Often, we work with vector spaces which consists of an appropriate. Many concepts concerning vectors in Rn can be extended to other mathematical systems. We can think of a vector space in.of a finite-dimensional nontrivial proper subspace of such a vector space is equivalent to ACA0 over RCA0. This paper is a continuation of 3.Subspaces of Vector Spaces. A subspace W of a vector space V is a su...

Hyperspectral image (HSI) clustering is a challenging task due to the high complexity of HSI data. Subspace has been proven be powerful for exploiting intrinsic relationship between data points. Despite impressive performance in clustering, traditional subspace methods often ignore inherent structural information among In this article, we revisit with graph convolution and present novel framewo...

This paper presents a new subspace modeling and selection approach for noisy speech recognition. In subspace modeling, we develop factor analysis (FA) for representing noisy speech. FA is a data generation model where the common factors are extracted with factor loading matrix and specific factors. We bridge the connection of FA to signal subspace (SS) approach. Interestingly, FA partitions noi...

Abstract We study the problem of determining minimum number $f(n,k,d)$ affine subspaces codimension $d$ that are required to cover all points $\mathbb{F}_2^n\setminus \{\vec{0}\}$ at least $k$ times while covering origin most $k - 1$ times. The case $k=1$ is a classic result Jamison, which was independently obtained by Brouwer and Schrijver for $d = . value $f(n,1,1)$ also follows from well-kno...

A new guideline for proper allocation of multipoles in the multiple multipole method (MMP) is proposed. In an ‘a posteriori’ approach, subspace fitting (SSF) is used to find the best location of multipole expansions for the two dimensional dielectric scattering problem. It is shown that the best location of multipole expansions (regarding their global approximating power) coincides with the med...