The construction of bi-frames is a fundamental problem in frame theory. Due to their wide applications, the study of vector-valued frames and subspace frames has interested many mathematicians in ...

Abstract: Extraction of invariant features is a crucial process in pattern recognition. In this paper, a universal framework for encoding invariant features with sparse vectors is described. Using ...

Abstract: Principle component analysis (PCA) and its improved models have found wide applications in pattern recognition field. PCA is a common method applied to dimensionality reduction and feature ...

In this paper, we discuss subspace-based support vector machines (SS-SVMs), in which an input vector is classified into the class with the maximum similarity. Namely, for each class we define the ...