Spherical signals exist in many applications, e.g., planetary data, LiDAR scans and digitalization of 3D objects, calling for models that can process spherical data effectively. It does not perform well when simply projecting into the 2D plane then using planar convolution neural networks (CNNs), because distortion from projection ineffective translation equivariance. Actually, good principles ...

In this paper we report on the parallelization of a split-step algorithm for the Schrödinger equation. The problem is represented in spherical coordinates in physical space and transformed to Fourier space for operation by the Laplacian operator, and Legendre space for operation by the Angular momentum operator and the Potential operator. Timing results are reported and analyzed for 3 different...

This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuz...

In this paper, we investigate the multiple attribute decision making (MADM) problems with fuzzy linguistic information. Motivated by the ideal of generalized Bonferroni mean, we develop the generalized fuzzy linguistic Bonferroni Mean (GFLBM) operator for aggregating the fuzzy linguistic information. For the situations where the input arguments have different importance, we then define the gene...

Functions on the double coset space K\G/K, where G is a group and K is a subgroup of G are called spherical functions. One can also study functions on G/K with values in a representation V of G which are equivariant with respect to the left action of K. This more general class of functions may be called vector valued spherical functions. The theory of such functions was developed by Harish-Chan...