Matrix calculations are used in communications standards such as 3GPP-LTE, WiMAX, and many others. For example, the MIMO (Multi Input Multi Output) algorithm in the LTE receiver is based on a 4×4 ...

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 ...

There are pros and cons of each matrix inverse algorithm. In the early days of programming, when machines had limited memory and slow processors, the practical differences between matrix inverse ...

Inverting a matrix is one of the most common tasks in data science and machine learning. In this article I explain why inverting a matrix is very difficult and present code that you can use as-is, or ...

The algorithm is able to re-discover older matrix multiplication algorithms and improve upon its own to discover newer and faster algorithms. “AlphaTensor is the first AI system for discovering novel, ...

With Deep Reinforcement Learning, DeepMind has discovered an algorithm no human thought of. It is supposed to significantly accelerate matrix multiplication.

A Hong Kong-based Matrix AI Network is developing a prototype of a new hybrid PoS/PoW consensus algorithm. This update was shared with Cointelegraph by Owen Tao, the company’s CEO. Tao described ...

By Ramon Uribe and Tom Cesear, Xilinx October 12, 2006 -- dspdesignline.com We implement fixed-point matrix inversion on a Virtex-4 FPGA using a synthesizable QR-decomposition MATLAB model and the ...