Linear Algebra plays a pivotal role in image processing, enabling various matrix operations that profoundly impact image quality and manipulation. This research investigates the application of matrix ...

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 ...

NumPy includes some tools for working with linear algebra in the numpy.linalg module. However, unless you really don’t want to add SciPy as a dependency to your project, it’s typically better to use ...

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Issues are used to track todos, bugs, feature requests, and more.

Abstract: This book contains a detailed discussion of the matrix operation, its properties, and its applications in finding the solution of linear equations and determinants. Linear algebra is a ...

*Note: This course discription is only applicable to the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

ABSTRACT: The current paper is mainly devoted for solving centrosymmetric linear systems of equations. Formulae for the determinants of tridiagonal centrosymmetric matrices are obtained explicitly.

Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data transformations. Different books cater to various needs. Some focus on ...