximation in Smirnov classes with variable exponent

, 2015
D. Israfilov, A. Testici
semanticscholar +1 more source