Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that ...

For high data rate wireless communications they use Orthogonal Frequency Division Multiplexing (OFDM) due to its high spectral efficiency and low computational complexity. It gives the architecture of ...

Complex matrix algebra is of great importance to a wide variety of applications. One of the most important application areas is telecommunications. Matrix calculations are used in communications ...

Researchers from the Institute for Artificial Intelligence at Peking University, led by Sun Zhong, have developed a ...