Breakdown of the Sonine expansion for the velocity distribution of granular gases
, 2006 The velocity distribution of a granular gas is analyzed in terms of the Sonine polynomials expansion. We derive an analytical expression for the third Sonine coefficient a3.
T. Pöschel +3 more
core +1 more source
A survey of kernel and spectral methods for clustering [PDF]
, 2007 Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with a special interest in two recent approaches: kernel and spectral methods ...
Masulli, F. +11 more
core +1 more source
Applying the possibilistic C-means algorithm in kernel-induced spaces [PDF]
, 2010 In this paper, we study a kernel extension of the classic possibilistic c-means. In the proposed extension, we implicitly map input patterns into a possibly high-dimensional space by means of positive semidefinite kernels. In this new space, we model the
Masulli, F. +5 more
core +1 more source
On Symmetrical Sonin Kernels in Terms of Hypergeometric-Type Functions
MathematicsIn this paper, a new class of kernels of integral transforms of the Laplace convolution type that we named symmetrical Sonin kernels is introduced and investigated. For a symmetrical Sonin kernel given in terms of elementary or special functions, its associated kernel has the same form with possibly different parameter values. In the paper, several new
openaire +2 more sources
Kernel-based clustering via Isolation Distributional Kernel
, 2023 Clustering has become one of the widely used automatic data-labeling techniques applied in a variety of disciplines. Kernel-based clustering is a technique designed to identify non-linearly separable clusters with irregular shapes.
Ye Zhu (13101348), KM Ting (13907250)
core
Time fractional Yang-Abdel-Cattani derivative in generalized MHD Casson fluid flow with heat source and chemical reaction. [PDF]
Sci Rep, 2023 Sehra, Sadia H, Haq SU, Khan I.
europepmc +1 more source
Hierarchic Bayesian models for kernel learning [PDF]
, 2005 The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance when compared to that obtained from any single data source.
Rogers, S. +3 more
core +1 more source
High-Degree Collisional Moments of Inelastic Maxwell Mixtures-Application to the Homogeneous Cooling and Uniform Shear Flow States. [PDF]
Entropy (Basel), 2023 Sánchez Romero C, Garzó V.
europepmc +1 more source
General Non-Markovian Quantum Dynamics. [PDF]
Entropy (Basel), 2021 Tarasov VE.
europepmc +1 more source
Improved Quantum-Classical Treatment of N2-N2 Inelastic Collisions: Effect of the Potentials and Complete Rate Coefficient Data Sets. [PDF]
J Chem Theory Comput, 2023 Hong Q +5 more
europepmc +1 more source