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 ...
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 ...
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 ...
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 ...
Dr. James McCaffrey of Microsoft Research guides you through a full-code, step-by-step tutorial on "one of the most important operations in machine learning." Computing the inverse of a matrix is one ...
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 ...
We implement fixed-point matrix inversion on a Virtex-4 FPGA using a synthesizable QR-decomposition MATLAB model and the AccelDSP Synthesis tool. The resulting function occupies 12% of a XC4VSX55 ...
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