Abstract: Large matrix inversion is usually a basic step in a wide range of signal processing or numerical problems, such as digital filtering, equalization detection, and etc. It is essential to ...

This project implements matrix inversion using the Neumann series algorithm accelerated with CUDA. The objective is to approximate the inverse of a 64×64 matrix by exploiting GPU parallelism and ...

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 ...

Abstract: Several modern communication systems, such as G.fast-based copper transmission or LTE-based wireless systems, benefit from MIMO techniques to achieve higher capacity. In most of these ...

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 ...

Matrix inversion is an important operationin many state-of-the-art DSP algorithmsand implementations, includingradar, sonar, and multiple antenna systemsfor communications. A commoncomponent of these ...

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 ...

There was an error while loading. Please reload this page. Rank Calculation: Computes the rank of a matrix via manual Gaussian elimination and row reduction with ...