Linear algebra serves as a foundational tool in image processing, bridging the gap between visual complexity and mathematical abstraction. With images represented as digital matrices, each pixel ...

ABSTRACT: In this paper, a series of bicomplex representation methods of quaternion division algebra is introduced. We present a new multiplication concept of quaternion matrices, a new determinant ...

Therefore, when we need to use linear algebra specific functions we'll load the scipy.linalg library. The first instance where we do this below is when we compute matrix inverses. NumPy Arrays Vectors ...

ABSTRACT: In this paper, a series of bicomplex representation methods of quaternion division algebra is introduced. We present a new multiplication concept of quaternion matrices, a new determinant ...

The central goals of most introductory linear algebra courses are to develop students' proficiency with matrix techniques, to promote their understanding of key concepts, and to increase their ability ...

Elementary set theory and solution sets of systems of linear equations. An introduction to proofs and the axiomatic methods through a study of the vector space axioms. Linear analytic geometry. Linear ...

Sparse linear algebra kernels achieve sub-optimal performance due to their poor cache locality. Matrix reordering is an effective pre-processing optimization that improves cache locality and ...