Introduces linear algebra and matrices, with an emphasis on applications, including methods to solve systems of linear algebraic and linear ordinary differential equations. Discusses computational ...

Abstract In this paper, we first study the solution to linear matrix inequality AXB + (AXB)* ⩾ (>, ⩽, <) C when the matrix G = (A B*) is full row rank, where C is a Hermitian matrix. Furthermore, for ...

AI training time is at a point in an exponential where more throughput isn't going to advance functionality much at all. The underlying problem, problem solving by training, is computationally ...

This is a preview. Log in through your library . Abstract The use of moment matrices and their determinants are shown to elucidate the structure of mixture estimation as carried out using the method ...

Nonnegative Matrix Factorization (NMF) has emerged as a powerful tool in data analysis, particularly noted for its ability to produce parts‐based, interpretable representations from high-dimensional ...

Maximum distance separable (MDS) matrices play a critical role in the design of secure cryptographic systems by ensuring optimal diffusion in block ciphers and related schemes. Owing to their ...

The objectives of this course are: to develop competence in the basic concepts of linear algebra, including systems of linear equations, vector spaces, subspaces, linear transformations, the ...