白皮書

Eigenvalue decomposition using the Catapult Algorithmic Synthesis Methodology

Advanced algorithmic evaluation for imaging, communication and audio applications

Eigenvalue Decomposition depicted via a deconstructed camera.

This report discusses the hardware implementation of “eigenvalue decomposition”. Eigenvalue decomposition is used in a wide range of applications for imaging, communication and audio such as image recognition using KL conversion, high-speed communication using MIMO antenna, and electric/sound wave arrival direction estimation using MUSIC method.

It is expected that more than four antennas will be required in many cases for future MIMO communications and electric wave arrival direction estimation with MUSIC method applications. With four antennas, the matrix size will be 4x4 with complex numbers and the computational load will be increased, so we were interested in verifying whether the method to obtain eigenvalues directly from the eigenvalue equation was reasonable or not. Therefore, we developed two effective algorithms in ANSI C++ to obtain eigenvalues and synthesized them with Catapult® to compare the area versus the number of cycles at the algorithm level, respectively.

Share

相關資訊

Google 使用高階合成開發 WebM 視訊解壓縮硬體 IP
White Paper

Google 使用高階合成開發 WebM 視訊解壓縮硬體 IP

本白皮書還將介紹 WebM 團隊在成功實作 G2 VP9 時實際使用 Catapult HLS 的情況,並分享結果和感想。